Suitability and limitations of portion-specific abattoir data as part of an early warning system for emerging diseases of swine in Ontario

<p>Abstract</p> <p>Background</p> <p>Abattoir data have the potential to provide information for geospatial disease surveillance applications, but the quality of the data and utility for detecting disease outbreaks is not well understood. The objectives of this study were to 1) identify non-disease factors that may bias these data for disease surveillance and 2) determine if major disease events that took place during the study period would be captured using multi-level modelling and scan statistics. We analyzed data collected at all provincially-inspected abattoirs in Ontario, Canada during 2001-2007. During these years there were outbreaks of porcine circovirus-associated disease (PCVAD), porcine reproductive and respiratory syndrome (PRRS) and swine influenza that produced widespread disease within the province. Negative binomial models with random intercepts for abattoir, to account for repeated measurements within abattoirs, were created. The relationships between partial carcass condemnation rates for pneumonia and nephritis with year, season, agricultural region, stock price, and abattoir processing capacity were explored. The utility of the spatial scan statistic for detecting clusters of high partial carcass condemnation rates in space, time, and space-time was investigated.</p> <p>Results</p> <p>Non-disease factors that were found to be associated with lung and kidney condemnation rates included abattoir processing capacity, agricultural region and season. Yearly trends in predicted condemnation rates varied by agricultural region, and temporal patterns were different for both types of condemnations. Some clusters of high condemnation rates of kidneys with nephritis in time and space-time preceded the timeframe during which case clusters were detected using traditional laboratory data. Yearly kidney condemnation rates related to nephritis lesions in eastern Ontario were most consistent with the trends that were expected in relation to the documented disease outbreaks. Yearly lung condemnation rates did not correspond with the timeframes during which major respiratory disease outbreaks took place.</p> <p>Conclusions</p> <p>This study demonstrated that a number of abattoir-related factors require consideration when using abattoir data for quantitative disease surveillance. Data pertaining to lungs condemned for pneumonia did not provide useful information for predicting disease events, while partial carcass condemnations of nephritis were most consistent with expected trends. Techniques that adjust for non-disease factors should be considered when applying cluster detection methods to abattoir data.</p

Hydrodynamic attraction of swimming microorganisms by surfaces

Cells swimming in confined environments are attracted by surfaces. We measure the steady-state distribution of smooth-swimming bacteria (Escherichia coli) between two glass plates. In agreement with earlier studies, we find a strong increase of the cell concentration at the boundaries. We demonstrate theoretically that hydrodynamic interactions of the swimming cells with solid surfaces lead to their re-orientation in the direction parallel to the surfaces, as well as their attraction by the closest wall. A model is derived for the steady-state distribution of swimming cells, which compares favorably with our measurements. We exploit our data to estimate the flagellar propulsive force in swimming E. coli

NF-κB-mediated effects on behavior and cartilage pathology in a non-invasive loading model of post-traumatic osteoarthritis

OBJECTIVE: This study aimed to examine the temporal activation of NF-κB and its relationship to the development of pain-related sensitivity and behavioral changes in a non-invasive murine knee loading model of PTOA. METHOD: Following knee injury NF-κB activity was assessed longitudinally via in vivo imaging in FVB. Cg-Tg (HIV-EGFP,luc)8Tsb/J mice. Measures of pain-related sensitivity and behavior were also assessed longitudinally for 16 weeks. Additionally, we antagonized NF-κB signaling via intra-articular delivery of an IκB kinase two antagonist to understand how local NF-κB inhibition might alter disease progression. RESULTS: Following joint injury NF-κB signaling within the knee joint was transiently increased and peaked on day 3 with an estimated 1.35 p/s/cm CONCLUSION: These findings underscore the development of behavioral changes in this non-invasive loading model of PTOA and their relationships to NF-κB activation and pathology. They also highlight the potential chondroprotective effects of NF-κB inhibition shortly following joint injury despite limitations in preventing the long-term development of joint degeneration in this model of PTOA

LGP2 plays a critical role in sensitizing mda-5 to activation by double-stranded RNA.

