Encouraging practitioners in infection prevention and control to publish: a cross-sectional survey

Aim: The aim of this cross-sectional survey was to determine the views of infection prevention and control practitioners (IPCPs) on publishing research. Methods: A convenience sample was obtained by approaching delegates at the 2015 Infection Prevention Society conference and data was captured via a hand-held electronic device. Findings: Of the 79 respondents most (83%) read Journal of Infection Prevention (JIP) and found it useful for informing their practice (72%). However, most (91%) had never published in JIP, and less than half (40%) published elsewhere. The main barrier to publication was not having work suitable for publication (38%). Support (37%), training in writing for publication (10%) and time (9%) were considered to be important facilitators in encouraging respondents to publish. Discussion: Strategies that support IPCPs in developing their writing skills may encourage more IPCPs to disseminate evidence to support best practice by publishing their work in peer reviewed journals

ASSESSING VARIABILITY OF AGREEMENT MEASURES IN REMOTE SENSING USING A BAYESIAN APPROACH

Remote sensing imagery is a popular accessment tool in agriculture, forestry, and rangeland management. Spectral classification of imagery provides a means of estimating production and identifYing potential problems, such as weed, insect, and disease infestations. Accuracy of classification is traditionally based on ground truthing and summary statistics such as Cohen\u27s Kappa. Variability assessment and comparison of these quantities have been limited to asymptotic procedures relying on large sample sizes and gaussian distributions. However, asymptotic methods fail to take into account the underlying distribution of the classified data and may produce invalid inferential results. Bayesian methodology is introduced to develop probability distributions for Cohen\u27s Conditional Kappa that can subsequently be used for image assessment and comparison. Techniques are demonstrated on a set of images used in identifYing a species of weed, yellow starthistle, at various spatial resolutions and flying times

ESTIMATING THE LIKELIHOOD OF YELLOW STARTHISTLE OCCURRENCE USING AN EMPIRICALLY DERIVED NONLINEAR REGRESSION MODEL

Yellow starthistle is a noxious weed common in the semiarid climate of Central Idaho and other western states. Early detection of yellow starthistle and predicting its infestation potential have important scientific and managerial implications. Weed detection and delineation are often carried out by visual observation or survey techniques. However, such methods may be ineffective in detecting sparse infestations. The distribution of yellow starthistle over a large region may be affected by various exogenous variables such as elevation, slope and aspect. These landscape variables can be used to develop prediction models to estimate the potential invasion of yellow starthistle into new areas. A nonlinear prediction model has been developed based on a polar coordinate transformation to investigate the ability of landscape characteristics to predict the likelihood of yellow starthistle occurrence in North Central Idaho. The study region included the lower Snake river and parts of the Salmon and Clearwater basins encompassing various land use categories. The model provided accurate estimates of incidence of yellow starthistle within each specified land use category and performed well in subsequent statistical validations

MODELING DISPERSAL OF YELLOW STARTHISTLE IN THE CANYON GRASSLANDS OF NORTH CENTRAL IDAHO

Yellow starthistle is an invasive plant species that reduces productivity and plant diversity within the canyon grasslands of Idaho. Early detection of yellow starthistle and predicting its spread have important managerial implications that could greatly reduce the economic/environmental losses due to this weed. The spread of an invasive plant species depends on its ability to reproduce and disperse seed into new areas. Typically, information on the factors that directly affect a plant’s ability to reproduce and subsequently disperse seed is not available or difficult to obtain. Alternatively, topographic factors, such as slope and aspect as well as competitive correlates such as vegetation indices related to plant community biomass could be used to model plant survival and seed movement. In this research, several spatial network models incorporating these variables were considered for the prediction of yellow starthistle dispersal. Models will differed in their assessment of plant movement costs, which can be separated into two processes, survival to reproduction and seed dispersal. The candidate models were evaluated based on their predictive ability and biological relevance. Topographical variables, slope and aspect, were found to be significant contributors to yellow starthistle dispersal models, whereas vegetation indices did not improve the prediction process. The optimal model was applied to an area in central Idaho for predicting the dispersal of yellow starthistle in 1987 given a known 1981 infestation

PREDICTION OF YELLOW STARTHISTLE SURVIVAL AND MOVEMENT OVER TIME AND SPACE

Yellow starthistle is a noxious weed that has become a serious plant pest with devastating impact on ranching operation and natural resources in western states. Early detection of yellow starthistle and predicting its spread has important managerial implications and greatly reduce the economic losses due to this weed. The dispersal of yellow starthistle consists of two main components, plant survival and seed movement. Resources and direct factors relating to these components are not typically available or are difficult to obtain. Alternatively, topographic factors, such as slope, aspect and elevation, are readily available and can be related to plant survival and seed movement. In this study, several GIS network models incorporating these topographic factors are considered for the prediction of yellow starthistle spread. The models differed in their assessment of the costs of movement derived from these factors. Models were evaluated based on their predictive ability and residual analysis. The optimal model gave an accurate estimate of the dispersal boundary for the study area. Further validation of the estimated model using an independent data set from a larger area also verified its predictive capability

Sex Hormone-Binding Globulin Levels Are Inversely Associated With Nonalcoholic Fatty Liver Disease in HIV-Infected and -Uninfected Men.

