Application of a Swab Sampling Method for the Detection of Norovirus and Rotavirus on Artificially Contaminated Food and Environmental Surfaces

Noroviruses and rotaviruses are the leading causes of non-bacterial gastroenteritis in humans worldwide. Virus-contaminated food and surfaces represent an important risk to public health. However, established detection methods for the viruses in food products are laborious and time-consuming. Here, we describe a detailed swabbing protocol combined with real-time RT-PCR for norovirus and rotavirus detection on artificially contaminated food and environmental surfaces. Recovery rates between 2 and 78% for norovirus and between 8 and 42% for rotavirus were determined for contaminated food surfaces of apple, pepper, cooked ham and salami. From contaminated environmental surfaces (stainless steel, ceramic plate, polyethylene, wood), recovery rates between 26 and 52% (norovirus) and between 10 and 58% (rotavirus) were determined. The results demonstrate the suitability of the swab sample method for virus detection on food and environmental surfaces. Compared to other methods, it is easy to perform and significantly time-saving, predestining it for routine testing.     

Distribution of14C-TNT and derivatives in different biochemical compartments ofPhaseolus vulgaris

¹⁴C-TNT was used to quantify the uptake rate and metabolic turnover of TNT inPhaseolus vulgaris. Seventeen plants were analysed by a special cell fractionation method with polar and nonpolar solvents and enzymes. We obtained three cytoplasmic fractions and five cell wall derived fractions. The recovery rate was 72% as measured by liquid scintillation counting.¹⁴C partitioned almost in equal amounts with approximately 50% in the cytoplasm and in the cell wall. The majority of the TNT-metabolites are present in the cytoplasm as was shown by GC/ ECD and thin layer chromatography. The¹⁴C in the cell wall is bound probably resulting in long-term immobilisation of these metabolites. We conclude that plants may also be a model for nitroaromatic turnover and immobilisation in soil components.     

Pedestrians' estimates of their own visibility: a simple and effective computer-based technique

INTRODUCTION: Research has shown that both pedestrians and drivers drastically overestimate pedestrians' nighttime visibility (NHSTSA, 2008a, 2008b; Owens & Sivak, 1996) and fail to appreciate the safety benefits of proven conspicuity aids. One solution is educational intervention (Tyrrell, Patton, & Brooks, 2004); however, the on-road assessment of its effectiveness is expensive and time consuming. METHOD: Experiment One introduces a computer-based alternative to the field-based approach, successfully replicating the previous study's trends among 94 students who either receive or do not receive an educational lecture. Experiment Two utilizes the simulation's portability to determine if professional roadway workers have a more accurate understanding of pedestrian conspicuity than students. Results: Results among 88 workers show they do not significantly appreciate the advantages of effective retroflective material configurations or vehicle headlamp settings, for example, any better than non-lectured students in Experiment One. Impact: The study's results demonstrate the need for education among all pedestrians and the benefits of efficient testing methods.     

Software for prioritizing conservation actions based on probabilistic information

Marxan is the most common decision-support tool used to inform the design of protected-area systems. The original version of Marxan does not consider risk and uncertainty associated with threatening processes affecting protected areas, including uncertainty about the location and condition of species’ populations and habitats now and in the future. We described and examined the functionality of a modified version of Marxan, Marxan with Probability. This software explicitly considers 4 types of uncertainty: probability that a feature exists in a particular place (estimated based on species distribution models or spatially explicit population models); probability that features in a site will be lost in the future due to a threatening process, such as climate change, natural catastrophes, and uncontrolled human interventions; probability that a feature will exist in the future due to natural successional processes, such as a fire or flood; and probability the feature exists but has been degraded by threatening processes, such as overfishing or pollution, and thus cannot contribute to conservation goals. We summarized the results of 5 studies that illustrate how each type of uncertainty can be used to inform protected area design. If there were uncertainty in species or habitat distribution, users could maximize the chance that these features were represented by including uncertainty using Marxan with Probability. Similarly, if threatening processes were considered, users minimized the chance that species or habitats were lost or degraded by using Marxan with Probability. Marxan with Probability opens up substantial new avenues for systematic conservation planning research and application by agencies.     

Beach macro-litter monitoring on southern Baltic beaches: results,experiences and recommendations

Major objectives were to provide a comprehensive dataset on beach macro-litter for parts of the southern Baltic Sea and to analyse if the methodology is fully applicable and a suitable monitoring method in the Baltic. We carried out a regular macro litter beach monitoring (OSPAR methodology, 4 time a year) on 35 beaches along the German and Lithuanian Baltic coast over 2–5 years. Additional experiments addressed the subjectivity of the field surveys and spatio-temporal variability on different scales. We observed no seasonality of the data and a monthly compared to a 3-monthly sampling resulted in 3 times higher annual item numbers. Along the Lithuanian coast, the average number of items per survey varied between 138 and 340 and along the German Baltic coast between 7 and 404, with a median value of 47. All data showed a very high spatio-temporal variability. Using the Matrix Scoring Technique we assessed beach litter sources. With 50% tourism and recreation was the most important source. 3D–transport simulations helped to explain the minor role of shipping as a source and, compared to the North Sea, the low numbers of items on German Baltic beaches. Floating litter had a short duration time in the western Baltic Sea and offshore drift dominated. Further, the common regular beach cleanings reduced the potential for local litter accumulation and translocation. We suggest a monitoring system on 14 Baltic beaches in Germany and 2 in Lithuania and provide cost calculations. The analysis of macro-litter in cormorant nesting material and the search for beached dead animals did not show any result. We can conclude that the macro-litter beach monitoring method is less suitable for Baltic beaches and should only serve as a complementary method in combination with others.     

An ecotoxicological view on neurotoxicity assessment

The numbers of potential neurotoxicants in the environment are raising and pose a great risk for humans and the environment. Currently neurotoxicity assessment is mostly performed to predict and prevent harm to human populations. Despite all the efforts invested in the last years in developing novel in vitro or in silico test systems, in vivo tests with rodents are still the only accepted test for neurotoxicity risk assessment in Europe. Despite an increasing number of reports of species showing altered behaviour, neurotoxicity assessment for species in the environment is not required and therefore mostly not performed. Considering the increasing numbers of environmental contaminants with potential neurotoxic potential, eco-neurotoxicity should be also considered in risk assessment. In order to do so novel test systems are needed that can cope with species differences within ecosystems. In the field, online-biomonitoring systems using behavioural information could be used to detect neurotoxic effects and effect-directed analyses could be applied to identify the neurotoxicants causing the effect. Additionally, toxic pressure calculations in combination with mixture modelling could use environmental chemical monitoring data to predict adverse effects and prioritize pollutants for laboratory testing. Cheminformatics based on computational toxicological data from in vitro and in vivo studies could help to identify potential neurotoxicants. An array of in vitro assays covering different modes of action could be applied to screen compounds for neurotoxicity. The selection of in vitro assays could be guided by AOPs relevant for eco-neurotoxicity. In order to be able to perform risk assessment for eco-neurotoxicity, methods need to focus on the most sensitive species in an ecosystem. A test battery using species from different trophic levels might be the best approach. To implement eco-neurotoxicity assessment into European risk assessment, cheminformatics and in vitro screening tests could be used as first approach to identify eco-neurotoxic pollutants. In a second step, a small species test battery could be applied to assess the risks of ecosystems.