Social Networks Shape the Transmission Dynamics of Hepatitis C Virus

Hepatitis C virus (HCV) infects 170 million people worldwide, and is a major public health problem in Brazil, where over 1% of the population may be infected and where multiple viral genotypes co-circulate. Chronically infected individuals are both the source of transmission to others and are at risk for HCV-related diseases, such as liver cancer and cirrhosis. Before the adoption of anti-HCV control measures in blood banks, this virus was mainly transmitted via blood transfusion. Today, needle sharing among injecting drug users is the most common form of HCV transmission. Of particular importance is that HCV prevalence is growing in non-risk groups. Since there is no vaccine against HCV, it is important to determine the factors that control viral transmission in order to develop more efficient control measures. However, despite the health costs associated with HCV, the factors that determine the spread of virus at the epidemiological scale are often poorly understood. Here, we sequenced partial NS5b gene sequences sampled from blood samples collected from 591 patients in Sao Paulo state, Brazil. We show that different viral genotypes entered Sao Paulo at different times, grew at different rates, and are associated with different age groups and risk behaviors. In particular, subtype 1b is older and grew more slowly than subtypes 1a and 3a, and is associated with multiple age classes. In contrast, subtypes 1a and 3b are associated with younger people infected more recently, possibly with higher rates of sexual transmission. The transmission dynamics of HCV in Sao Paulo therefore vary by subtype and are determined by a combination of age, risk exposure and underlying social network. We conclude that social factors may play a key role in determining the rate and pattern of HCV spread, and should influence future intervention policies.

Chain motifs: The tails and handles of complex networks

A great part of the interest in complex networks has been motivated by the presence of structured, frequently nonuniform, connectivity. Because diverse connectivity patterns tend to result in distinct network dynamics, and also because they provide the means to identify and classify several types of complex network, it becomes important to obtain meaningful measurements of the local network topology. In addition to traditional features such as the node degree, clustering coefficient, and shortest path, motifs have been introduced in the literature in order to provide complementary descriptions of the network connectivity. The current work proposes a different type of motif, namely, chains of nodes, that is, sequences of connected nodes with degree 2. These chains have been subdivided into cords, tails, rings, and handles, depending on the type of their extremities (e.g., open or connected). A theoretical analysis of the density of such motifs in random and scale-free networks is described, and an algorithm for identifying these motifs in general networks is presented. The potential of considering chains for network characterization has been illustrated with respect to five categories of real-world networks including 16 cases. Several interesting findings were obtained, including the fact that several chains were observed in real-world networks, especially the world wide web, books, and the power grid. The possibility of chains resulting from incompletely sampled networks is also investigated.

Communication structure of cortical networks

Large-scale cortical networks exhibit characteristic topological properties that shape communication between brain regions and global cortical dynamics. Analysis of complex networks allows the description of connectedness, distance, clustering, and centrality that reveal different aspects of how the network's nodes communicate. Here, we focus on a novel analysis of complex walks in a series of mammalian cortical networks that model potential dynamics of information flow between individual brain regions. We introduce two new measures called absorption and driftness. Absorption is the average length of random walks between any two nodes, and takes into account all paths that may diffuse activity throughout the network. Driftness is the ratio between absorption and the corresponding shortest path length. For a given node of the network, we also define four related measurements, namely in-and out-absorption as well as in-and out-driftness, as the averages of the corresponding measures from all nodes to that node, and from that node to all nodes, respectively. We find that the cat thalamo-cortical system incorporates features of two classic network topologies, Erdos-Renyi graphs with respect to in-absorption and in-driftness, and configuration models with respect to out-absorption and out-driftness. Moreover, taken together these four measures separate the network nodes based on broad functional roles (visual, auditory, somatomotor, and frontolimbic).

Connectivity and dynamics of neuronal networks as defined by the shape of individual neurons

Biological neuronal networks constitute a special class of dynamical systems, as they are formed by individual geometrical components, namely the neurons. In the existing literature, relatively little attention has been given to the influence of neuron shape on the overall connectivity and dynamics of the emerging networks. The current work addresses this issue by considering simplified neuronal shapes consisting of circular regions (soma/axons) with spokes (dendrites). Networks are grown by placing these patterns randomly in the two-dimensional (2D) plane and establishing connections whenever a piece of dendrite falls inside an axon. Several topological and dynamical properties of the resulting graph are measured, including the degree distribution, clustering coefficients, symmetry of connections, size of the largest connected component, as well as three hierarchical measurements of the local topology. By varying the number of processes of the individual basic patterns, we can quantify relationships between the individual neuronal shape and the topological and dynamical features of the networks. Integrate-and-fire dynamics on these networks is also investigated with respect to transient activation from a source node, indicating that long-range connections play an important role in the propagation of avalanches.

