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The ecology of infectious diseases involves wildlife, yet the wildlife interface is often neglected and understudied. Pathogens related to infectious diseases are often maintained within wildlife populations and can spread to livestock and humans. In this study, we explored the fecal microbiome of coyotes and wild hogs in the Texas panhandle using polymerase chain reactions and 16S sequencing methods. The fecal microbiota of coyotes was dominated by members of the phyla Bacteroidetes, Firmicutes, and Proteobacteria. At the genus taxonomic level, Odoribacter, Allobaculum, Coprobacillus, and Alloprevotella were the dominant genera of the core fecal microbiota of coyotes. While for wild hogs, the fecal microbiota was dominated by bacterial members of the phyla Bacteroidetes, Spirochaetes, Firmicutes, and Proteobacteria. Five genera, Treponema, Prevotella, Alloprevotella, Vampirovibrio, and Sphaerochaeta, constitute the most abundant genera of the core microbiota of wild hogs in this study. Functional profile of the microbiota of coyotes and wild hogs identified 13 and 17 human-related diseases that were statistically associated with the fecal microbiota, respectively (p < 0.05). Our study is a unique investigation of the microbiota using free-living wildlife in the Texas Panhandle and contributes to awareness of the role played by gastrointestinal microbiota of wild canids and hogs in infectious disease reservoir and transmission risk. This report will contribute to the lacking information on coyote and wild hog microbial communities by providing insights into their composition and ecology which may likely be different from those of captive species or domesticated animals. This study will contribute to baseline knowledge for future studies on wildlife gut microbiomes. [ABSTRACT FROM AUTHOR]

Several genome-wide analyses are conducted to study the DNA copy-number variations (CNVs) in the phenotypically concordant or discordant monozygotic twins. The twins are found to exhibit different CNV profiles, hence giving a better insight into their disease-predisposition loci.

Abstract Background Neuroscientists often need to access a wide range of data sets distributed over the Internet. These data sets, however, are typically neither integrated nor interoperable, resulting in a barrier to answering complex neuroscience research questions. Domain ontologies can enable the querying heterogeneous data sets, but they are not sufficient for neuroscience since the data of interest commonly span multiple research domains. To this end, e-Neuroscience seeks to provide an integrated platform for neuroscientists to discover new knowledge through seamless integration of the very diverse types of neuroscience data. Here we present a Semantic Web approach to building this e-Neuroscience framework by using the Resource Description Framework (RDF) and its vocabulary description language, RDF Schema (RDFS), as a standard data model to facilitate both representation and integration of the data. Results We have constructed a pilot ontology for BrainPharm (a subset of SenseLab) using RDFS and then converted a subset of the BrainPharm data into RDF according to the ontological structure. We have also integrated the converted BrainPharm data with existing RDF hypothesis and publication data from a pilot version of SWAN (Semantic Web Applications in Neuromedicine). Our implementation uses the RDF Data Model in Oracle Database 10g release 2 for data integration, query, and inference, while our Web interface allows users to query the data and retrieve the results in a convenient fashion. Conclusion Accessing and integrating biomedical data which cuts across multiple disciplines will be increasingly indispensable and beneficial to neuroscience researchers. The Semantic Web approach we undertook has demonstrated a promising way to semantically integrate data sets created independently. It also shows how advanced queries and inferences can be performed over the integrated data, which are hard to achieve using traditional data integration approaches. Our pilot results suggest that our Semantic Web approach is suitable for realizing e-Neuroscience and generic enough to be applied in other biomedical fields.

A reaction mechanism for the 5'-RP excision activity of the 8kDa domain, which focuses on a catalytic groove near its helix-hairpin-helix motif is presented. It is proposed that the additional contacts between amino acid residues in the catalytic groove and the dRP group may be responsible for the 8kDa domain recognition of the preincised AP. Results demonstrate that the binding affinity of the 8kDa domain for the nicked AP site is much higher than that for the AP nucleotide without nicking, indicating that the 5'-phosphate was necessary for recognition.

Abstract Background This paper describes the development of a web-based tool, GenDrux, which extracts and presents (over the Internet) information related to the disease-gene-drug nexus. This information is archived from the relevant biomedical literature using automated methods. GenDrux is designed to alleviate the difficulties of manually processing the vast biomedical literature to identify disease-gene-drug relationships. GenDrux will evolve with the literature without additional algorithmic modifications. Results GenDrux, a pilot system, is developed in the domain of breast cancer and can be accessed at http://www.microarray.uab.edu/drug_gene.pl. GenDrux can be queried based on drug, gene and/or disease name. From over 8,000 relevant abstracts from the biomedical literature related to breast cancer, we have archived a corpus of more than 4,000 articles that depict gene expression-drug activity relationships for breast cancer and related cancers. The archiving process has been automated. Conclusions The successful development, implementation, and evaluation of this and similar systems when created may provide clinicians with a tool for literature management, clinical decision making, thus setting the platform for personalized therapy in the future.

Abstract Background Gene expression patterns of olfactory receptors (ORs) are an important component of the signal encoding mechanism in the olfactory system since they determine the interactions between odorant ligands and sensory neurons. We have developed the Olfactory Receptor Microarray Database (ORMD) to house OR gene expression data. ORMD is integrated with the Olfactory Receptor Database (ORDB), which is a key repository of OR gene information. Both databases aim to aid experimental research related to olfaction. Description ORMD is a Web-accessible database that provides a secure data repository for OR microarray experiments. It contains both publicly available and private data; accessing the latter requires authenticated login. The ORMD is designed to allow users to not only deposit gene expression data but also manage their projects/experiments. For example, contributors can choose whether to make their datasets public. For each experiment, users can download the raw data files and view and export the gene expression data. For each OR gene being probed in a microarray experiment, a hyperlink to that gene in ORDB provides access to genomic and proteomic information related to the corresponding olfactory receptor. Individual ORs archived in ORDB are also linked to ORMD, allowing users access to the related microarray gene expression data. Conclusion ORMD serves as a data repository and project management system. It facilitates the study of microarray experiments of gene expression in the olfactory system. In conjunction with ORDB, ORMD integrates gene expression data with the genomic and functional data of ORs, and is thus a useful resource for both olfactory researchers and the public.

A study was conducted to examine the role of [Phe.sup.7] in endogenous nonselective agonists ACTH and [alpha]-MSH on human (h) melanocortin receptors (MC1R, MC3R, and MC4R) binding and signaling. The NDP-[alpha]-MSH and N-D-Nal[(2').sup.7]-ACTH1-17 does not share the same binding site and the highly basic C-terminal fragment ([Lys.sup.15]-[Lys.sup.16]-[Arg.sup.17]) of N-D-Nal[(2').sup.7]-ACTH1?17 induced a new [beta]-turn shift which contribute to the selective agonist activity at hMC3R and hMC4R.