Sharif Digital Repository

Background: We developed transformer-based deep learning models based on natural language processing for early risk assessment of Alzheimer’s disease from the picture description test. Methods: The lack of large datasets poses the most important limitation for using complex models that do not require feature engineering. Transformer-based pre-trained deep language models have recently made a large leap in NLP research and application. These models are pre-trained on available large datasets to understand natural language texts appropriately, and are shown to subsequently perform well on classification tasks with small training sets. The overall classification model is a simple classifier on... 

In this study, we are proposing a novel nonlinear classification approach to discriminate between Alzheimer's Disease (AD) and a control group using T1-weighted and T2-weighted Magnetic Resonance Images (MRI's) of brain. Since T1-weighted images and T2-weighted images have inherent physical differences, obviously each of them has its own particular medical data and hence, we extracted some specific features from each. Then the variations of the relevant eigenvalues of the extracted features were tracked to pick up the most informative ones. The final features were assigned to two parallel systems to be nonlinearly categorized. Considering the fact that AD defects the white and gray regions... 

Substantial terms have been recognized on the associated risk elements, comorbidities as well as, putative pathophysiological processes of Alzheimer disease and related dementias (ADRDs) as well as, type 2 diabetes mellitus (T2DM), a few from greatest important disease from the moments. Very much is considered regarding the biology and chemistry of each predicament, nevertheless T2DM and ADRDs are an actually similar pattern developing from the similar origins of maturing or synergistic conditions connected by aggressive patho-corporeal terms and continues to be ambiguous. In this depth-critique article, we aimed to investigate all possibilities and represented a novel and applicable... 

Substantial terms have been recognized on the associated risk elements, comorbidities as well as, putative pathophysiological processes of Alzheimer disease and related dementias (ADRDs) as well as, type 2 diabetes mellitus (T2DM), a few from greatest important disease from the moments. Very much is considered regarding the biology and chemistry of each predicament, nevertheless T2DM and ADRDs are an actually similar pattern developing from the similar origins of maturing or synergistic conditions connected by aggressive patho-corporeal terms and continues to be ambiguous. In this depth-critique article, we aimed to investigate all possibilities and represented a novel and applicable... 

Image fusion means to integrate information from one image to another image. Medical images according to the nature of the images are divided into structural (such as CT and MRI) and functional (such as SPECT, PET). This article fused MRI and PET images and the purpose is adding structural information from MRI to functional information of PET images. The images decomposed with Nonsubsampled Contourlet Transform and then two images were fused with applying fusion rules. The coefficients of the low frequency band are combined by a maximal energy rule and coefficients of the high frequency bands are combined by a maximal variance rule. Finally, visual and quantitative criteria were used to... 

In this paper, distributed electroencephalographic (EEG) sources in the brain have been mapped with the objective of early diagnosis of Alzheimer's disease (AD). To this end, records from a montage of a high-density EEG from 17 early AD patients and 17 matched healthy control subjects were considered. Subjects were in eyes-closed, resting-state condition. Cortical EEG sources were modeled by the standardized low-resolution brain electromagnetic tomography (sLORETA) method. Relative logarithmic power spectral density values were obtained in the four conventional frequency bands (alpha, beta, delta, and theta) and 12 cortical regions. Results show that in the left brain hemisphere, the theta... 

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... 

Currently, Alzheimer's disease (AD) accounts for more than half of all dementia cases. Although genetics, age, and environmental factors affect the disease, the cause of AD is not yet fully known. Various drugs have been proposed for the prevention and treatment of AD, but the delivery of these therapeutic agents to the brain is difficult. The blood–brain barrier prevents systemic drugs from accessing the central nervous system and designing a suitable system to overcome this barrier has attracted much attention. The intranasal pathway, given its proximity to the brain, provides a great opportunity for drug delivery. Understanding the physiological characteristics of the nose can be useful... 

Accumulation of amyloid beta (Aβ) soluble forms in the cerebral parenchyma is the mainstream concept underlying memory deficit in the early phase of Alzheimer's disease (AD). PKMζ plays a critical role in the maintenance of long-term memory. Yet, the role of this brain-specific enzyme has not been addressed in AD. We examined the impact of hippocampal PKMζ overexpression on AD-related memory impairment in rats. Oligomeric form of Aβ (oAβ) or vehicle was bilaterally microinjected into the dorsal hippocampus of male Wistar rats under stereotaxic surgery. One week later, 2 μl of lentiviral vector (108 T.U. / ml.) encoding PKMζ genome was microinjected into the dorsal hippocampus. Seven days... 

The high concentration of zinc metal ions in Aβ aggregations is one of the most cited hallmarks of Alzheimer's disease (AD), and several substantial pieces of evidence emphasize the key role of zinc metal ions in the pathogenesis of AD. In this study, while designing a multifunctional peptide for simultaneous targeting Aβ aggregation and chelating the zinc metal ion, a novel and comprehensive approach is introduced for evaluating the multifunctionality of a multifunctional drugs based on computational methods. The multifunctional peptide consists of inhibitor and chelator domains, which are included in the C-terminal hydrophobic region of Aβ, and the first four amino acids of human albumin.... 

