AKRs expression in peripheral blood lymphocytes from smokers: the role of body mass index.

Aldo-keto reductases (AKRs) metabolize a wide range of substrates, including polycyclic aromatic hydrocarbons (PAHs), generating metabolites (o-quinones) and reactive oxygen species (ROS), which are capable of initiating and promoting carcinogenesis. Exposure to PAHs, their metabolites, and ROS further increase AKRs isoform expression that may amplify oxidative damage. Human AKR enzymes are highly polymorphic, and allelic variants may contribute to different AKRs expression in individuals. Despite the importance of AKRs in PAHs metabolism, there are no studies that evaluate, in general human populations, the effect of PAHs on AKRs expression in peripheral blood lymphocytes (PBLs). The aim of this study was to determine the effect of tobacco smoke exposure, and AKR1A1*2 and AKR1C3*2 polymorphisms, on AKR1A1 and AKR1C1-AKR1C3 messenger RNA (mRNA) levels in PBLs from smokers. In the smoker group, there is a statistically significant positive association between AKR1A1, AKR1C1, and AKR1C3 mRNA induction and urine cotinine levels in individuals with a body mass index (BMI) less than 25. However, AKR1A1*2 and AKR1C3*2 alleles did not influence AKR1A1 and AKR1C1-AKR1C3 mRNA levels. These results suggest that AKRs induction by PAHs in smokers' PBLs is associated with BMI; therefore, the role of adipose tissue accumulation in PAHs' effects needs further investigation.

A hybrid human and machine resource curation pipeline for the Neuroscience Information Framework.

The breadth of information resources available to researchers on the Internet continues to expand, particularly in light of recently implemented data-sharing policies required by funding agencies. However, the nature of dense, multifaceted neuroscience data and the design of contemporary search engine systems makes efficient, reliable and relevant discovery of such information a significant challenge. This challenge is specifically pertinent for online databases, whose dynamic content is 'hidden' from search engines. The Neuroscience Information Framework (NIF; http://www.neuinfo.org) was funded by the NIH Blueprint for Neuroscience Research to address the problem of finding and utilizing neuroscience-relevant resources such as software tools, data sets, experimental animals and antibodies across the Internet. From the outset, NIF sought to provide an accounting of available resources, whereas developing technical solutions to finding, accessing and utilizing them. The curators therefore, are tasked with identifying and registering resources, examining data, writing configuration files to index and display data and keeping the contents current. In the initial phases of the project, all aspects of the registration and curation processes were manual. However, as the number of resources grew, manual curation became impractical. This report describes our experiences and successes with developing automated resource discovery and semiautomated type characterization with text-mining scripts that facilitate curation team efforts to discover, integrate and display new content. We also describe the DISCO framework, a suite of automated web services that significantly reduce manual curation efforts to periodically check for resource updates. Lastly, we discuss DOMEO, a semi-automated annotation tool that improves the discovery and curation of resources that are not necessarily website-based (i.e. reagents, software tools). Although the ultimate goal of automation was to reduce the workload of the curators, it has resulted in valuable analytic by-products that address accessibility, use and citation of resources that can now be shared with resource owners and the larger scientific community. DATABASE URL: http://neuinfo.org.

Integration of multidisciplinary sensory data: a pilot model of the human brain project approach.

The paper provides an overview of neuroinformatics research at Yale University being performed as part of the national Human Brain Project. This research is exploring the integration of multidisciplinary sensory data, using the olfactory system as a model domain. The neuroinformatics activities fall into three main areas: 1) building databases and related tools that support experimental olfactory research at Yale and can also serve as resources for the field as a whole, 2) using computer models (molecular models and neuronal models) to help understand data being collected experimentally and to help guide further laboratory experiments, 3) performing basic neuroinformatics research to develop new informatics technologies, including a flexible data model (EAV/CR, entity-attribute-value with classes and relationships) designed to facilitate the integration of diverse heterogeneous data within a single unifying framework.

Easing the transition between attribute-value databases and conventional databases for scientific data.

We have previously developed and described a modeling and development framework called EAV/CR, which is appropriate for designing databases containing highly heterogeneous and evolving data, as in the case of scientific databases for rapidly advancing domains. The use of EAV/CR has been hampered by the lack of generic tools for non-procedurally transferring data into or out of legacy systems or analytical packages: the transfer task is complicated by the different representation of EAV vs. conventional data, which is not addressed by commercial data-transfer programs. We have therefore created such a tool, which works with a wide variety of data sources that are accessible via Microsoft OLE DB technology. The data transfer tool requires minimal programmer intervention to set up, and no programming to use on a regular basis. Current limitations of the tool are also noted.

Reengineering a database for clinical trials management: lessons for system architects.

This paper describes the process of enhancing Trial/DB, a database system for clinical studies management. The system's enhancements have been driven by the need to maximize the effectiveness of developer personnel in supporting numerous and diverse users, of study designers in setting up new studies, and of administrators in managing ongoing studies. Trial/DB was originally designed to work over a local area network within a single institution, and basic architectural changes were necessary to make it work over the Internet efficiently as well as securely. Further, as its use spread to diverse communities of users, changes were made to let the processes of study design and project management adapt to the working styles of the principal investigators and administrators for each study. The lessons learned in the process should prove instructive for system architects as well as managers of electronic patient record systems.

Exploring performance issues for a clinical database organized using an entity-attribute-value representation.

