Array based detection of antibiotic resistance genes in Gram negative bacteria isolated from retail poultry meat in the UK and Ireland

The use of antibiotics in birds and animals intended for human consumption within the European Union (EU) and elsewhere has been subject to regulation prohibiting the use of antimicrobials as growth promoters and the use of last resort antibiotics in an attempt to reduce the spread of multi-resistant Gram negative bacteria. Given the inexorable spread of antibiotic resistance there is an increasing need for improved monitoring of our food. Using selective media, Gram negative bacteria were isolated from retail chicken of UK-Intensively reared (n = 27), Irish-Intensively reared (n = 19) and UK-Free range (n = 30) origin and subjected to an oligonucleotide based array system for the detection of 47 clinically relevant antibiotic resistance genes (ARGs) and two integrase genes. High incidences of β-lactamase genes were noted in all sample types, acc (67%), cmy (80%), fox (55%) and tem (40%) while chloramphenicol resistant determinants were detected in bacteria from the UK poultry portions and were absent in bacteria from the Irish samples. Denaturing Gradient Gel Electrophoresis (DGGE) was used to qualitatively analyse the Gram negative population in the samples and showed the expected diversity based on band stabbing and DNA sequencing. The array system proved to be a quick method for the detection of antibiotic resistance gene (ARG) burden within a mixed Gram negative bacterial population.

Implementation of Parallel (p,q) Counters for High Speed Digital Multipliers

Both the (5,3) counter and (2,2,3) counter multiplication techniques are investigated for the efficiency of their operation speed and the viability of the architectures when implemented in a fast bipolar ECL technology. The implementation of the counters in series-gated ECL and threshold logic are contrasted for speed, noise immunity and complexity, and are critically compared with the fastest practical design of a full-adder. A novel circuit technique to overcome the problems of needing high fan-in input weights in threshold circuits through the use of negative weighted inputs is presented. The authors conclude that a (2,2,3) counter based array multiplier implemented in series-gated ECL should enable a significant increase in speed over conventional full adder based array multipliers.

A benchmark-driven modelling approach for evaluating deployment choices on a multi-core architecture

The complexity of current and emerging architectures provides users with options about how best to use the available resources, but makes predicting performance challenging. In this work a benchmark-driven model is developed for a simple shallow water code on a Cray XE6 system, to explore how deployment choices such as domain decomposition and core affinity affect performance. The resource sharing present in modern multi-core architectures adds various levels of heterogeneity to the system. Shared resources often includes cache, memory, network controllers and in some cases floating point units (as in the AMD Bulldozer), which mean that the access time depends on the mapping of application tasks, and the core's location within the system. Heterogeneity further increases with the use of hardware-accelerators such as GPUs and the Intel Xeon Phi, where many specialist cores are attached to general-purpose cores. This trend for shared resources and non-uniform cores is expected to continue into the exascale era. The complexity of these systems means that various runtime scenarios are possible, and it has been found that under-populating nodes, altering the domain decomposition and non-standard task to core mappings can dramatically alter performance. To find this out, however, is often a process of trial and error. To better inform this process, a performance model was developed for a simple regular grid-based kernel code, shallow. The code comprises two distinct types of work, loop-based array updates and nearest-neighbour halo-exchanges. Separate performance models were developed for each part, both based on a similar methodology. Application specific benchmarks were run to measure performance for different problem sizes under different execution scenarios. These results were then fed into a performance model that derives resource usage for a given deployment scenario, with interpolation between results as necessary.

A cluster-based implementation of a fault-tolerant parallel reduction algorithm using swarm-array computing

Recent research in multi-agent systems incorporate fault tolerance concepts. However, the research does not explore the extension and implementation of such ideas for large scale parallel computing systems. The work reported in this paper investigates a swarm array computing approach, namely ‘Intelligent Agents’. In the approach considered a task to be executed on a parallel computing system is decomposed to sub-tasks and mapped onto agents that traverse an abstracted hardware layer. The agents intercommunicate across processors to share information during the event of a predicted core/processor failure and for successfully completing the task. The agents hence contribute towards fault tolerance and towards building reliable systems. The feasibility of the approach is validated by simulations on an FPGA using a multi-agent simulator and implementation of a parallel reduction algorithm on a computer cluster using the Message Passing Interface.

