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Recent exploitation of the avian immune system has highlighted its suitability for the generation of high-quality, high-affinity antibodies to a wide range of antigens for a number of therapeutic and biotechnological applications. The glycosylation profile of potential immunoglobulin therapeutics is species specific and is heavily influenced by the cell-line/culture conditions used for production. Hence, knowledge of the carbohydrate moieties present on immunoglobulins is essential as certain glycan structures can adversely impact their physicochemical and biological properties. This study describes the detailed N-glycan profile of IgY polyclonal antibodies from the serum of leghorn chickens using a fully quantitative high-throughput N-glycan analysis approach, based on ultra-performance liquid chromatography (UPLC) separation of released glycans. Structural assignments revealed serum IgY to contain complex bi-, tri- and tetra-antennary glycans with or without core fucose and bisects, hybrid and high mannose glycans. High sialic acid content was also observed, with the presence of rare sialic acid structures, likely polysialic acids. It is concluded that IgY is heavily decorated with complex glycans; however, no known non-human or immunogenic glycans were identified. Thus, IgY is a potentially promising candidate for immunoglobulin-based therapies for the treatment of various infectious diseases.

Abstract The cost of monitoring and detecting pollutants in natural waters is of major concern. Current and forthcoming bodies of legislation will continue to drive demand for spatial and selective monitoring of our environment, as the focus increasingly moves towards effective enforcement of legislation through detection of harmful events, and unambiguous identification of perpetrators. However, these monitoring demands are not being met due to the infrastructure and maintenance costs of conventional sensing models. Advanced autonomous platforms capable of performing complex analytical measurements at remote locations still require individual power, wireless communication, processor and electronic transducer units, along with regular maintenance visits. Hence the cost base for these systems is prohibitively high, and the spatial density and frequency of measurements are insufficient to meet requirements. In this paper, we present a more cost effective approach for water quality monitoring using a low cost mobile sensing/communications platform together with very low cost stand-alone ‘satellite’ indicator stations that have an integrated colorimetric sensing material. The mobile platform is equipped with a wireless video camera that is used to interrogate each station to harvest information about the water quality. In simulation experiments, the first cycle of measurements is carried out to identify a ‘normal’ condition followed by a second cycle during which the platform successfully detected and communicated the presence of a chemical contaminant that had been localised at one of the satellite stations.

Terrestrial mobile laser scanning systems provide rapid and cost effective 3D point cloud data which can be used for extracting features such as the road edge along a route corridor. This information can assist road authorities in carrying out safety risk assessment studies along road networks. The knowledge of the road edge is also a prerequisite for the automatic estimation of most other road features. In this paper, we present an algorithm which has been developed for extracting left and right road edges from terrestrial mobile LiDAR data. The algorithm is based on a novel combination of two modified versions of the parametric active contour or snake model. The parameters involved in the algorithm are selected empirically and are fixed for all the road sections. We have developed a novel way of initialising the snake model based on the navigation information obtained from the mobile mapping vehicle. We tested our algorithm on different types of road sections representing rural, urban and national primary road sections. The successful extraction of road edges from these multiple road section environments validates our algorithm. These findings and knowledge provide valuable insights as well as a prototype road edge extraction tool-set, for both national road authorities and survey companies. Refereed/Peer-reviewed

Thoroughbred horse racing is a global sport with major hubs in Europe, North America, Australasia and Japan. Regional preferences for certain traits have resulted in phenotypic variation that may result from adaptation to the local racing ecosystem. Here, we test the hypothesis that genes selected for regional phenotypic variation may be identified by analysis of selection signatures in pan-genomic SNP genotype data. Comparing Australian to non-Australian Thoroughbred horses (n = 99), the most highly differentiated loci in a composite selection signals (CSS) analysis were on ECA6 (34.75-34.85 Mb), ECA14 (33.2-33.52 Mb and 35.52-36.94 Mb) and ECA16 (24.28-26.52 Mb) in regions containing candidate genes for exercise adaptations including cardiac function (ARHGAP26, HBEGF, SRA1), synapse development and locomotion (APBB3, ATXN7, CLSTN3), stress response (NR3C1) and the skeletal muscle response to exercise (ARHGAP26, NDUFA2). In a genome-wide association study for field-measured speed in two-year-olds (n = 179) SNPs contained within the single association peak (33.2-35.6 Mb) overlapped with the ECA14 CSS signals and spanned a protocadherin gene cluster. Association tests using higher density SNP genotypes across the ECA14 locus identified a SNP within the PCDHGC5 gene associated with elite racing performance (n = 922). These results indicate that there may be differential selection for racing performance under racing and management conditions that are specific to certain geographic racing regions. In Australia breeders have principally selected horses for favourable genetic variants at loci containing genes that modulate behaviour, locomotion and skeletal muscle physiology that together appear to be contributing to early two-year-old speed.