The DExD/H box RNA helicases retinoic acid-inducible gene-I (RIG-I) and melanoma differentiation associated gene-5 (mda-5) sense viral RNA in the cytoplasm of infected cells and activate signal transduction pathways that trigger the production of type I interferons (IFNs). Laboratory of genetics and physiology 2 (LGP2) is thought to influence IFN production by regulating the activity of RIG-I and mda-5, although its mechanism of action is not known and its function is controversial. Here we show that expression of LGP2 potentiates IFN induction by polyinosinic-polycytidylic acid [poly(I:C)], commonly used as a synthetic mimic of viral dsRNA, and that this is particularly significant at limited levels of the inducer. The observed enhancement is mediated through co-operation with mda-5, which depends upon LGP2 for maximal activation in response to poly(I:C). This co-operation is dependent upon dsRNA binding by LGP2, and the presence of helicase domain IV, both of which are required for LGP2 to interact with mda-5. In contrast, although RIG-I can also be activated by poly(I:C), LGP2 does not have the ability to enhance IFN induction by RIG-I, and instead acts as an inhibitor of RIG-I-dependent poly(I:C) signaling. Thus the level of LGP2 expression is a critical factor in determining the cellular sensitivity to induction by dsRNA, and this may be important for rapid activation of the IFN response at early times post-infection when the levels of inducer are low

Magnetic Field-Induced Condensation of Triplons in Han Purple Pigment BaCuSi2_2O6_6

Besides being an ancient pigment, BaCuSi$_2$O$_6$ is a quasi-2D magnetic insulator with a gapped spin dimer ground state. The application of strong magnetic fields closes this gap creating a gas of bosonic spin triplet excitations called triplons. The topology of the spin lattice makes BaCuSi$_2$O$_6$ an ideal candidate for studying the Bose-Einstein condensation of triplons as a function of the external magnetic field, which acts as a chemical potential. In agreement with quantum Monte Carlo numerical simulations, we observe a distinct lambda-anomaly in the specific heat together with a maximum in the magnetic susceptibility upon cooling down to liquid Helium temperatures.Comment: published on August 20, 200

Investigating the spatial risk distribution of West Nile virus disease in birds and humans in southern Ontario from 2002 to 2005

<p>Abstract</p> <p>Background</p> <p>The West Nile virus (WNv) became a veterinary public health concern in southern Ontario in 2001 and has continued to threaten public health. Wild bird mortality has been shown to be an indicator for tracking the geographic distribution of the WNv. The purpose of this study was to investigate the latent risk distribution of WNv disease among dead birds and humans in southern Ontario and to compare the spatial risk patterns for the period 2002–2005. The relationship between the mortality fraction in birds and incidence rate in humans was also investigated.</p> <p>Methods</p> <p>Choropleth maps were created to investigate the spatial variation in bird and human WNv risk for the public health units of southern Ontario. The data were smoothed by empirical Bayesian estimation before being mapped. Isopleth risk maps for both the bird and human data were created to identify high risk areas and to investigate the potential relationship between the WNv mortality fraction in birds and incidence rates in humans. This was carried out by the geostatistical prediction method of kriging. A Poisson regression analysis was used to model regional human WNv case counts as a function of the spatial coordinates in the east and north direction and the regional bird mortality fractions. The presence of disease clustering and the location of disease clusters were investigated by the spatial scan test.</p> <p>Results</p> <p>The isopleth risk maps exhibited high risk areas that were relatively constant from year to year. There was an overlap in the bird and human high risk areas, which occurred in the central-west and south-west areas of southern Ontario. The annual WNv cause-specific mortality fractions in birds for 2002 to 2005 were 31.9, 22.0, 19.2 and 25.2 positive birds per 100 birds tested, respectively. The annual human WNv incidence rates for 2002 to 2005 were 2.21, 0.76, 0.13 and 2.10 human cases per 100,000 population, respectively. The relative risk of human WNv disease was 0.72 times lower for a public health unit that was 100 km north of another public health unit. The relative risk of human WNv disease increased by the factor 1.44 with every 10 positive birds per 100 tested. The scan statistic detected disease cluster in the bird and human data. The human clusters were not significant, when the analysis was conditioned on the bird data.</p> <p>Conclusion</p> <p>The study indicates a significant relationship between the spatial pattern of WNv risk in humans and birds.</p