The impact of measurement errors in the identification of regulatory networks

Background: There are several studies in the literature depicting measurement error in gene expression data and also, several others about regulatory network models. However, only a little fraction describes a combination of measurement error in mathematical regulatory networks and shows how to identify these networks under different rates of noise. Results: This article investigates the effects of measurement error on the estimation of the parameters in regulatory networks. Simulation studies indicate that, in both time series (dependent) and non-time series (independent) data, the measurement error strongly affects the estimated parameters of the regulatory network models, biasing them as predicted by the theory. Moreover, when testing the parameters of the regulatory network models, p-values computed by ignoring the measurement error are not reliable, since the rate of false positives are not controlled under the null hypothesis. In order to overcome these problems, we present an improved version of the Ordinary Least Square estimator in independent (regression models) and dependent (autoregressive models) data when the variables are subject to noises. Moreover, measurement error estimation procedures for microarrays are also described. Simulation results also show that both corrected methods perform better than the standard ones (i.e., ignoring measurement error). The proposed methodologies are illustrated using microarray data from lung cancer patients and mouse liver time series data. Conclusions: Measurement error dangerously affects the identification of regulatory network models, thus, they must be reduced or taken into account in order to avoid erroneous conclusions. This could be one of the reasons for high biological false positive rates identified in actual regulatory network models.

The development of social tourism in Brazil

This article reflects on the origins and development of social tourism in Brazil, with particular reference to the socio-economic conditions in the country. It discusses the theoretical conceptualisation of social tourism and its implementations in the non-European context. The case study presented here is based on a secondary bibliographical research of existing definitions and an in-depth analysis of the political conditions that have framed its development. More particularly, this article will discuss public initiatives since the Labour Party gained power in Brazil in 2003. Apart from public sector involvement in social tourism, this article also examines the role of the third sector in provision. The example of Social Service of Commerce will be presented. This article will conclude by evaluating the phenomenon of social tourism in Brazil, highlighting where progress has been made and which are the key challenges that need to be overcome.

Reconfiguration of distribution networks to minimize loss and disruption costs using genetic algorithms

In this paper a computational implementation of an evolutionary algorithm (EA) is shown in order to tackle the problem of reconfiguring radial distribution systems. The developed module considers power quality indices such as long duration interruptions and customer process disruptions due to voltage sags, by using the Monte Carlo simulation method. Power quality costs are modeled into the mathematical problem formulation, which are added to the cost of network losses. As for the EA codification proposed, a decimal representation is used. The EA operators, namely selection, recombination and mutation, which are considered for the reconfiguration algorithm, are herein analyzed. A number of selection procedures are analyzed, namely tournament, elitism and a mixed technique using both elitism and tournament. The recombination operator was developed by considering a chromosome structure representation that maps the network branches and system radiality, and another structure that takes into account the network topology and feasibility of network operation to exchange genetic material. The topologies regarding the initial population are randomly produced so as radial configurations are produced through the Prim and Kruskal algorithms that rapidly build minimum spanning trees. (C) 2009 Elsevier B.V. All rights reserved.

Bait and Habitat Preferences, and Temporal Variability of Social Wasps (Hymenoptera: Vespidae) Attracted to Vertebrate Carrion

In addition to feeding on carrion tissues and fluids, social wasps can also prey on immature and adult carrion flies, thereby reducing their populations and retarding the decomposition process of carcasses. In this study, we report on the occurrence and behavior of social wasps attracted to vertebrate carrion. The collections were made monthly from September 2006 to October 2007 in three environments (rural, urban, and forest) in six municipalities of southeast Brazil, using baited bottle traps. We collected Agelaia pallipes (Olivier, 1791) (n = 143), Agelaia vicina (Saussure, 1854) (n = 106), Agelaia multipicta (Haliday, 1836) (n = 18), and Polybia paulista Ihering, 1896 (n = 3). The wasps were observed feeding directly on the baits and preying on adult insects collected in the traps. Bait and habitat associations, temporal variability of social wasps, and possible forensic implications of their actions are discussed.

Trypanosoma cruzi: Effects of social stress in Calomys callosus a natural reservoir of infection

Social environment can represent a major source of stress affecting cortisol and/or corticosterone levels, thereby altering the immune response. We have investigated the effects of social isolation on the development of Trypanosoma cruzi infection in female Calomys callosus, a natural reservoir of this protozoan parasite. Animals were divided in groups of five animals each. The animals of one group were kept together in a single cage. In a second group, four females were kept together in a cage with one male. In the final group, five individuals were kept isolated in private cages. The isolated animals showed body weight reduction, decreased numbers of peritoneal macrophages, lower global leucocytes counts, smaller lytic antibody percentage and a significantly higher level of blood parasites compared to the other animals. Their behavior was also altered. They were more aggressive than grouped females, or females exposed to the presence of a male. These results suggest that isolation creates a distinct social behavior in which immunity is impaired and pathogenesis is enhanced. (C) 2008 Elsevier Inc. All rights reserved.

A comparison of social structures in Rio de Janeiro and Sao Paulo

This article presents the results of a comparative study on socio-spatial structures in Rio de Janeiro and Sao Paulo in 2000. We drew on data from the national Demographic Census by weighted areas to construct the Erikson, Goldthorpe, and Portocarrero (EGP) classification and the International Socio-Economic Index (ISEI), both widely used in social stratification studies. This information was then submitted to group analyses for the two cities, allowing comparison of the presence of social groups in each city. Next, using spatial statistics, we assessed the spatial distribution of the socio-economic classes and the presence of social segregation in the two metropolitan areas. The results suggest the presence of strong similarity between the social structures in the two cities, also marked by similarly intense patterns of social segregation at the metropolitan level.

