Hematodinium sp. infection in Norway lobster Nephrops norvegicus and its effects on meat quality

Hematodinium and Hematodinium-like species have emerged in the last 3 decades as important parasitic pathogens of crustaceans worldwide, causing a significant economic loss to fisheries and related markets. In some species (notably the Tanner crab Chionoecetes bairdi), the parasite reportedly causes the cooked meat to taste bitter and aspirin-like. The bitter taste, together with the gross pathology of the infection, renders these crabs unmarketable. Surprisingly, no organoleptic tests have ever been conducted to date, and the cause for the bitter taste is still unknown. Nevertheless, it is generally assumed that the bitter taste occurs widely in cooked meats and products derived from crustaceans infected with Hematodinium. In the present study, we analysed the meat quality and organoleptic attributes after capture and during storage of Norway lobsters Nephrops norvegicus from Scottish waters that were either asymptomatic or symptomatic of patent Hematodinium infection. Results from the sensory evaluation of the cooked product indicate that tail meat from symptomatic N. norvegicus is bland in flavour and aftertaste, and more friable or sloppier in texture than meat from asymptomatic animals. As a consequence, infected meat tends to be less palatable, although surprisingly no bitter taste is reported. From an analytical point of view, tail meat from patently infected animals is at an advanced stage of auto - lysis, while no difference in microbial load is detected. These results suggest that Norway lobsters heavily infected with Hematodinium are of inferior marketing quality even after the tails have been cooked

Teaching mathematics for search using a tutorial style of delivery

Understanding of mathematics is needed to underpin the process of search, either explicitly with Exact Match (Boolean logic, adjacency) or implicitly with Best match natural language search. In this paper we outline some pedagogical challenges in teaching mathematics for information retrieval (IR) to postgraduate information science students. The aim is to take these challenges either found by experience or in the literature, to identify both theoretical and practical ideas in order to improve the delivery of the material and positively affect the learning of the target audience by using a tutorial style of teaching. Results show that there is evidence to support the notion that a more pro-active style of teaching using tutorials yield benefits both in terms of assessment results and student satisfaction

An Extended Gene Protein/Products Boolean Network Model Including Post-Transcriptional Regulation

Background: Networks Biology allows the study of complex interactions between biological systems using formal, well structured, and computationally friendly models. Several different network models can be created, depending on the type of interactions that need to be investigated. Gene Regulatory Networks (GRN) are an effective model commonly used to study the complex regulatory mechanisms of a cell. Unfortunately, given their intrinsic complexity and non discrete nature, the computational study of realistic-sized complex GRNs requires some abstractions. Boolean Networks (BNs), for example, are a reliable model that can be used to represent networks where the possible state of a node is a boolean value (0 or 1). Despite this strong simplification, BNs have been used to study both structural and dynamic properties of real as well as randomly generated GRNs. Results: In this paper we show how it is possible to include the post-transcriptional regulation mechanism (a key process mediated by small non-coding RNA molecules like the miRNAs) into the BN model of a GRN. The enhanced BN model is implemented in a software toolkit (EBNT) that allows to analyze boolean GRNs from both a structural and a dynamic point of view. The open-source toolkit is compatible with available visualization tools like Cytoscape and allows to run detailed analysis of the network topology as well as of its attractors, trajectories, and state-space. In the paper, a small GRN built around the mTOR gene is used to demonstrate the main capabilities of the toolkit. Conclusions: The extended model proposed in this paper opens new opportunities in the study of gene regulation. Several of the successful researches done with the support of BN to understand high-level characteristics of regulatory networks, can now be improved to better understand the role of post-transcriptional regulation for example as a network-wide noise-reduction or stabilization mechanism

Real-world emissions from non-road mobile machinery in London

The 2016 London atmospheric emissions inventory estimates that, the construction sector contributes 34% of the total PM 10 and 7% of the total NO X – the largest and 5 th largest sources, respectively. Recent on-road light duty diesel vehicle emission tests have shown significant differences between real-world NO X emissions compared with results from laboratory based regulatory tests. The aim of this study was therefore to quantify the ‘real-world’ tail-pipe NO X, CO 2, and particle emissions, for 30 of the most commonly used construction machines in London under normal working conditions. The highest NO X emissions (g/kWh) were from the older engines (Stage III-A ~4.88 g/kWh and III-B ~4.61 g/kWh), these were reduced significantly (~78%) in the newer (Stage IV ~1.05 g/kWh) engines due to more advanced engine management systems and exhaust after treatment. One Stage IV machine emitted NO X similar to a Stage III-B machine, the failure of this SCR was only detectable using PEMS as no warning was given by the machine. Higher NO X conformity factors were observed for Stage IV machines, due to the lower NO X emission standards, which these machines must adhere to. On average, Stage III-B machines (~525 g/kWh) emitted the lowest levels of CO 2 emissions, compared to Stage III-A (~875 g/kWh) and Stage IV (~575 g/kWh) machines. Overall, a statistically significant (~41%) decrease was observed in the CO 2 emissions (g/kWh) between Stage III-A and III-B machines, while no statistically significant difference was found between Stage III-B and IV machines. Particle mass measurements, which were only measured from generators, showed that generators of all engine sizes were within their respective Stage III-A emission standards. A 95% reduction in NO X and 2 orders of magnitude reduction in particle number was observed for a SCR-DPF retrofitted generator, compared to the same generator prior to exhaust gas after-treatment strategy. </p