Alzheimer’s disease (AD) is currently ranked as the sixth leading cause of death in the United States and recent estimates indicate that the disorder may rank third, just behind heart disease and cancer, as a cause of death for older people. Clearly, predicting this disease in the early stages and preventing it from progressing is of great importance. The diagnosis of Alzheimer’s disease (AD) requires a variety of medical tests, which leads to huge amounts of multivariate heterogeneous data. It can be difficult and exhausting to manually compare, visualize, and analyze this data due to the heterogeneous nature of medical tests, therefore, an efficient approach for accurate prediction of the... 

Alzheimer's Disease (AD) begins several years before the symptoms develop. It starts with Mild Cognitive Impairment (MCI) which can be separated into Early MCI and Late MCI (EMCI and LMCI). Functional connectivity analysis and classification are done among the different stages of illness with Functional Magnetic Resonance Imaging (fMRI). In this study, in addition to the four stages including healthy, EMCI, LMCI, and AD, the patients have been tracked for a year. Indeed, the classification has been done among 7 groups to analyze the functional connectivity changes in one year in different stages. After generating the functional connectivity graphs for eliminating the weak links, three... 

Formation of the amyloid beta (Aβ) peptide aggregations represents an indispensable role in appearing and progression of Alzheimer disease. β-sheet breaker peptides can be designed and modified with different amino acids in order to improve biological properties and binding affinity to the amyloid beta peptide. In the present study, three peptide sequences were designed based on the hopeful results of LIAIMA peptide and molecular docking studies were carried out onto the monomer and fibril structure of amyloid beta peptide using AutoDock Vina software. According to the obtained interactions and binding energy from docking, the best-designed peptide (D-GABA-FPLIAIMA) was chosen and... 

Functional magnetic resonance imaging (fMRI) is a non-invasive method that helps to analyze brain function based on BOLD signal fluctuations. Functional Connectivity (FC) catches the transient relationship between various brain regions usually measured by correlation analysis. The elements of the correlation matrix are between -1 to 1. Some of them are very small values usually related to weak and spurious correlations due to noises and artifacts. They can not be concluded as real strong correlations between brain regions and their existence could make a misconception and leads to fake results. It is crucial to make a conclusion based on reliable and informative correlations. In order to... 

Functional magnetic resonance imaging (fMRI) is a non-invasive method that helps to analyze brain function based on BOLD signal fluctuations. Functional Connectivity (FC) catches the transient relationship between various brain regions usually measured by correlation analysis. The elements of the correlation matrix are between -1 to 1. Some of them are very small values usually related to weak and spurious correlations due to noises and artifacts. They can not be concluded as real strong correlations between brain regions and their existence could make a misconception and leads to fake results. It is crucial to make a conclusion based on reliable and informative correlations. In order to... 

Slow-gamma (35-45 Hz) phase synchronization and the coupling between slow-gamma and low-frequency theta oscillations (4–8 Hz) are closely related to memory retrieval and cognitive functions. In this pilot study, we assess the Phase Amplitude Coupling (PAC) between theta and slow-gamma oscillatory bands and the quality of synchronization in slow-gamma oscillations using Phase Locking Value (PLV) on EEG data from healthy individuals and patients diagnosed with amnestic Mild Cognitive Impairment (aMCI) and Alzheimer's Disease (AD) during an oddball olfactory task. Our study indicates noticeable differences between the PLV and PAC values corresponding to olfactory stimulation in the three groups... 

Purpose: Alzheimer's disease (AD) starts years before its signs and symptoms including the dementia become apparent. Diagnosis of the AD in the early stages is important to reduce the speed of brain decline. Aim of the study: Identifying the alterations in the functional connectivity of the brain during the disease stages is among the main important issues in this regard. Therefore, in this study, the changes in the functional connectivity during the AD stages were analyzed. Materials and methods: By employing the functional magnetic resonance imaging (fMRI) data and graph theory, weighted undirected graphs of the whole-brain and default mode network (DMN) network were investigated... 

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... 

Alzheimer’s disease (AD) is an irreversible neurological disorder that progresses gradually and can cause severe cognitive and behavioral impairments. This disease is currently considered a social and economic incurable issue due to its complicated and multifactorial characteristics. Despite decades of extensive research, we still lack definitive AD diagnostic and effective therapeutic tools. Consequently, one of the most challenging subjects in modern medicine is the need for the development of new strategies for the treatment of AD. A large body of evidence indicates that amyloid-β (Aβ) peptide fibrillation plays a key role in the onset and progression of AD. Recent studies have reported... 

It is reported that approximately 40 million people are suffering from dementia, globally. Dementia is a group of symptoms that affect neurons and cause some mental disorders, such as losing memory. Alzheimer's disease (AD) which is known as the most common cause of dementia, is one of the top medical care concerns across the world. Although the exact sources of the disease are not understood, is it believed that aggregation of amyloid-beta (Aβ) outside of neuron cells and tau aggregation or neurofibrillary tangles (NFTs) formation inside the cell may play crucial roles. In this paper, we are going to review studies that targeted inhibition of amyloid plaque and tau protein tangle formation,...