The negative impact of road accidents cannot be ignored in terms of the very sizeable social and economic loss. Road infrastructure has been identified as one of the main causes of the road accidents. They are required to be recorded, located, measured, and classified in order to schedule maintenance and identify the possible risk elements of the road. Toward this, an accurate knowledge of the road edges increases the reliability and precision of extracting other road features. We have developed an automated algorithm for extracting road edges from mobile laser scanning (MLS) data based on the parametric active contour or snake model. The algorithm involves several internal and external energy parameters that need to be analyzed in order to find their optimal values. In this paper, we present a detailed analysis of the snake energy parameters involved in our road edge extraction algorithm. Their optimal values enable us to automate the process of extracting edges from MLS data for tested road sections. We present a modified external energy in our algorithm and demonstrate its utility for extracting road edges from low and nonuniform point density datasets. A novel validation approach is presented, which provides a qualitative assessment of the extracted road edges based on direct comparisons with reference road edges. This approach provides an alternative to traditional road edge validation methodologies that are based on creating buffer zones around reference road edges and then computing quality measure values for the extracted edges. We tested our road edge extraction algorithm on datasets that were acquired using multiple MLS systems along various complex road sections. The successful extraction of road edges from these datasets validates the robustness of our algorithm for use in complex route corridor environments. Refereed/Peer-reviewed

peer-reviewed Bovine tuberculosis (bTB) is an infectious disease of cattle generally caused by Mycobacterium bovis, a bacterium that can elicit disease humans. Since the 1950s, the objective of the national bTB eradication program in Republic of Ireland was the biological extinction of bTB; that purpose has yet to be achieved. Objectives of the present study were to develop the statistical methodology and variance components to undertake routine genetic evaluations for resistance to bTB; also of interest was the detection of regions of the bovine genome putatively associated with bTB infection in dairy and beef breeds. The novelty of the present study, in terms of research on bTB infection, was the use of beef breeds in the genome-wide association and the utilization of imputed whole genome sequence data. Phenotypic bTB data on 781,270 animals together with imputed whole genome sequence data on 7,346 of these animals’ sires were available. Linear mixed models were used to quantify variance components for bTB and EBVs were validated. Within-breed and multi-breed genome-wide associations were undertaken using a single-SNP regression approach. The estimated genetic standard deviation (0.09), heritability (0.12), and repeatability (0.30) substantiate that genetic selection help to eradicate bTB. The multi-breed genome-wide association analysis identified 38 SNPs and 64 QTL regions associated with bTB infection; two QTL regions (both on BTA23) identified in the multi-breed analysis overlapped with the within-breed analyses of Charolais, Limousin, and Holstein-Friesian. Results from the association analysis, coupled with previous studies, suggest bTB is controlled by an infinitely large number of loci, each having a small effect. The methodology and results from the present study will be used to develop national genetic evaluations for bTB in the Republic of Ireland. In addition, results can also be used to help uncover the biological architecture underlying resistance to bTB infection in cattle.

This paper demonstrates the full centrifugal microfluidic integration and automation of all liquid handling steps of a 7-step fluorescence-linked immunosorbent assay (FLISA) for quantifying nitrate and nitrite levels in whole blood within about 15 min. The assay protocol encompasses the extraction of metered plasma, the controlled release of sample and reagents (enzymes, co-factors and fluorescent labels), and incubation and detection steps. Flow control is implemented by a rotationally actuated dissolvable film (DF) valving scheme. In the valves, the burst pressure is primarily determined by the radial position, geometry and volume of the valve chamber and its inlet channel and can thus be individually tuned over an extraordinarily wide range of equivalent spin rates between 1,000 RPM and 5,500 RPM. Furthermore, the vapour barrier properties of the DF valves are investigated in this paper in order to further show the potential for commercially relevant on-board storage of liquid reagents during shelf-life of bioanalytical, ready-to-use discs. © 2013 by the authors; licensee MDPI, Basel, Switzerland.