Measured Dynamic Social Contact Patterns Explain the Spread of H1N1v Influenza

Patterns of social mixing are key determinants of epidemic spread. Here we present the results of an internet-based social contact survey completed by a cohort of participants over 9,000 times between July 2009 and March 2010, during the 2009 H1N1v influenza epidemic. We quantify the changes in social contact patterns over time, finding that school children make 40% fewer contacts during holiday periods than during term time. We use these dynamically varying contact patterns to parameterise an age-structured model of influenza spread, capturing well the observed patterns of incidence; the changing contact patterns resulted in a fall of approximately 35% in the reproduction number of influenza during the holidays. This work illustrates the importance of including changing mixing patterns in epidemic models. We conclude that changes in contact patterns explain changes in disease incidence, and that the timing of school terms drove the 2009 H1N1v epidemic in the UK. Changes in social mixing patterns can be usefully measured through simple internet-based surveys

Rapid detection of pandemic influenza in the presence of seasonal influenza

Background: Key to the control of pandemic influenza are surveillance systems that raise alarms rapidly and sensitively. In addition, they must minimise false alarms during a normal influenza season. We develop a method that uses historical syndromic influenza data from the existing surveillance system 'SERVIS' (Scottish Enhanced Respiratory Virus Infection Surveillance) for influenza-like illness (ILI) in Scotland. Methods: We develop an algorithm based on the weekly case ratio (WCR) of reported ILI cases to generate an alarm for pandemic influenza. From the seasonal influenza data from 13 Scottish health boards, we estimate the joint probability distribution of the country-level WCR and the number of health boards showing synchronous increases in reported influenza cases over the previous week. Pandemic cases are sampled with various case reporting rates from simulated pandemic influenza infections and overlaid with seasonal SERVIS data from 2001 to 2007. Using this combined time series we test our method for speed of detection, sensitivity and specificity. Also, the 2008-09 SERVIS ILI cases are used for testing detection performances of the three methods with a real pandemic data. Results: We compare our method, based on our simulation study, to the moving-average Cumulative Sums (Mov-Avg Cusum) and ILI rate threshold methods and find it to be more sensitive and rapid. For 1% case reporting and detection specificity of 95%, our method is 100% sensitive and has median detection time (MDT) of 4 weeks while the Mov-Avg Cusum and ILI rate threshold methods are, respectively, 97% and 100% sensitive with MDT of 5 weeks. At 99% specificity, our method remains 100% sensitive with MDT of 5 weeks. Although the threshold method maintains its sensitivity of 100% with MDT of 5 weeks, sensitivity of Mov-Avg Cusum declines to 92% with increased MDT of 6 weeks. For a two-fold decrease in the case reporting rate (0.5%) and 99% specificity, the WCR and threshold methods, respectively, have MDT of 5 and 6 weeks with both having sensitivity close to 100% while the Mov-Avg Cusum method can only manage sensitivity of 77% with MDT of 6 weeks. However, the WCR and Mov-Avg Cusum methods outperform the ILI threshold method by 1 week in retrospective detection of the 2009 pandemic in Scotland. Conclusions: While computationally and statistically simple to implement, the WCR algorithm is capable of raising alarms, rapidly and sensitively, for influenza pandemics against a background of seasonal influenza. Although the algorithm was developed using the SERVIS data, it has the capacity to be used at other geographic scales and for different disease systems where buying some early extra time is critical

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

The Embodiment of Success and Failure as Forward versus Backward Movements

People often speak of success (e.g., “advance”) and failure (e.g., “setback”) as if they were forward versus backward movements through space. Two experiments sought to examine whether grounded associations of this type influence motor behavior. In Experiment 1, participants categorized success versus failure words by moving a joystick forward or backward. Failure categorizations were faster when moving backward, whereas success categorizations were faster when moving forward. Experiment 2 removed the requirement to categorize stimuli and used a word rehearsal task instead. Even without Experiment 1’s response procedures, a similar cross-over interaction was obtained (e.g., failure memorizations sped backward movements relative to forward ones). The findings are novel yet consistent with theories of embodied cognition and self-regulation

Effects of Irritant Chemicals on Aedes aegypti Resting Behavior: Is There a Simple Shift to Untreated “Safe Sites”?