Development of a dense SNP-based linkage map of an apple rootstock progeny using the Malus Infinium whole genome genotyping array

Background A whole-genome genotyping array has previously been developed for Malus using SNP data from 28 Malus genotypes. This array offers the prospect of high throughput genotyping and linkage map development for any given Malus progeny. To test the applicability of the array for mapping in diverse Malus genotypes, we applied the array to the construction of a SNPbased linkage map of an apple rootstock progeny. Results Of the 7,867 Malus SNP markers on the array, 1,823 (23.2 %) were heterozygous in one of the two parents of the progeny, 1,007 (12.8 %) were heterozygous in both parental genotypes, whilst just 2.8 % of the 921 Pyrus SNPs were heterozygous. A linkage map spanning 1,282.2 cM was produced comprising 2,272 SNP markers, 306 SSR markers and the S-locus. The length of the M432 linkage map was increased by 52.7 cM with the addition of the SNP markers, whilst marker density increased from 3.8 cM/marker to 0.5 cM/marker. Just three regions in excess of 10 cM remain where no markers were mapped. We compared the positions of the mapped SNP markers on the M432 map with their predicted positions on the ‘Golden Delicious’ genome sequence. A total of 311 markers (13.7 % of all mapped markers) mapped to positions that conflicted with their predicted positions on the ‘Golden Delicious’ pseudo-chromosomes, indicating the presence of paralogous genomic regions or misassignments of genome sequence contigs during the assembly and anchoring of the genome sequence. Conclusions We incorporated data for the 2,272 SNP markers onto the map of the M432 progeny and have presented the most complete and saturated map of the full 17 linkage groups of M. pumila to date. The data were generated rapidly in a high-throughput semi-automated pipeline, permitting significant savings in time and cost over linkage map construction using microsatellites. The application of the array will permit linkage maps to be developed for QTL analyses in a cost-effective manner, and the identification of SNPs that have been assigned erroneous positions on the ‘Golden Delicious’ reference sequence will assist in the continued improvement of the genome sequence assembly for that variety.

Classification of cortical microcircuits based on micro-electrode-array data from slices of rat barrel cortex

The bewildering complexity of cortical microcircuits at the single cell level gives rise to surprisingly robust emergent activity patterns at the level of laminar and columnar local field potentials (LFPs) in response to targeted local stimuli. Here we report the results of our multivariate data-analytic approach based on simultaneous multi-site recordings using micro-electrode-array chips for investigation of the microcircuitary of rat somatosensory (barrel) cortex. We find high repeatability of stimulus-induced responses, and typical spatial distributions of LFP responses to stimuli in supragranular, granular, and infragranular layers, where the last form a particularly distinct class. Population spikes appear to travel with about 33 cm/s from granular to infragranular layers. Responses within barrel related columns have different profiles than those in neighbouring columns to the left or interchangeably to the right. Variations between slices occur, but can be minimized by strictly obeying controlled experimental protocols. Cluster analysis on normalized recordings indicates specific spatial distributions of time series reflecting the location of sources and sinks independent of the stimulus layer. Although the precise correspondences between single cell activity and LFPs are still far from clear, a sophisticated neuroinformatics approach in combination with multi-site LFP recordings in the standardized slice preparation is suitable for comparing normal conditions to genetically or pharmacologically altered situations based on real cortical microcircuitry.

Genes driving potato tuber initiation and growth: identification based on transcriptional changes using the POCI array

The increasing amount of available expressed gene sequence data makes whole-transcriptome analysis of certain crop species possible. Potato currently has the second largest number of publicly available expressed sequence tag (EST) sequences among the Solanaceae. Most of these ESTs, plus other proprietary sequences, were combined and used to generate a unigene assembly. The set of 246,182 sequences produced 46,345 unigenes, which were used to design a 44K 60-mer oligo array (Potato Oligo Chip Initiative: POCI). In this study, we attempt to identify genes controlling and driving the process of tuber initiation and growth by implementing large-scale transcriptional changes using the newly developed POCI array. Major gene expression profiles could be identified exhibiting differential expression at key developmental stages. These profiles were associated with functional roles in cell division and growth. A subset of genes involved in the regulation of the cell cycle, based on their Gene Ontology classification, exhibit a clear transient upregulation at tuber onset indicating increased cell division during these stages. The POCI array allows the study of potato gene expression on a much broader level than previously possible and will greatly enhance analysis of transcriptional control mechanisms in a wide range of potato research areas. POCI sequence and annotation data are publicly available through the POCI database (http://pgrc.ipk-gatersleben.de/poci).

