MBAT: a scalable informatics system for unifying digital atlasing workflows.

BACKGROUND: Digital atlases provide a common semantic and spatial coordinate system that can be leveraged to compare, contrast, and correlate data from disparate sources. As the quality and amount of biological data continues to advance and grow, searching, referencing, and comparing this data with a researcher's own data is essential. However, the integration process is cumbersome and time-consuming due to misaligned data, implicitly defined associations, and incompatible data sources. This work addressing these challenges by providing a unified and adaptable environment to accelerate the workflow to gather, align, and analyze the data. RESULTS: The MouseBIRN Atlasing Toolkit (MBAT) project was developed as a cross-platform, free open-source application that unifies and accelerates the digital atlas workflow. A tiered, plug-in architecture was designed for the neuroinformatics and genomics goals of the project to provide a modular and extensible design. MBAT provides the ability to use a single query to search and retrieve data from multiple data sources, align image data using the user's preferred registration method, composite data from multiple sources in a common space, and link relevant informatics information to the current view of the data or atlas. The workspaces leverage tool plug-ins to extend and allow future extensions of the basic workspace functionality. A wide variety of tool plug-ins were developed that integrate pre-existing as well as newly created technology into each workspace. Novel atlasing features were also developed, such as supporting multiple label sets, dynamic selection and grouping of labels, and synchronized, context-driven display of ontological data. CONCLUSIONS: MBAT empowers researchers to discover correlations among disparate data by providing a unified environment for bringing together distributed reference resources, a user's image data, and biological atlases into the same spatial or semantic context. Through its extensible tiered plug-in architecture, MBAT allows researchers to customize all platform components to quickly achieve personalized workflows.

A descriptive study of nonfatal, unintentional home-based injury in urban settings: evidence from Hong Kong.

This study investigates the epidemiological characteristics of non-fatal unintentional household injuries in Hong Kong, the city with the world's highest population density. A population-based, cross-sectional, random telephone survey was conducted with a modified Chinese WHO injury and violence survey questionnarie in May 2007. Descriptive and univariate analysis was conducted to highlight the associated factors. The prevalence of all non-fatal unintentional home injuries in the preceding year was 40.2%. Contusion/crushing injuries, open wounds and burn-related scalds were the most commonly reported home injury and the extremities were the commonest injured body parts. Female gender, younger age and residence in private housing residence were significantly associated with higher likelihood of injuries and most injuries had incurred medical expenses. This is the first study to reported systemtically about the patterns of non-fatal unintentional household injuries in Hong Kong. Future interventions should be targeted to these high risk groups identified in this study.