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10.1038/s41598-018-29017-1 http://scihub22266oqcxt.onion/10.1038/s41598-018-29017-1 C6048099!6048099!30013173     free     free     free Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Sci+Rep 2018 ; 8 (ä): ä Nephropedia Template TP {{tp|p=30013173|t=2018. Structural cortical network reorganization associated with early conversion to multiple sclerosis |pdf=|usr=}}{{30013173}} gab.com Text Structural cortical network reorganization associated with early conversion to multiple sclerosis JO: Sci Rep http://www.kidney.de/pget.php?&tw=1&pmid=30013173 #FOAvip Brain structural covariance networks (SCNs) based on pairwise statistical associations of cortical thickness data across brain areas reflect underlying physical and functional connections between them. SCNs capture the complexity of human brain cortex structure and are disrupted in neurodegenerative conditions. However, the longitudinal assessment of SCN dynamics has not yet been explored, despite its potential to unveil mechanisms underlying neurodegeneration. Here, we evaluated the changes of SCNs over 12 months in patients with a first inflammatory-demyelinating attack of the Central Nervous System and assessed their clinical relevance by comparing SCN dynamics of patients with and without conversion to multiple sclerosis (MS) over one year. All subjects underwent clinical and brain MRI assessments over one year. Brain cortical thicknesses for each subject and time point were used to obtain group-level between-area correlation matrices from which nodal connectivity metrics were obtained. Robust bootstrap-based statistical approaches (allowing sampling with replacement) assessed the significance of longitudinal changes. Patients who converted to MS exhibited significantly greater network connectivity at baseline than non-converters (p?=?0.02) and a subsequent connectivity loss over time (p?=?0.001?0.02), not observed in non-converters? network. These findings suggest SCN analysis is sensitive to brain tissue changes in early MS, reflecting clinically relevant aspects of the condition. However, this is preliminary work, indicated by the low sample sizes, and its results and conclusions should be treated with caution and confirmed with larger cohorts. Twit Text FOAVip Structural cortical network reorganization associated with early conversion to multiple sclerosis ????Sci Rep http://www.kidney.de/pget.php?&tw=1&pmid=30013173 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=30013173 #FOAvip English Wikipedia <ref>{{Cite pmid|30013173}}</ref> Structural cortical network reorganization associated with early conversion to multiple sclerosis #MMPMID30013173 Tur C; Eshaghi A; Altmann DR; Jenkins TM; Prados F; Grussu F; Charalambous T; Schmidt A; Ourselin S; Clayden JD; Wheeler-Kingshott CAMG; Thompson AJ; Ciccarelli O; Toosy AT Sci Rep 2018[]; 8 (ä): ä PMID30013173show ga Brain structural covariance networks (SCNs) based on pairwise statistical associations of cortical thickness data across brain areas reflect underlying physical and functional connections between them. SCNs capture the complexity of human brain cortex structure and are disrupted in neurodegenerative conditions. However, the longitudinal assessment of SCN dynamics has not yet been explored, despite its potential to unveil mechanisms underlying neurodegeneration. Here, we evaluated the changes of SCNs over 12 months in patients with a first inflammatory-demyelinating attack of the Central Nervous System and assessed their clinical relevance by comparing SCN dynamics of patients with and without conversion to multiple sclerosis (MS) over one year. All subjects underwent clinical and brain MRI assessments over one year. Brain cortical thicknesses for each subject and time point were used to obtain group-level between-area correlation matrices from which nodal connectivity metrics were obtained. Robust bootstrap-based statistical approaches (allowing sampling with replacement) assessed the significance of longitudinal changes. Patients who converted to MS exhibited significantly greater network connectivity at baseline than non-converters (p?=?0.02) and a subsequent connectivity loss over time (p?=?0.001?0.02), not observed in non-converters? network. These findings suggest SCN analysis is sensitive to brain tissue changes in early MS, reflecting clinically relevant aspects of the condition. However, this is preliminary work, indicated by the low sample sizes, and its results and conclusions should be treated with caution and confirmed with larger cohorts. äStructural cortical network reorganization associated with early conve(epmc).pdf DeepDyve Pubget Overpricing