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The brain compensatory mechanisms and Alzheimer's disease progression:a new protective strategy
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作者 Natalia Bobkova Vasily Vorobyov 《Neural Regeneration Research》 SCIE CAS CSCD 2015年第5期696-697,共2页
Compensatory/adaptive mechanisms in the brain are hy- pothesized to be involved in its protection from the Alz- heimer's disease (AD) progression. These mechanisms are activated by malfunctioning of various brain s... Compensatory/adaptive mechanisms in the brain are hy- pothesized to be involved in its protection from the Alz- heimer's disease (AD) progression. These mechanisms are activated by malfunctioning of various brain systems: anti- oxidant, neurotrophic, neurotransmitter, immune, and oth- ers. Detailed analysis of compensatory^adaptive capabilities of these systems might be a start point for further discovery and development of perspective approaches for early diag- nostics and treatment of AD and associated neurodegenera- tive disorders. 展开更多
关键词 The brain compensatory mechanisms and Alzheimer’s disease progression AD
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The compensatory phenomenon of the functional connectome related to pathological biomarkers in individuals with subjective cognitive decline 被引量:8
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作者 Haifeng Chen Xiaoning Sheng +6 位作者 Caimei Luo Ruomeng Qin Qing Ye Hui Zhao Yun Xu Feng Bai 《Translational Neurodegeneration》 SCIE CAS 2020年第2期234-247,共14页
Background Subjective cognitive decline(SCD)is a preclinical stage along the Alzheimer’s disease(AD)continuum.However,little is known about the aberrant patterns of connectivity and topological alterations of the bra... Background Subjective cognitive decline(SCD)is a preclinical stage along the Alzheimer’s disease(AD)continuum.However,little is known about the aberrant patterns of connectivity and topological alterations of the brain functional connectome and their diagnostic value in SCD.Methods Resting-state functional magnetic resonance imaging and graph theory analyses were used to investigate the alterations of the functional connectome in 66 SCD individuals and 64 healthy controls(HC).Pearson correlation analysis was computed to assess the relationships among network metrics,neuropsychological performance and pathological biomarkers.Finally,we used the multiple kernel learning-support vector machine(MKL-SVM)to differentiate the SCD and HC individuals.Results SCD individuals showed higher nodal topological properties(including nodal strength,nodal global efficiency and nodal local efficiency)associated with amyloid-βlevels and memory function than the HC,and these regions were mainly located in the default mode network(DMN).Moreover,increased local and medium-range connectivity mainly between the bilateral parahippocampal gyrus(PHG)and other DMN-related regions was found in SCD individuals compared with HC individuals.These aberrant functional network measures exhibited good classification performance in the differentiation of SCD individuals from HC individuals at an accuracy up to 79.23%.Conclusion The findings of this study provide insight into the compensatory mechanism of the functional connectome underlying SCD.The proposed classification method highlights the potential of connectome-based metrics for the identification of the preclinical stage of AD. 展开更多
关键词 Subjective cognitive decline rs-fMRI Machine learning compensatory mechanism
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