BACKGROUND: The entity-attribute-value representation with classes and relationships (EAV/CR) provides a flexible and simple database schema to store heterogeneous biomedical data. In certain circumstances, however, the EAV/CR model is known to retrieve data less efficiently than conventionally based database schemas. OBJECTIVE: To perform a pilot study that systematically quantifies performance differences for database queries directed at real-world microbiology data modeled with EAV/CR and conventional representations, and to explore the relative merits of different EAV/CR query implementation strategies. METHODS: Clinical microbiology data obtained over a ten-year period were stored using both database models. Query execution times were compared for four clinically oriented attribute-centered and entity-centered queries operating under varying conditions of database size and system memory. The performance characteristics of three different EAV/CR query strategies were also examined. RESULTS: Performance was similar for entity-centered queries in the two database models. Performance in the EAV/CR model was approximately three to five times less efficient than its conventional counterpart for attribute-centered queries. The differences in query efficiency became slightly greater as database size increased, although they were reduced with the addition of system memory. The authors found that EAV/CR queries formulated using multiple, simple SQL statements executed in batch were more efficient than single, large SQL statements. CONCLUSION: This paper describes a pilot project to explore issues in and compare query performance for EAV/CR and conventional database representations. Although attribute-centered queries were less efficient in the EAV/CR model, these inefficiencies may be addressable, at least in part, by the use of more powerful hardware or more memory, or both.

GEM: a proposal for a more comprehensive guideline document model using XML.

OBJECTIVE: To develop a guideline document model that includes a sufficiently broad set of concepts to be useful throughout the guideline life cycle. DESIGN: Current guideline document models are limited in that they reflect the specific orientation of the stakeholder who created them; thus, developers and disseminators often provide few constructs for conceptualizing recommendations, while implementers de-emphasize concepts related to establishing guideline validity. The authors developed the Guideline Elements Model (GEM) using XML to better represent the heterogeneous knowledge contained in practice guidelines. Core constructs were derived from the Institute of Medicine's Guideline Appraisal Instrument, the National Guideline Clearinghouse, and the augmented decision table guideline representation. These were supplemented by additional concepts from a literature review. RESULTS: The GEM hierarchy includes more than 100 elements. Major concepts relate to a guideline's identity, developer, purpose, intended audience, method of development, target population, knowledge components, testing, and review plan. Knowledge components in guideline documents include recommendations (which in turn comprise conditionals and imperatives), definitions, and algorithms. CONCLUSION: GEM is more comprehensive than existing models and is expressively adequate to represent the heterogeneous information contained in guidelines. Use of XML contributes to a flexible, comprehensible, shareable, and reusable knowledge representation that is both readable by human beings and processible by computers.

WebEAV: automatic metadata-driven generation of web interfaces to entity-attribute-value databases.

The task of creating and maintaining a front end to a large institutional entity-attribute-value (EAV) database can be cumbersome when using traditional client-server technology. Switching to Web technology as a delivery vehicle solves some of these problems but introduces others. In particular, Web development environments tend to be primitive, and many features that client-server developers take for granted are missing. WebEAV is a generic framework for Web development that is intended to streamline the process of Web application development for databases having a significant EAV component. It also addresses some challenging user interface issues that arise when any complex system is created. The authors describe the architecture of WebEAV and provide an overview of its features with suitable examples.

Olfactory receptor database: a sensory chemoreceptor resource.

The Olfactory Receptor Database (ORDB) is a WWW-accessible database that has been expanded from an olfactory receptor resource to a chemoreceptor resource. It stores data on six classes of G-protein-coupled sensory chemoreceptors: (i) olfactory receptor-like proteins, (ii) vomeronasal receptors, (iii) insect olfactory receptors, (iv) worm chemo-receptors, (v) taste papilla receptors and (vi) fungal pheromone receptors. A complementary database of the ligands of these receptors (OdorDB) has been constructed and is publicly available in a pilot mode. The database schema of ORDB has been changed from traditional relational to EAV/CR (Entity-Attribute-Value with Classes and Relationships), which allows the interoperability of ORDB with other related databases as well as the creation of intra-database associations among objects. This inter-operability facilitates users to follow information from odor molecule binding to its putative receptor, to the properties of the neuron expressing the receptor, to a computational model of activity of olfactory bulb neurons. In addition, tools and resources have been added allowing users to access interactive phylogenetic trees and alignments of sensory chemoreceptors. ORDB is available via the WWW at http://ycmi.med. yale.edu/senselab/ordb/

Organization of heterogeneous scientific data using the EAV/CR representation.

Entity-attribute-value (EAV) representation is a means of organizing highly heterogeneous data using a relatively simple physical database schema. EAV representation is widely used in the medical domain, most notably in the storage of data related to clinical patient records. Its potential strengths suggest its use in other biomedical areas, in particular research databases whose schemas are complex as well as constantly changing to reflect evolving knowledge in rapidly advancing scientific domains. When deployed for such purposes, the basic EAV representation needs to be augmented significantly to handle the modeling of complex objects (classes) as well as to manage interobject relationships. The authors refer to their modification of the basic EAV paradigm as EAV/CR (EAV with classes and relationships). They describe EAV/CR representation with examples from two biomedical databases that use it.

Neuronal database integration: the Senselab EAV data model.

We discuss an approach towards integrating heterogeneous nervous system data using an augmented Entity-Attribute-Value (EAV) schema design. This approach, widely used in implementing electronic patient record systems (EPRSs), allows the physical schema of the database to be relatively immune to changes in domain knowledge. This is because new kinds of facts are added as data (or as metadata) rather than hard-coded as the names of newly created tables or columns. Because the domain knowledge is stored as metadata, a framework developed in one scientific domain can be ported to another with only modest revision. We describe our progress in creating a code framework that handles browsing and hyperlinking of the different kinds of data.