BackgroundNonalcoholic fatty liver disease (NAFLD) is a leading cause of liver disease worldwide. Elevated sex hormone-binding globulin (SHBG) levels have been observed in the setting of HIV and may protect against some metabolic disorders. We aimed to investigate whether higher SHBG levels may protect against NAFLD in men with/without HIV.MethodsNAFLD was assessed using noncontrast computed tomography in 530 men in the Multicenter AIDS Cohort Study (MACS) who drank <3 alcoholic drinks/d and were uninfected with chronic hepatitis C or B (340HIV+, 190HIV-). Morning serum samples were tested for SHBG, total testosterone (TT), and adiponectin. Multivariable logistic regression was used to assess associations between HIV, SHBG, TT, adiponectin, and NAFLD.ResultsMedian SHBG was highest among HIV+/NAFLD- men and lowest among HIV-/NAFLD+ men. Adjusted for demographics, HIV, visceral adiposity, HOMA-IR, TT, and PNPLA3 genotype, higher SHBG was associated with lower odds of NAFLD (odds ratio [OR], 0.52 per doubling; 95% confidence interval [CI], 0.34-0.80). In separate multivariable models without SHBG, HIV (OR, 0.46; 95% CI, 0.26-0.79) and higher adiponectin (OR, 0.66 per doubling; 95% CI, 0.49-0.89) were associated with lower NAFLD odds, whereas TT was not significantly associated (OR, 0.74 per doubling; 95% CI, 0.53-1.04). Adjusting for SHBG attenuated the associations of HIV (OR, 0.61; 95% CI, 0.34-1.08) and adiponectin (OR, 0.74; 95% CI, 0.54-1.02) with NAFLD.ConclusionsSHBG levels were higher among HIV+ men, were independently associated with lower NAFLD, and could partially explain the associations of HIV and higher adiponectin with lower NAFLD in our cohort. These findings suggest that SHBG may protect against NAFLD, supporting further prospective and mechanistic studies

Water Contaminants Associated With Unconventional Oil and Gas Extraction Cause Immunotoxicity to Amphibian Tadpoles

Chemicals associated with unconventional oil and gas (UOG) operations have been shown to contaminate surface and ground water with a variety of endocrine disrupting compounds (EDCs) inducing multiple developmental alteration in mice. However, little is known about the impacts of UOG-associated contaminants on amphibian health and resistance to an emerging ranavirus infectious disease caused by viruses in the genus Ranavirus, especially at the vulnerable tadpole stage. Here we used tadpoles of the amphibian Xenopus laevis and the ranavirus Frog virus 3 (FV3) as a model relevant to aquatic environment conservation research for investigating the immunotoxic effects of exposure to a mixture of 23 UOG-associated chemicals with EDC activity. Xenopus tadpoles were exposed to an equimass mixture of 23 UOG-associated chemicals (range from 0.1 to 10 µg/l) for 3 weeks prior to infection with FV3. Our data show that exposure to the UOG chemical mixture is toxic for tadpoles at ecological doses of 5 to 10 µg/l. Lower doses significantly altered homeostatic expression of myeloid lineage genes and compromised tadpole responses to FV3 through expression of TNF-α, IL-1β, and Type I IFN genes, correlating with an increase in viral load. Exposure to a subset of 6 UOG chemicals was still sufficient to perturb the antiviral gene expression response. These findings suggest that UOG-associated water pollutants at low but environmentally relevant doses have the potential to induce acute alterations of immune function and antiviral immunity

Landing Gear Components Noise Study - PIV and Hot-Wire Measurements

PIV and hot-wire measurements of the wake flow from rods and bars are presented. The test models include rods of different diameters and cross sections and a rod juxtaposed to a plate. The latter is representative of the latch door that is attached to an aircraft landing gear when the gear is deployed, while the single and multiple rod configurations tested are representative of some of the various struts and cables configuration present on an aircraft landing gear. The test set up is described and the flow measurements are presented. The effect of model surface treatment and freestream turbulence on the spanwise coherence of the vortex shedding is studied for several rod and bar configurations