The LONI Pipeline is a graphical environment for construction, validation and execution of advanced neuroimaging data analysis protocols (Rex et al., 2003). It enables automated data format conversion, allows Grid utilization, facilitates data provenance, and provides a significant library of computational tools. There are two main advantages of the LONI Pipeline over other graphical analysis workflow architectures. It is built as a distributed Grid computing environment and permits efficient tool integration, protocol validation and broad resource distribution. To integrate existing data and computational tools within the LONI Pipeline environment, no modification of the resources themselves is required. The LONI Pipeline provides several types of process submissions based on the underlying server hardware infrastructure. Only workflow instructions and references to data, executable scripts and binary instructions are stored within the LONI Pipeline environment. This makes it portable, computationally efficient, distributed and independent of the individual binary processes involved in pipeline data-analysis workflows. We have expanded the LONI Pipeline (V.4.2) to include server-to-server (peer-to-peer) communication and a 3-tier failover infrastructure (Grid hardware, Sun Grid Engine/Distributed Resource Management Application API middleware, and the Pipeline server). Additionally, the LONI Pipeline provides three layers of background-server executions for all users/sites/systems. These new LONI Pipeline features facilitate resource-interoperability, decentralized computing, construction and validation of efficient and robust neuroimaging data-analysis workflows. Using brain imaging data from the Alzheimer's Disease Neuroimaging Initiative (Mueller et al., 2005), we demonstrate integration of disparate resources, graphical construction of complex neuroimaging analysis protocols and distributed parallel computing. The LONI Pipeline, its features, specifications, documentation and usage are available online ().

SummaryBackground Relapses of multiple sclerosis decrease during pregnancy, when the hormone estriol is increased. Estriol treatment is anti-infl ammatory and neuroprotective in preclinical studies. In a small single-arm study of people with multiple sclerosis estriol reduced gadolinium-enhancing lesions and was favourably immunomodulatory. We assessed whether estriol treatment reduces multiple sclerosis relapses in women.

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Strains of mice, through breeding or the disruption of normal genetic pathways, are widely used to model human diseases. Atlases are an invaluable aid in understanding the impact of such manipulations by providing a standard for comparison. We have developed a digital atlas of the adult C57BL/6J mouse brain as a comprehensive framework for storing and accessing the myriad types of information about the mouse brain. Our implementation was constructed using several different imaging techniques: magnetic resonance microscopy, blockface imaging, classical histology and immunohistochemistry. Along with raw and annotated images, it contains database management systems and a set of tools for comparing information from different techniques. The framework allows facile correlation of results from different animals, investigators or laboratories by establishing a canonical representation of the mouse brain and providing the tools for the insertion of independent data into the same space as the atlas. This tool will aid in managing the increasingly complex and voluminous amounts of information about the mammalian brain. It provides a framework that encompasses genetic information in the context of anatomical imaging and holds tremendous promise for producing new insights into the relationship between genotype and phenotype. We describe a suite of tools that enables the independent entry of other types of data, facile retrieval of information and straightforward display of images. Thus, the atlas becomes a framework for managing complex genetic and epigenetic information about the mouse brain. The atlas and associated tools may be accessed at

Gender-related differences in experimental allergic encephalomyelitis (EAE) were examined in the SJL mouse with the purpose of characterizing an animal model ideal for the study of gender-related differences in multiple sclerosis (MS). For the model to allow for study of the induction and the effector phase of disease, the adoptive EAE model was characterized. First, the SJL strain was shown to be nonresponsive with regard to the development of antisyngeneic HY-specific responses in females, thereby permitting intergender adoptive transfers of T lymphocytes during EAE induction. Then, when myelin basic protein (MBP)-specific T cells derived from females were adoptively transferred into female and male recipients, female recipients demonstrated a more rapid onset of disease (p = 0.01), greater maximal acute-phase clinical scores (p < 0.0001) and greater mean clinical scores (p < 0.0001) compared with male recipients. When MBP-specific T cells derived from males were adoptively transferred, female recipients again tended to be more severely affected. Histopathologic analysis revealed quantitative differences between genders that paralleled clinical expression. These results document a clear gender-related difference in adoptive EAE in the SJL, with clinical and histopathologic disease greater in females compared with males. This model will be a useful tool for addressing autoimmune mechanisms underlying gender-related differences in MS.