Population-level effect of HSV-2 therapy on the incidence of HIV in sub-Saharan Africa.

BACKGROUND: Herpes simplex virus type 2 (HSV-2) infection increases acquisition and transmission of HIV, but the results of trials measuring the impact of HSV-2 therapy on HIV genital shedding and HIV acquisition are mixed, and the potential impact of HSV-2 therapy on the incidence of HIV at the population level is unknown. METHODS: The effects of episodic and suppressive HSV-2 therapy were simulated using the individual-level model STDSIM fitted to data from Cotonou, Benin (relatively low HIV prevalence) and Kisumu, Kenya (high HIV prevalence). Clinician- and patient-initiated episodic therapy, started when symptomatic, were assumed to reduce ulcer duration. Suppressive therapy, given regardless of symptoms, was also assumed to reduce ulcer frequency and HSV-2 infectiousness. RESULTS: Clinician-initiated episodic therapy in the general population had almost no effect on the incidence of HIV. The impact of patient-initiated therapy was higher because of earlier treatment initiation, but still low (20% in the long term. Impact was increased in both cities by also treating a proportion of their clients. Long-term suppressive therapy with high coverage in the general population could reduce HIV incidence by more than 30%. CONCLUSIONS: These results show that HSV-2 therapy could potentially have a population-level impact on the incidence of HIV, especially in more concentrated epidemics. However, a substantial impact requires high coverage and long duration therapy, or very high symptom recognition and treatment-seeking behaviour

Elementary processes governing the evolution of road networks

Urbanisation is a fundamental phenomenon whose quantitative characterisation is still inadequate. We report here the empirical analysis of a unique data set regarding almost 200 years of evolution of the road network in a large area located north of Milan (Italy). We find that urbanisation is characterised by the homogenisation of cell shapes, and by the stability throughout time of high-centrality roads which constitute the backbone of the urban structure, confirming the importance of historical paths. We show quantitatively that the growth of the network is governed by two elementary processes: (i) `densification', corresponding to an increase in the local density of roads around existing urban centres and (ii) `exploration', whereby new roads trigger the spatial evolution of the urbanisation front. The empirical identification of such simple elementary mechanisms suggests the existence of general, simple properties of urbanisation and opens new directions for its modelling and quantitative description.Comment: 10 pages, 6 figure

Junction resolving enzymes use multivalency to keep the Holliday junction dynamic

Holliday junction (HJ) resolution by resolving enzymes is essential for chromosome segregation and recombination-mediated DNA repair. HJs undergo two types of structural dynamics that determine the outcome of recombination: conformer exchange between two isoforms and branch migration. However, it is unknown how the preferred branch point and conformer are achieved between enzyme binding and HJ resolution given the extensive binding interactions seen in static crystal structures. Single-molecule fluorescence resonance energy transfer analysis of resolving enzymes from bacteriophages (T7 endonuclease I), bacteria (RuvC), fungi (GEN1) and humans (hMus81-Eme1) showed that both types of HJ dynamics still occur after enzyme binding. These dimeric enzymes use their multivalent interactions to achieve this, going through a partially dissociated intermediate in which the HJ undergoes nearly unencumbered dynamics. This evolutionarily conserved property of HJ resolving enzymes provides previously unappreciated insight on how junction resolution, conformer exchange and branch migration may be coordinated.11Nsciescopu

Choosing sensitivity analyses for randomised trials: principles

Background Sensitivity analyses are an important tool for understanding the extent to which the results of randomised trials depend upon the assumptions of the analysis. There is currently no guidance governing the choice of sensitivity analyses. Discussion We provide a principled approach to choosing sensitivity analyses through the consideration of the following questions: 1) Does the proposed sensitivity analysis address the same question as the primary analysis? 2) Is it possible for the proposed sensitivity analysis to return a different result to the primary analysis? 3) If the results do differ, is there any uncertainty as to which will be believed? Answering all of these questions in the affirmative will help researchers to identify relevant sensitivity analyses. Treating analyses as sensitivity analyses when one or more of the answers are negative can be misleading and confuse the interpretation of studies. The value of these questions is illustrated with several examples. Summary By removing unreasonable analyses that might have been performed, these questions will lead to relevant sensitivity analyses, which help to assess the robustness of trial results