Evaluation of an elastomer based gold microelectrode array for neural recording applications

We are reporting on the fabrication and electrical characterization of a novel elastomer based micro-cuff neural interface. Electrodes are gold (Au) tracks of sub-100nm thickness and are thermally evaporated on a 0.5 mm thick polydimethylsiloxane (PDMS) substrate. We investigate how electrode area and immersion in phosphate buffered saline (PBS) at 37°C influence electrode impedance. A microfluidic channel is bonded to the electrode array to form the cuff. In an acute, in-vivo, proof-of-principle recording, the device is capable of detecting light stroking and pinch of a hind leg of an anaesthetized rat.

The systolic array genetic algorithm, an example of systolic arrays as a reconfigurable design methodology

We advocate the use of systolic design techniques to create custom hardware for Custom Computing Machines. We have developed a hardware genetic algorithm based on systolic arrays to illustrate the feasibility of the approach. The architecture is independent of the lengths of chromosomes used and can be scaled in size to accommodate different population sizes. An FPGA prototype design can process 16 million genes per second.

Carbohydrate-based therapeutics

In recent years there has been a resurgence of interest in the biological roles of carbohydrates and as a result it is now known that carbohydrates are involved in a vast array of disease processes. This review summarises progress in the development of carbohydrate-based therapeutics that involve: inhibition of carbohydrate-lectin interactions; immunisation, using monoclonal antibodies for carbohydrate antigens; inhibition of enzymes that synthesise disease-associated carbohydrates; replacement of carbohydrate-processing enzymes; targeting of drugs to specific disease cells via carbohydrate-lectin interactions; carbohydrate based anti-thrombotic agents.

Intelligent cores and intelligent agents: two approaches to achieve autonomy in swarm-array computing

How can a bridge be built between autonomic computing approaches and parallel computing systems? How can autonomic computing approaches be extended towards building reliable systems? How can existing technologies be merged to provide a solution for self-managing systems? The work reported in this paper aims to answer these questions by proposing Swarm-Array Computing, a novel technique inspired from swarm robotics and built on the foundations of autonomic and parallel computing paradigms. Two approaches based on intelligent cores and intelligent agents are proposed to achieve autonomy in parallel computing systems. The feasibility of the proposed approaches is validated on a multi-agent simulator.

Building reliable systems for space applications using swarm-array computing

Space applications demand the need for building reliable systems. Autonomic computing defines such reliable systems as self-managing systems. The work reported in this paper combines agent-based and swarm robotic approaches leading to swarm-array computing, a novel technique to achieve self-managing distributed parallel computing systems. Two swarm-array computing approaches based on swarms of computational resources and swarms of tasks are explored. FPGA is considered as the computing system. The feasibility of the two proposed approaches that binds the computing system and the task together is simulated on the SeSAm multi-agent simulator.

Building reliable systems for space applications using swarm-array computing

Space applications demand the need for building reliable systems. Autonomic computing defines such reliable systems as self-managing systems. The work reported in this paper combines agent-based and swarm robotic approaches leading to swarm-array computing, a novel technique to achieve self-managing distributed parallel computing systems. Two swarm-array computing approaches based on swarms of computational resources and swarms of tasks are explored. FPGA is considered as the computing system. The feasibility of the two proposed approaches that binds the computing system and the task together is simulated on the SeSAm multi-agent simulator.

Investigating the feasibility of a swarm-array computing approach

The work reported in this paper proposes a novel synergy between parallel computing and swarm robotics to offer a new computing paradigm, 'swarm-array computing' that can harness and apply autonomic computing for parallel computing systems. One approach among three proposed approaches in swarm-array computing based on landscapes of intelligent cores, in which the cores of a parallel computing system are abstracted to swarm agents, is investigated. A task is executed and transferred seamlessly between cores in the proposed approach thereby achieving self-ware properties that characterize autonomic computing. FPGAs are considered as an experimental platform taking into account its application in space robotics. The feasibility of the proposed approach is validated on the SeSAm multi-agent simulator.

An autonomic approach in swarm-array computing

Can autonomic computing concepts be applied to traditional multi-core systems found in high performance computing environments? In this paper, we propose a novel synergy between parallel computing and swarm robotics to offer a new computing paradigm, `Swarm-Array Computing' that can harness and apply autonomic computing for parallel computing systems. One approach among three proposed approaches in swarm-array computing based on landscapes of intelligent cores, in which the cores of a parallel computing system are abstracted to swarm agents, is investigated. A task gets executed and transferred seamlessly between cores in the proposed approach thereby achieving self-ware properties that characterize autonomic computing. FPGAs are considered as an experimental platform taking into account its application in space robotics. The feasibility of the proposed approach is validated on the SeSAm multi-agent simulator.