Response to AIDS in Brazil: contributions of social movements and the sanitary reform

This paper briefly outlines how the political scenario and the mobilization of different actors have contributed to the construction of a public health policy in response to the AIDS epidemics in Brazil. Three factors are presented and discussed: the political context of the 1980s, characterized by redemocratization, growth of social movements, and consolidation of the Brazilian health care reform; the socio-cultural context of the 1970s and 1980s, characterized by achievement of individual freedom, which was key to the organization of the AIDS movement; and finally the actions carried out in the international scenario to support the sustainability of the Brazilian domestic policy and the reinforcement of a global response to face the epidemics in lower-middle income economies.

Insulin-like peptide genes in honey bee fat body respond differently to manipulation of social behavioral physiology

Nutrient sensitive insulin-like peptides (ILPs) have profound effects on invertebrate metabolism, nutrient storage, fertility and aging. Many insects transcribe ILPs in specialized neurosecretory cells at changing levels correlated with life history. However, the major site of insect metabolism and nutrient storage is not the brain, but rather the fat body, where functions of ILP expression are rarely studied and poorly understood. Fat body is analogous to mammalian liver and adipose tissue, with nutrient stores that often correlate with behavior. We used the honey bee (Apis mellifera), an insect with complex behavior, to test whether ILP genes in fat body respond to experimentally induced changes of behavioral physiology. Honey bee fat body influences endocrine state and behavior by secreting the yolk protein precursor vitellogenin (Vg), which suppresses lipophilic juvenile hormone and social foraging behavior. In a two-factorial experiment, we used RNA interference (RNAi)-mediated vg gene knockdown and amino acid nutrient enrichment of hemolymph (blood) to perturb this regulatory module. We document factor-specific changes in fat body ilp1 and ilp2 mRNA, the bee`s ILP-encoding genes, and confirm that our protocol affects social behavior. We show that ilp1 and ilp2 are regulated independently and differently and diverge in their specific expression-localization between fat body oenocyte and trophocyte cells. Insect ilp functions may be better understood by broadening research to account for expression in fat body and not only brain.

MODELING THE EVOLUTION OF COMPLEX NETWORKS THROUGH THE PATH-STAR TRANSFORMATION AND OPTIMAL MULTIVARIATE METHODS

The topology of real-world complex networks, such as in transportation and communication, is always changing with time. Such changes can arise not only as a natural consequence of their growth, but also due to major modi. cations in their intrinsic organization. For instance, the network of transportation routes between cities and towns ( hence locations) of a given country undergo a major change with the progressive implementation of commercial air transportation. While the locations could be originally interconnected through highways ( paths, giving rise to geographical networks), transportation between those sites progressively shifted or was complemented by air transportation, with scale free characteristics. In the present work we introduce the path-star transformation ( in its uniform and preferential versions) as a means to model such network transformations where paths give rise to stars of connectivity. It is also shown, through optimal multivariate statistical methods (i.e. canonical projections and maximum likelihood classification) that while the US highways network adheres closely to a geographical network model, its path-star transformation yields a network whose topological properties closely resembles those of the respective airport transportation network.

Sensitivity of complex networks measurements

Complex networks obtained from real-world networks are often characterized by incompleteness and noise, consequences of imperfect sampling as well as artifacts in the acquisition process. Because the characterization, analysis and modeling of complex systems underlain by complex networks are critically affected by the quality and completeness of the respective initial structures, it becomes imperative to devise methodologies for identifying and quantifying the effects of the sampling on the network structure. One way to evaluate these effects is through an analysis of the sensitivity of complex network measurements to perturbations in the topology of the network. In this paper, measurement sensibility is quantified in terms of the relative entropy of the respective distributions. Three particularly important kinds of progressive perturbations to the network are considered, namely, edge suppression, addition and rewiring. The measurements allowing the best balance of stability (smaller sensitivity to perturbations) and discriminability (separation between different network topologies) are identified with respect to each type of perturbation. Such an analysis includes eight different measurements applied on six different complex networks models and three real-world networks. This approach allows one to choose the appropriate measurements in order to obtain accurate results for networks where sampling bias cannot be avoided-a very frequent situation in research on complex networks.

On the efficiency of data representation on the modeling and characterization of complex networks

Specific choices about how to represent complex networks can have a substantial impact on the execution time required for the respective construction and analysis of those structures. In this work we report a comparison of the effects of representing complex networks statically by adjacency matrices or dynamically by adjacency lists. Three theoretical models of complex networks are considered: two types of Erdos-Renyi as well as the Barabasi-Albert model. We investigated the effect of the different representations with respect to the construction and measurement of several topological properties (i.e. degree, clustering coefficient, shortest path length, and betweenness centrality). We found that different forms of representation generally have a substantial effect on the execution time, with the sparse representation frequently resulting in remarkably superior performance. (C) 2011 Elsevier B.V. All rights reserved.