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      Can resistance training impact MRI outcomes in relapsing-remitting multiple sclerosis?

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          Abstract

          Multiple sclerosis (MS) is characterised by accelerated brain atrophy, which relates to disease progression. Previous research shows that progressive resistance training (PRT) can counteract brain atrophy in other populations.

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          Most cited references32

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          Exercise induces hippocampal BDNF through a PGC-1α/FNDC5 pathway.

          Exercise can improve cognitive function and has been linked to the increased expression of brain-derived neurotrophic factor (BDNF). However, the underlying molecular mechanisms driving the elevation of this neurotrophin remain unknown. Here we show that FNDC5, a previously identified muscle protein that is induced in exercise and is cleaved and secreted as irisin, is also elevated by endurance exercise in the hippocampus of mice. Neuronal Fndc5 gene expression is regulated by PGC-1α, and Pgc1a(-/-) mice show reduced Fndc5 expression in the brain. Forced expression of FNDC5 in primary cortical neurons increases Bdnf expression, whereas RNAi-mediated knockdown of FNDC5 reduces Bdnf. Importantly, peripheral delivery of FNDC5 to the liver via adenoviral vectors, resulting in elevated blood irisin, induces expression of Bdnf and other neuroprotective genes in the hippocampus. Taken together, our findings link endurance exercise and the important metabolic mediators, PGC-1α and FNDC5, with BDNF expression in the brain. Copyright © 2013 Elsevier Inc. All rights reserved.
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            Cortical plasticity: from synapses to maps.

            It has been clear for almost two decades that cortical representations in adult animals are not fixed entities, but rather, are dynamic and are continuously modified by experience. The cortex can preferentially allocate area to represent the particular peripheral input sources that are proportionally most used. Alterations in cortical representations appear to underlie learning tasks dependent on the use of the behaviorally important peripheral inputs that they represent. The rules governing this cortical representational plasticity following manipulations of inputs, including learning, are increasingly well understood. In parallel with developments in the field of cortical map plasticity, studies of synaptic plasticity have characterized specific elementary forms of plasticity, including associative long-term potentiation and long-term depression of excitatory postsynaptic potentials. Investigators have made many important strides toward understanding the molecular underpinnings of these fundamental plasticity processes and toward defining the learning rules that govern their induction. The fields of cortical synaptic plasticity and cortical map plasticity have been implicitly linked by the hypothesis that synaptic plasticity underlies cortical map reorganization. Recent experimental and theoretical work has provided increasingly stronger support for this hypothesis. The goal of the current paper is to review the fields of both synaptic and cortical map plasticity with an emphasis on the work that attempts to unite both fields. A second objective is to highlight the gaps in our understanding of synaptic and cellular mechanisms underlying cortical representational plasticity.
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              The Multiple Sclerosis Impact Scale (MSIS-29): a new patient-based outcome measure.

              J. Höbart (2001)
              Changes in health policy have underlined the importance of evidence-based clinical practice and rigorous evaluation of patient-based outcomes. As patient-based outcome measurement is particularly important in treatment trials of multiple sclerosis, a number of disease-specific instruments have been developed recently. One limitation of these instruments is that none was developed using the standard psychometric approach of reducing a large item pool generated from people with multiple sclerosis. Consequently, an outcome measure for clinical trials of multiple sclerosis that is disease specific and combines patient perspective with rigorous psychometric methods will complement existing instruments. The aim of this study was to develop such a measure. Standard psychometric methods were used. A pool of 129 questionnaire items was generated from interviews with 30 people with multiple sclerosis, expert opinion and literature review. The questionnaire was administered by postal survey to 1530 people selected randomly from the Multiple Sclerosis Society membership database. Redundant items and those with limited measurement properties were removed. The remaining items (n = 41) were grouped into scales using factor analysis, and then refined to form the Multiple Sclerosis Impact Scale (MSIS-29), an instrument measuring the physical (20 items) and psychological (nine items) impact of multiple sclerosis. Five psychometric properties of the MSIS-29 (data quality, scaling assumptions, acceptability, reliability and validity) were examined in a separate postal survey of 1250 Multiple Sclerosis Society members. A preliminary responsiveness study of the MSIS-29 was undertaken in 55 people admitted for rehabilitation and intravenous steroid treatment of relapses. The MSIS-29 satisfied all psychometric criteria. Data quality was excellent, missing data were low (maximum 3.9%), item test-re-test reliability was high (r = 0.65-0.90) and scale scores could be generated for >98% of respondents. Item descriptive statistics, item convergent and discriminant validity, and factor analysis indicated that it was legitimate to generate scores for MSIS-29 scales by summing items. MSIS-29 scales showed good variability, small floor and ceiling effects, high internal consistency (Cronbach's alpha
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                Author and article information

                Journal
                Multiple Sclerosis Journal
                Mult Scler
                SAGE Publications
                1352-4585
                1477-0970
                December 20 2017
                July 28 2017
                :
                :
                : 135245851772264
                Article
                10.1177/1352458517722645
                28752800
                9d986a0d-8eab-46af-b93f-cf0dcf8ee9c2
                © 2017

                http://journals.sagepub.com/page/policies/text-and-data-mining-license

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