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    ABSTRACT: Higher levels of fitness or physical function are positively associated with cognitive outcomes but the potential underlying mechanisms via brain structure are still to be elucidated in detail. We examined associations between brain structure and physical function (contemporaneous and change over the previous three years) in community-dwelling older adults. Participants from the Lothian Birth Cohort 1936 (N=694) underwent brain MRI at age 73 years to assess intracranial volume, and the volumes of total brain tissue, ventricles, grey matter, normal-appearing white matter, and white matter lesions. At ages 70 and 73, physical function was assessed by 6-meter walk, grip strength, and forced expiratory volume. A summary 'physical function factor' was derived from the individual measures using principal components analysis. Performance on each individual physical function measure declined across the three year interval (p<0.001). Higher level of physical function at ages 70 and 73 was associated with larger total brain tissue and white matter volumes, and smaller ventricular and white matter lesion volumes (standardized β ranged in magnitude from 0.07 to 0.17, p<0.001 to 0.034). Decline in physical function from age 70 to 73 was associated with smaller white matter volume (0.08, p<0.01, though not after correction for multiple testing), but not with any other brain volumetric measurements. Physical function was related to brain volumes in community-dwelling older adults: declining physical function was associated with less white matter tissue. Further study is required to explore the detailed mechanisms through which physical function might influence brain structure, and vice versa.
    Full-text · Article · Nov 2013 · PLoS ONE
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    ABSTRACT: The eye is an ideal target for exploiting the potential of human induced pluripotent stem cell (hiPSC) technology in order to understand disease pathways and explore novel therapeutic strategies for inherited retinal disease. The aim of this article is to map the pathway from state-of-the art laboratory-based discoveries to realising the translational potential of this emerging technique. We describe the relevance and routes to establishing hiPSCs in selected models of human retinal disease. Additionally, we define pathways for applying hiPSC technology in treating currently incurable, progressive and blinding retinal disease.
    Full-text · Article · Oct 2013 · Progress in Retinal and Eye Research
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    ABSTRACT: Standard univariate analyses of brain imaging data have revealed a host of structural and functional brain alterations in schizophrenia. However, these analyses typically involve examining each voxel separately and making inferences at group-level, thus limiting clinical translation of their findings. Taking into account the fact that brain alterations in schizophrenia expand over a widely distributed network of brain regions, univariate analysis methods may not be the most suited choice for imaging data analysis. To address these limitations, the neuroimaging community has turned to machine learning methods both because of their ability to examine voxels jointly and their potential for making inferences at a single-subject level. This article provides a critical overview of the current and foreseeable applications of machine learning, in identifying imaging-based biomarkers that could be used for the diagnosis, early detection and treatment response of schizophrenia, and could, thus, be of high clinical relevance. We discuss promising future research directions and the main difficulties facing machine learning researchers as far as their potential translation into clinical practice is concerned.
    Full-text · Article · Sep 2013 · Clinical neuroimaging
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