Sharif Digital Repository

According to the Amyloid hypothesis, as the foremost scientific explanation for Alzheimer Disease (AD), the neuropathology of AD is related to toxic fragments of amyloid beta (Aβ) protein. Based on this hypothesis, an attractive therapeutic approach was demonstrated to identify multifunctional peptides able to modulate Aβ pathologies as the source of AD. On this premise, a bifunctional polypeptide based on the iAβ5p lead compound, was designed to inhibit Aβ aggregation and free metal ions. Herein, the efficacy of this novel drug in Zn2+ and Cd2+ ion chelation was examined through an integrated technique comprising combined Docking, QM, and MD simulations. MD relaxation of a set of probable... 

Recently graph theory and complex networks have been widely used as a mean to model functionality of the brain. Among different neuroimaging techniques available for constructing the brain functional networks, electroencephalography (EEG) with its high temporal resolution is a useful instrument of the analysis of functional interdependencies between different brain regions. Alzheimer's disease (AD) is a neurodegenerative disease, which leads to substantial cognitive decline, and eventually, dementia in aged people. To achieve a deeper insight into the behavior of functional cerebral networks in AD, here we study their synchronizability in 17 newly diagnosed AD patients compared to 17 healthy... 

In this study, we have proposed a novel method investigates MR-Images for normal and abnormal brains which effected by Alzheimer's Disease (AD) to extract 336 number of different features based on texture analysis. Before applying this algorithm, we have to use a registration method because of variety in size of normal and abnormal images. Consequently, the output of Texture Analysis System (TAS) is a vector containing 336 elements that are features extracted from texture. This vector is considered as the input of the Artificial Neural Network (ANN) which is feed-forward one. The features extracted from the Gray-level Co-occurrence Matrix (GLCM) have been interpreted and compared with normal... 

Techniques available in graph theory can be applied to signals recorded from human brain. In network analysis of EEG signals, the individual nodes are EEG sensor locations and the edges correspond to functional relations between them that are extracted from EEG time series. In this paper, we study EEG-based directed functional networks in Alzheimer's disease (AD). To this end, directed connectivity matrices of 25 AD patients and 26 healthy subjects are processed and a number of meaningful graph theory metrics are studied. Our data show that functional networks of AD brains have significantly reduced global connectivity in alpha and beta bands (P < 0.05). The AD brains have significantly...