Pseudomonas syringae pv. coryli, the causal agent of bacterial twig dieback of Corylus avellana

Thirty-eight bacterial strains isolated from hazelnut (Corylus avellana) cv. Tonda Gentile delle Langhe showing a twig dieback in Piedmont and Sardinia, Italy, were studied by a polyphasic approach. All strains were assessed by fatty acids analysis and repetitive sequence-based polymerase chain reaction (PCR) fingerprinting using BOX and ERIC primer sets. Representative strains also were assessed by sequencing the 16S rDNA and hrpL genes, determining the presence of the syrB gene, testing their biochemical and nutritional characteristics, and determining their pathogenicity to hazelnut and other plants species or plant organs. Moreover, they were compared with reference strains of other phytopathogenic pseudomonads. The strains from hazelnut belong to Pseudomonas syringae (sensu latu), LOPAT group Ia. Both fatty acids and repetitive-sequence-based PCR clearly discriminate such strains from other Pseudomonas spp., including P. avellanae and other P. syringae pathovars as well as P. syringae pv. syringae strains from hazelnut. Also, the sequencing of 16S rDNA and hrpL genes differentiated them from P. avellanae and from P. syringae pv. syringae. They did not possess the syrB gene. Some nutritional tests also differentiated them from related P. syringae pathovars. Upon artificial inoculation, these strains incited severe twig diebacks only on hazelnut. Our results justify the creation of a new pathovar because the strains from hazelnut constitute a homogeneous group and a discrete phenon. The name of P. syringae pv. coryli is proposed and criteria for routine identification are presented.

Artificial Intelligence: the basics

Artificial Intelligence: The Basics is a concise and cutting-edge introduction to the fast moving world of AI. The author Kevin Warwick, a pioneer in the field, examines issues of what it means to be man or machine and looks at advances in robotics which have blurred the boundaries. Topics covered include: how intelligence can be defined, whether machines can 'think', sensory input in machine systems, the nature of consciousness, the controversial culturing of human neurons. Exploring issues at the heart of the subject, this book is suitable for anyone interested in AI, and provides an illuminating and accessible introduction to this fascinating subject.

A model of UK domestic appliance-use using Artificial Neural Networks

The development of an Artificial Neural Network model of UK domestic appliance energy consumption is presented. The model uses diary-style appliance use data and a survey questionnaire collected from 51 households during the summer of 2010. It also incorporates measured energy data and is sensitive to socioeconomic, physical dwelling and temperature variables. A prototype model is constructed in MATLAB using a two layer feed forward network with backpropagation training and has a12:10:24architecture.Model outputs include appliance load profiles which can be applied to the fields of energy planning (micro renewables and smart grids), building simulation tools and energy policy.

Escherichia coli isolates from extraintestinal organs of livestock animals harbour diverse virulence genes and belong to multiple genetic lineages

Escherichia coli, the most common cause of bacteraemia in humans in the UK, can also cause serious diseases in animals. However the population structure, virulence and antimicrobial resistance genes of those from extraintestinal organs of livestock animals are poorly characterised. The aims of this study were to investigate the diversity of these isolates from livestock animals and to understand if there was any correlation between the virulence and antimicrobial resistance genes and the genetic backbone of the bacteria and if these isolates were similar to those isolated from humans. Here 39 E. coli isolates from liver (n=31), spleen (n=5) and blood (n=3) of cattle (n=34), sheep (n=3), chicken (n=1) and pig (n=1) were assigned to 19 serogroups with O8 being the most common (n=7), followed by O101, O20 (both n=3) and O153 (n=2). They belong to 29 multi-locus sequence types, 20 clonal complexes with ST23 (n=7), ST10 (n=6), ST117 and ST155 (both n=3) being most common and were distributed among phylogenetic group A (n=16), B1 (n=12), B2 (n=2) and D (n=9). The pattern of a subset of putative virulence genes was different in almost all isolates. No correlation between serogroups, animal hosts, MLST types, virulence and antimicrobial resistance genes was identified. The distributions of clonal complexes and virulence genes were similar to other extraintestinal or commensal E. coli from humans and other animals, suggesting a zoonotic potential. The diverse and various combinations of virulence genes implied that the infections were caused by different mechanisms and infection control will be challenging.