Background And Purpose: The pathogenesis of cerebral small vessel disease remains incompletely understood. The relationship between circadian rhythm disturbances and histopathologic measures of cerebral small vessel disease has not been studied. We hypothesized that disrupted circadian rest-activity rhythms would be associated with a higher burden of cerebral small vessel disease pathology.
Methods: We studied 561 community-dwelling older adults (mean age at death, 91.2, 27.4% male) from the Rush Memory and Aging Project. We used actigraphy to quantify several measures of 24-hour rest-activity rhythmicity, including interdaily stability, intradaily variability, and amplitude, and used ordinal logistic regression models to relate these measures to the severity of cerebral arteriolosclerosis, atherosclerosis, macroinfarcts, and microinfarcts, assessed at autopsy.
Results: Lower interdaily stability was associated with a higher burden of arteriolosclerosis, higher intradaily variability was associated with a higher burden of atherosclerosis and subcortical infarcts, and lower amplitude was associated with a higher burden of arteriosclerosis, atherosclerosis and subcortical macroinfarcts. Moreover, the associations between interdaily stability and arteriolosclerosis and intradaily variability and subcortical infarcts were independent of cardiovascular risk factors, sleep fragmentation, and medical comorbidities.
Conclusions: Disrupted rest-activity rhythms are associated with a greater burden of cerebral small vessel disease in older adults.
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http://dx.doi.org/10.1161/STROKEAHA.120.030870 | DOI Listing |
Front Biosci (Schol Ed)
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Laboratory of Genomic Research, Research Institute for Genetic and Molecular Epidemiology, Kursk State Medical University, 305041 Kursk, Russia.
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December 2024
Retired Professor, The University of Melbourne, Victoria, Australia.
Several recent studies have optimized deep neural networks to learn high-dimensional relationships linking structural and functional connectivity across the human connectome. However, the extent to which these models recapitulate individual-specific characteristics of resting-state functional brain networks remains unclear. A core concern relates to whether current individual predictions outperform simple benchmarks such as group averages and null conditions.
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December 2024
Department of Biomedical Engineering, Faculty of Engineering and Information Technology, The University of Melbourne, Melbourne, VIC, Australia.
Connectome generative models, otherwise known as generative network models, provide insight into the wiring principles underpinning brain network organization. While these models can approximate numerous statistical properties of empirical networks, they typically fail to explicitly characterize an important contributor to brain organization-axonal growth. Emulating the chemoaffinity-guided axonal growth, we provide a novel generative model in which axons dynamically steer the direction of propagation based on distance-dependent chemoattractive forces acting on their growth cones.
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Neurology, Dalhousie University, Halifax, CAN.
This case report discusses a unique presentation of an artery of Percheron (AOP) infarct resulting in rapidly resolving internuclear ophthalmoplegia (INO) without classical signs. This is the case of a 70-year-old male patient who presented to a community Emergency Department following acute code stroke activation. Physical exam and imaging studies including non-contrast CT, CT angiography, CT perfusion, and MRI were performed.
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