Using built environment characteristics to predict walking for exercise

Background: Environments conducive to walking may help people avoid sedentary lifestyles and associated diseases. Recent studies developed walkability models combining several built environment characteristics to optimally predict walking. Developing and testing such models with the same data could lead to overestimating one's ability to predict walking in an independent sample of the population. More accurate estimates of model fit can be obtained by splitting a single study population into training and validation sets (holdout approach) or through developing and evaluating models in different populations. We used these two approaches to test whether built environment characteristics near the home predict walking for exercise. Study participants lived in western Washington State and were adult members of a health maintenance organization. The physical activity data used in this study were collected by telephone interview and were selected for their relevance to cardiovascular disease. In order to limit confounding by prior health conditions, the sample was restricted to participants in good self-reported health and without a documented history of cardiovascular disease. Results: For 1,608 participants meeting the inclusion criteria, the mean age was 64 years, 90 percent were white, 37 percent had a college degree, and 62 percent of participants reported that they walked for exercise. Single built environment characteristics, such as residential density or connectivity, did not significantly predict walking for exercise. Regression models using multiple built environment characteristics to predict walking were not successful at predicting walking for exercise in an independent population sample. In the validation set, none of the logistic models had a C-statistic confidence interval excluding the null value of 0.5, and none of the linear models explained more than one percent of the variance in time spent walking for exercise. We did not detect significant differences in walking for exercise among census areas or postal codes, which were used as proxies for neighborhoods. Conclusion: None of the built environment characteristics significantly predicted walking for exercise, nor did combinations of these characteristics predict walking for exercise when tested using a holdout approach. These results reflect a lack of neighborhood-level variation in walking for exercise for the population studied.University of Washington Royalty Research fund award; by contracts R01-HL043201, R01-HL068639, and T32-HL07902 from the National Heart, Lung, and Blood Institute; and by grant R01-AG09556 from the National Institute on Aging

Just urban transitions: Toward a research agenda

While there are excellent policy and academic foundations for thinking about and making sense of urban climate action and questions of justice and climate change independently, there is less work that considers their intersection. The nature and dynamics of, and requirements for, a just urban transition (JUT)—the fusion of climate action and justice concerns at the urban scale—are not well understood. In this review article we seek to rectify this by first examining the different strains of justice scholarship (environmental, energy, climate, urban) that are informing and should inform JUT. We then turn to a discussion of just transitions in general, tracing the history of the term and current understandings in the literature. These two explorations provide a foundation for considering both scholarly and policy‐relevant JUT agendas. We identify what is still needed to know in order to recognize, study, and foster JUT.This article is categorized under:The Carbon Economy and Climate Mitigation > Benefits of MitigationClimate, Nature, and Ethics > Climate Change and Global JusticeJust urban transitions research and policy agendas center alternative urban futures: cities where the distribution of environmental risks and benefits do not disproportionately burden marginalized groups; where decision‐making is transparent, engaged, and democratic; and where policies seek to remedy structural inequalities and prior injustices.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154981/1/wcc640_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154981/2/wcc640.pd

Long-Term Functionality of Rural Water Services in Developing Countries: A System Dynamics Approach to Understanding the Dynamic Interaction of Causal Factors

Research has shown that sustainability of rural water infrastructure in developing countries is largely affected by the dynamic and systemic interactions of technical, social, financial, institutional, and environmental factors that can lead to premature water system failure. This research employs systems dynamic modeling, which uses feedback mechanisms to understand how these factors interact dynamically to influence long-term rural water system functionality. To do this, the research first identified and aggregated key factors from literature, then asked water sector experts to indicate the polarity and strength between factors through Delphi and cross impact survey questionnaires, and finally used system dynamics modeling to identify and prioritize feedback mechanisms. The resulting model identified 101 feedback mechanisms that were dominated primarily by three and four-factor loops that contained some combination of the factors: Water System Functionality, Community, Financial, Government, Management, and Technology. These feedback mechanisms were then scored and prioritized, with the most dominant feedback mechanism identified as Water System Functionality – Community – Finance – Management. This research offers insight into the dynamic interaction of factors impacting sustainability of rural water infrastructure through the identification of these feedback mechanisms and makes a compelling case for future research to longitudinally investigate the interaction of these factors in various contexts