Aedes aegypti, the primary vector mosquito of dengue virus, typically lives near or inside human dwellings, and feeds preferentially on humans. The control of this mosquito vector remains the most important dengue prevention method. The use of chemicals at levels toxic to mosquitoes is currently the only confirmed effective adult vector control strategy with interventions usually applied following epidemic onset. However, research indicates that sub-lethal chemical approaches to prevent human-vector contact at the house level exist: contact irritancy and spatial repellency. The optimum efficacy of an intervention based on contact irritant actions of chemicals will, however, require full knowledge of variables that will influence vector resting behavior and thereby chemical uptake from treated sources. Here we characterize the resting patterns of female Ae. aegypti on two material types at various dark:light surface area coverage ratios and contrast configurations under chemical-free and treated conditions using a laboratory behavioral assay. Change in resting behavior between baseline and treatment conditions was quantified to determine potential negative effects of untreated surfaces (“safe sites”) when irritant responses are elicited. We show that treatment of preferred resting sites with known irritant compounds do not stimulate mosquitoes to move to safe sites after making contact with treated surfaces

Genome-wide inference of regulatory networks in Streptomyces coelicolor

Background: The onset of antibiotics production in Streptomyces species is co-ordinated with differentiation events. An understanding of the genetic circuits that regulate these coupled biological phenomena is essential to discover and engineer the pharmacologically important natural products made by these species. The availability of genomic tools and access to a large warehouse of transcriptome data for the model organism, Streptomyces coelicolor, provides incentive to decipher the intricacies of the regulatory cascades and develop biologically meaningful hypotheses. Results: In this study, more than 500 samples of genome-wide temporal transcriptome data, comprising wild-type and more than 25 regulatory gene mutants of Streptomyces coelicolor probed across multiple stress and medium conditions, were investigated. Information based on transcript and functional similarity was used to update a previously-predicted whole-genome operon map and further applied to predict transcriptional networks constituting modules enriched in diverse functions such as secondary metabolism, and sigma factor. The predicted network displays a scale-free architecture with a small-world property observed in many biological networks. The networks were further investigated to identify functionally-relevant modules that exhibit functional coherence and a consensus motif in the promoter elements indicative of DNA-binding elements. Conclusions: Despite the enormous experimental as well as computational challenges, a systems approach for integrating diverse genome-scale datasets to elucidate complex regulatory networks is beginning to emerge. We present an integrated analysis of transcriptome data and genomic features to refine a whole-genome operon map and to construct regulatory networks at the cistron level in Streptomyces coelicolor. The functionally-relevant modules identified in this study pose as potential targets for further studies and verification.

Genetic variants in novel pathways influence blood pressure and cardiovascular disease risk.

Blood pressure is a heritable trait influenced by several biological pathways and responsive to environmental stimuli. Over one billion people worldwide have hypertension (≥140 mm Hg systolic blood pressure or  ≥90 mm Hg diastolic blood pressure). Even small increments in blood pressure are associated with an increased risk of cardiovascular events. This genome-wide association study of systolic and diastolic blood pressure, which used a multi-stage design in 200,000 individuals of European descent, identified sixteen novel loci: six of these loci contain genes previously known or suspected to regulate blood pressure (GUCY1A3-GUCY1B3, NPR3-C5orf23, ADM, FURIN-FES, GOSR2, GNAS-EDN3); the other ten provide new clues to blood pressure physiology. A genetic risk score based on 29 genome-wide significant variants was associated with hypertension, left ventricular wall thickness, stroke and coronary artery disease, but not kidney disease or kidney function. We also observed associations with blood pressure in East Asian, South Asian and African ancestry individuals. Our findings provide new insights into the genetics and biology of blood pressure, and suggest potential novel therapeutic pathways for cardiovascular disease prevention

Increased food production and reduced water use through optimized crop distribution

Growing demand for agricultural commodities for food, fuel and other uses is expected to be met through an intensification of production on lands that are currently under cultivation. Intensification typically entails investments in modern technology - such as irrigation or fertilizers - and increases in cropping frequency in regions suitable for multiple growing seasons. Here we combine a process-based crop water model with maps of spatially interpolated yields for 14 major food crops to identify potential differences in food production and water use between current and optimized crop distributions. We find that the current distribution of crops around the world neither attains maximum production nor minimum water use. We identify possible alternative configurations of the agricultural landscape that, by reshaping the global distribution of crops within current rainfed and irrigated croplands based on total water consumption, would feed an additional 825 million people while reducing the consumptive use of rainwater and irrigation water by 14% and 12%, respectively. Such an optimization process does not entail a loss of crop diversity, cropland expansion or impacts on nutrient and feed availability. It also does not necessarily invoke massive investments in modern technology that in many regions would require a switch from smallholder farming to large-scale commercial agriculture with important impacts on rural livelihoods

Measurement of the cross section for inclusive isolated-photon production in pp collisions at √s=13TeV using the ATLAS detector

Inclusive isolated-photon production in pp collisions at a centre-of-mass energy of 13TeVis studied with the ATLAS detector at the LHC using a data set with an integrated luminosity of 3.2fb−1. The cross section is measured as a function of the photon transverse energy above 125GeVin different regions of photon pseudorapidity. Next-to-leading-order perturbative QCD and Monte Carlo event-generator predictions are compared to the cross-section measurements and provide an adequate description of the data