Structural studies of thermally stable, combustion-resistant polymer composites

Composites of the industrially important polymer, poly(methyl methacrylate) (PMMA), were prepared by free-radical polymerization of MMA with varying amounts (1–30 wt. %) of sodium dioctylsulfosuccinate (Aerosol OT or AOT) surfactant added to the reaction mixture. The composites with AOT incorporated show enhanced resistance to thermal degradation compared to pure PMMA homopolymer, and micro-cone combustion calorimetry measurements also show that the composites are combustion-resistant. The physical properties of the polymers, particularly at low concentrations of surfactant, are not significantly modified by the incorporation of AOT, whereas the degradation is modified considerably for even the smallest concentration of AOT (1 wt. %). Structural analyses over very different lengthscales were performed. X-ray scattering was used to determine nm-scale structure, and scanning electron microscopy was used to determine μm-scale structure. Two self-assembled species were observed: large phase-separated regions of AOT using electron microscopy and regions of hexagonally packed rods of AOT using X-ray scattering. Therefore, the combustion resistance is observed whenever AOT self-assembles. These results demonstrate a promising method of physically incorporating a small organic molecule to obtain a highly thermally stable and combustion-resistant material without significantly changing the properties of the polymer

Towards healthy school neighbourhoods: a baseline analysis in Greater London

Creating healthy environments around schools is important to promote healthy childhood development and is a critical component of public health. In this paper we present a tool to characterize exposure to multiple urban environment features within 400 m (5-10 minutes walking distance) of schools in Greater London. We modelled joint exposure to air pollution (NO2 and PM2.5), access to public greenspace, food environment, and road safety for 2,929 schools, employing a Bayesian non-parametric approach based on the Dirichlet Process Mixture modelling. We identified 12 latent clusters of schools with similar exposure profiles and observed some spatial clustering patterns. Socioeconomic and ethnicity disparities were manifested with respect to exposure profiles. Specifically, three clusters (containing 645 schools) showed the highest joint exposure to air pollution, poor food environment, and unsafe roads and were characterized with high deprivation. The most deprived cluster of schools had a median of 2.5 ha greenspace, 29.0 µg/m3 of NO2, 19.3 µg/m3 of PM2.5, 20 fast food retailers, and five child pedestrian crashes over a three-year period. The least deprived cluster of schools had a median of 21.8 ha greenspace, 15.6 µg/m3 of NO2, 15.1 µg/m3 of PM2.5, 2 fast food retailers, and one child pedestrian crash over a three-year period. To have a school-level understanding of exposure levels, we then benchmarked schools based on the probability of exceeding the median exposure to various features of interest. Our study accounts for multiple exposures, enabling us to highlight spatial distribution of exposure profile clusters, and to identify predominant exposure to urban environment features for each cluster of schools. Our findings can help relevant stakeholders, such as schools and public health authorities, to compare schools based on their exposure levels, prioritize interventions, and design local policies that target the schools most in need

London hybrid exposure model: improving human exposure estimates to NO2 and PM2.5 in an urban setting

Here we describe the development of the London Hybrid Exposure Model (LHEM), which calculates exposure of the Greater London population to outdoor air pollution sources, in-buildings, in-vehicles and outdoors, using survey data of when and where people spend their time. For comparison and to estimate exposure misclassification we compared Londoners LHEM exposure with exposure at the residential address, a commonly used exposure metric in epidemiological research. In 2011, the mean annual LHEM exposure to outdoor sources was estimated to be 37÷ lower for PM2.5 and 63÷ lower for NO2 than at the residential address. These decreased estimates reflect, the effects of reduced exposure indoors, the amount of time spent indoors (95÷), and the mode and duration of travel in London. We find that an individual's exposure to PM2.5 and NO2 outside their residential address is highly correlated (Pearson's R of 0.9). In contrast, LHEM exposure estimates for PM2.5 and NO2 suggest that the degree of correlation is influe..