The pan-genome of Lactobacillus reuteri strains originating from the pig gastrointestinal tract

Background Lactobacillus reuteri is a gut symbiont of a wide variety of vertebrate species that has diversified into distinct phylogenetic clades which are to a large degree host-specific. Previous work demonstrated host specificity in mice and begun to determine the mechanisms by which gut colonisation and host restriction is achieved. However, how L. reuteri strains colonise the gastrointestinal (GI) tract of pigs is unknown. Results To gain insight into the ecology of L. reuteri in the pig gut, the genome sequence of the porcine small intestinal isolate L. reuteri ATCC 53608 was completed and consisted of a chromosome of 1.94 Mbp and two plasmids of 138.5 kbp and 9.09 kbp, respectively. Furthermore, we generated draft genomes of four additional L. reuteri strains isolated from pig faeces or lower GI tract, lp167-67, pg-3b, 20-2 and 3c6, and subjected all five genomes to a comparative genomic analysis together with the previously completed genome of strain I5007. A phylogenetic analysis based on whole genomes showed that porcine L. reuteri strains fall into two distinct clades, as previously suggested by multi-locus sequence analysis. These six pig L. reuteri genomes contained a core set of 1364 orthologous gene clusters, as determined by OrthoMCL analysis, that contributed to a pan-genome totalling 3373 gene clusters. Genome comparisons of the six pig L. reuteri strains with 14 L. reuteri strains from other host origins gave a total pan-genome of 5225 gene clusters that included a core genome of 851 gene clusters but revealed that there were no pig-specific genes per se. However, genes specific for and conserved among strains of the two pig phylogenetic lineages were detected, some of which encoded cell surface proteins that could contribute to the diversification of the two lineages and their observed host specificity. Conclusions This study extends the phylogenetic analysis of L. reuteri strains at a genome-wide level, pointing to distinct evolutionary trajectories of porcine L. reuteri lineages, and providing new insights into the genomic events in L. reuteri that occurred during specialisation to their hosts. The occurrence of two distinct pig-derived clades may reflect differences in host genotype, environmental factors such as dietary components or to evolution from ancestral strains of human and rodent origin following contact with pig populations

Nucleus segmentation : towards automated solutions

Single nucleus segmentation is a frequent challenge of microscopy image processing, since it is the first step of many quantitative data analysis pipelines. The quality of tracking single cells, extracting features or classifying cellular phenotypes strongly depends on segmentation accuracy. Worldwide competitions have been held, aiming to improve segmentation, and recent years have definitely brought significant improvements: large annotated datasets are now freely available, several 2D segmentation strategies have been extended to 3D, and deep learning approaches have increased accuracy. However, even today, no generally accepted solution and benchmarking platform exist. We review the most recent single-cell segmentation tools, and provide an interactive method browser to select the most appropriate solution.Peer reviewe

Facilitating file retrieval on resource limited devices

The rapid development of mobile technologies has facilitated users to generate and store files on mobile devices. However, it has become a challenging issue for users to search efficiently and effectively for files of interest in a mobile environment that involves a large number of mobile nodes. In this thesis, file management and retrieval alternatives have been investigated to propose a feasible framework that can be employed on resource-limited devices without altering their operating systems. The file annotation and retrieval framework (FARM) proposed in the thesis automatically annotates the files with their basic file attributes by extracting them from the underlying operating system of the device. The framework is implemented in the JME platform as a case study. This framework provides a variety of features for managing the metadata and file search features on the device itself and on other devices in a networked environment. FARM not only automates the file-search process but also provides accurate results as demonstrated by the experimental analysis. In order to facilitate a file search and take advantage of the Semantic Web Technologies, the SemFARM framework is proposed which utilizes the knowledge of a generic ontology. The generic ontology defines the most common keywords that can be used as the metadata of stored files. This provides semantic-based file search capabilities on low-end devices where the search keywords are enriched with additional knowledge extracted from the defined ontology. The existing frameworks annotate image files only, while SemFARM can be used to annotate all types of files. Semantic heterogeneity is a challenging issue and necessitates extensive research to accomplish the aim of a semantic web. For this reason, significant research efforts have been made in recent years by proposing an enormous number of ontology alignment systems to deal with ontology heterogeneities. In the process of aligning different ontologies, it is essential to encompass their semantic, structural or any system-specific measures in mapping decisions to produce more accurate alignments. The proposed solution, in this thesis, for ontology alignment presents a structural matcher, which computes the similarity between the super-classes, sub-classes and properties of two entities from different ontologies that require aligning. The proposed alignment system (OARS) uses Rough Sets to aggregate the results obtained from various matchers in order to deal with uncertainties during the mapping process of entities. The OARS uses a combinational approach by using a string-based and linguistic-based matcher, in addition to structural-matcher for computing the overall similarity between two entities. The performance of the OARS is evaluated in comparison with existing state of the art alignment systems in terms of precision and recall. The performance tests are performed by using benchmark ontologies and the results show significant improvements, specifically in terms of recall on all groups of test ontologies. There is no such existing framework, which can use alignments for file search on mobile devices. The ontology alignment paradigm is integrated in the SemFARM to further enhance the file search features of the framework as it utilises the knowledge of more than one ontology in order to perform a search query. The experimental evaluations show that it performs better in terms of precision and recall where more than one ontology is available when searching for a required file.EThOS - Electronic Theses Online ServiceEducation Commission of PakistanTechnology, PeshawarGBUnited Kingdo

CHORUS Deliverable 4.5: Report of the 3rd CHORUS Conference

The third and last CHORUS conference on Multimedia Search Engines took place from the 26th to the 27th of May 2009 in Brussels, Belgium. About 100 participants from 15 European countries, the US, Japan and Australia learned about the latest developments in the domain. An exhibition of 13 stands presented 16 research projects currently ongoing around the world

Developing the Read/Write Library

Background: This article considers the use of Fedora-based library digital asset management systems (DAMS) as digital humanities (DH) research platforms.Analysis: The features of DAMS are evaluated to identify the ways in which they can currently meet researcher needs, and to suggest areas where further development is necessary.Conclusion and implications: Fedora-based DAMS hold great promise as the basis of digital humanities research platforms. Mature functionality is available for identity management, file and metadata management, versioning, publishing, social media sharing, discovery, interoperability, and long-term preservation. Further development is necessary in order to incorporate annotation, mark-up, and text analysis tools

Context Aware Computing for The Internet of Things: A Survey

As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a significant increment of the growth rate in the future. These sensors continuously generate enormous amounts of data. However, in order to add value to raw sensor data we need to understand it. Collection, modelling, reasoning, and distribution of context in relation to sensor data plays critical role in this challenge. Context-aware computing has proven to be successful in understanding sensor data. In this paper, we survey context awareness from an IoT perspective. We present the necessary background by introducing the IoT paradigm and context-aware fundamentals at the beginning. Then we provide an in-depth analysis of context life cycle. We evaluate a subset of projects (50) which represent the majority of research and commercial solutions proposed in the field of context-aware computing conducted over the last decade (2001-2011) based on our own taxonomy. Finally, based on our evaluation, we highlight the lessons to be learnt from the past and some possible directions for future research. The survey addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201