Exoplanets and SETI

The discovery of exoplanets has both focused and expanded the search for extraterrestrial intelligence. The consideration of Earth as an exoplanet, the knowledge of the orbital parameters of individual exoplanets, and our new understanding of the prevalence of exoplanets throughout the galaxy have all altered the search strategies of communication SETI efforts, by inspiring new "Schelling points" (i.e. optimal search strategies for beacons). Future efforts to characterize individual planets photometrically and spectroscopically, with imaging and via transit, will also allow for searches for a variety of technosignatures on their surfaces, in their atmospheres, and in orbit around them. In the near-term, searches for new planetary systems might even turn up free-floating megastructures.Comment: 9 page invited review. v2 adds some references and v3 has other minor additions and modification

Co-evolution of density and topology in a simple model of city formation

We study the influence that population density and the road network have on each others' growth and evolution. We use a simple model of formation and evolution of city roads which reproduces the most important empirical features of street networks in cities. Within this framework, we explicitely introduce the topology of the road network and analyze how it evolves and interact with the evolution of population density. We show that accessibility issues -pushing individuals to get closer to high centrality nodes- lead to high density regions and the appearance of densely populated centers. In particular, this model reproduces the empirical fact that the density profile decreases exponentially from a core district. In this simplified model, the size of the core district depends on the relative importance of transportation and rent costs.Comment: 13 pages, 13 figure

Hierarchy measure for complex networks

Nature, technology and society are full of complexity arising from the intricate web of the interactions among the units of the related systems (e.g., proteins, computers, people). Consequently, one of the most successful recent approaches to capturing the fundamental features of the structure and dynamics of complex systems has been the investigation of the networks associated with the above units (nodes) together with their relations (edges). Most complex systems have an inherently hierarchical organization and, correspondingly, the networks behind them also exhibit hierarchical features. Indeed, several papers have been devoted to describing this essential aspect of networks, however, without resulting in a widely accepted, converging concept concerning the quantitative characterization of the level of their hierarchy. Here we develop an approach and propose a quantity (measure) which is simple enough to be widely applicable, reveals a number of universal features of the organization of real-world networks and, as we demonstrate, is capable of capturing the essential features of the structure and the degree of hierarchy in a complex network. The measure we introduce is based on a generalization of the m-reach centrality, which we first extend to directed/partially directed graphs. Then, we define the global reaching centrality (GRC), which is the difference between the maximum and the average value of the generalized reach centralities over the network. We investigate the behavior of the GRC considering both a synthetic model with an adjustable level of hierarchy and real networks. Results for real networks show that our hierarchy measure is related to the controllability of the given system. We also propose a visualization procedure for large complex networks that can be used to obtain an overall qualitative picture about the nature of their hierarchical structure.Comment: 29 pages, 9 figures, 4 table

Sociological and Communication-Theoretical Perspectives on the Commercialization of the Sciences

Both self-organization and organization are important for the further development of the sciences: the two dynamics condition and enable each other. Commercial and public considerations can interact and "interpenetrate" in historical organization; different codes of communication are then "recombined." However, self-organization in the symbolically generalized codes of communication can be expected to operate at the global level. The Triple Helix model allows for both a neo-institutional appreciation in terms of historical networks of university-industry-government relations and a neo-evolutionary interpretation in terms of three functions: (i) novelty production, (i) wealth generation, and (iii) political control. Using this model, one can appreciate both subdynamics. The mutual information in three dimensions enables us to measure the trade-off between organization and self-organization as a possible synergy. The question of optimization between commercial and public interests in the different sciences can thus be made empirical.Comment: Science & Education (forthcoming

Academic Performance and Behavioral Patterns

Identifying the factors that influence academic performance is an essential part of educational research. Previous studies have documented the importance of personality traits, class attendance, and social network structure. Because most of these analyses were based on a single behavioral aspect and/or small sample sizes, there is currently no quantification of the interplay of these factors. Here, we study the academic performance among a cohort of 538 undergraduate students forming a single, densely connected social network. Our work is based on data collected using smartphones, which the students used as their primary phones for two years. The availability of multi-channel data from a single population allows us to directly compare the explanatory power of individual and social characteristics. We find that the most informative indicators of performance are based on social ties and that network indicators result in better model performance than individual characteristics (including both personality and class attendance). We confirm earlier findings that class attendance is the most important predictor among individual characteristics. Finally, our results suggest the presence of strong homophily and/or peer effects among university students