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alzheimer-disease
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Transformer-based deep neural network language models for Alzheimer’s disease risk assessment from targeted speech
, Article BMC Medical Informatics and Decision Making ; Volume 21, Issue 1 , 2021 ; 14726947 (ISSN) ; Aghajan, H ; Soleymani Baghshah, M ; Sharif University of Technology
BioMed Central Ltd
2021
Abstract
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...
Parallel nonlinear analysis of weighted brain's gray and white matter images for Alzheimer's dementia diagnosis
, Article Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference ; 2010 , Pages 5573-5576 ; 1557170X (ISSN) ; Torabi, M ; Kim, K ; Sharif University of Technology
2010
Abstract
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...
A perspective to the correlation between brain insulin resistance and alzheimer: medicinal chemistry approach
, Article Current Diabetes Reviews ; Volume 15, Issue 4 , 2019 , Pages 255-258 ; 15733998 (ISSN) ; Bagherzadeh, M ; Rabiee, M ; Sharif University of Technology
Bentham Science Publishers
2019
Abstract
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...
A perspective to the correlation between brain insulin resistance and Alzheimer: Medicinal chemistry approach
, Article Current Diabetes Reviews ; Volume 15, Issue 4 , 2019 , Pages 255-258 ; 15733998 (ISSN) ; Bagherzadeh, M ; Rabiee, M ; Sharif University of Technology
Bentham Science Publishers
2019
Abstract
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...
MRI-PET image fusion based on NSCT transform using local energy and local variance fusion rules
, Article Journal of Medical Engineering and Technology ; Vol. 38, issue. 4 , 2014 , p. 211-219 ; Fatemizadeh, E ; Behnam, H ; Sharif University of Technology
Abstract
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...
Diagnosis of early Alzheimer's disease based on EEG source localization and a standardized realistic head model
, Article IEEE Journal of Biomedical and Health Informatics ; Volume 17, Issue 6 , 2013 , Pages 1039-1045 ; 21682194 (ISSN) ; Zahedi, E ; Jalili, M ; Keikhosravi, A ; Vahdat, B. V ; Sharif University of Technology
2013
Abstract
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...
Synchronizability of EEG-based functional networks in early alzheimer's disease
, Article IEEE Transactions on Neural Systems and Rehabilitation Engineering ; Volume 20, Issue 5 , 2012 , Pages 636-641 ; 15344320 (ISSN) ; Jalili, M ; Knyazeva, M. G ; Sharif University of Technology
IEEE
2012
Abstract
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...
Polymeric nanoparticles for nasal drug delivery to the brain: relevance to alzheimer's disease
, Article Advanced Therapeutics ; Volume 4, Issue 3 , 2021 ; 23663987 (ISSN) ; Ahmadi, S ; Afshari, R ; Khalaji, S ; Rabiee, M ; Bagherzadeh, M ; Fatahi, Y ; Dinarvand, R ; Tahriri, M ; Tayebi, L ; Hamblin, M. R ; Webster, T. J ; Sharif University of Technology
Blackwell Publishing Ltd
2021
Abstract
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...
Overexpression of protein kinase Mζ in the hippocampus mitigates alzheimer's disease-related cognitive deficit in rats
, Article Brain Research Bulletin ; Volume 166 , 2021 , Pages 64-72 ; 03619230 (ISSN) ; Roosta Azad, R ; Motamedi, F ; Mirzapour Delavar, H ; Ghasemi, S ; Aliakbari, S ; Pourbadie, H. G ; Sharif University of Technology
Elsevier Inc
2021
Abstract
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...
Evaluating the multifunctionality of a new modulator of zinc-induced Aβ aggregation using a novel computational approach
, Article Journal of Chemical Information and Modeling ; Volume 61, Issue 3 , 2021 , Pages 1383-1401 ; 15499596 (ISSN) ; Shamloo, A ; Sharif University of Technology
American Chemical Society
2021
Abstract
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 early diagnosis using manifold-based semi-supervised learning
, Article Brain Sciences ; Volume 7, Issue 8 , 2017 ; 20763425 (ISSN) ; Habibollahi Saatlou, F ; Mohammadzade, H ; Sharif University of Technology
Abstract
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...
Multiclass classification of patients during different stages of Alzheimer's disease using fMRI time-series
, Article Biomedical Physics and Engineering Express ; Volume 6, Issue 5 , 2020 ; Fatemizadeh, E ; Motie Nasrabadi, A ; Sharif University of Technology
IOP Publishing Ltd
2020
Abstract
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...
Design of peptide-based inhibitor agent against amyloid-β aggregation: Molecular docking, synthesis and in vitro evaluation
, Article Bioorganic Chemistry ; Volume 102 , September , 2020 ; Erfani, M ; Bavi, O ; Khazaei, S ; Sharifzadeh, M ; Hajiramezanali, M ; Beiki, D ; Shamloo, A ; Sharif University of Technology
Academic Press Inc
2020
Abstract
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...
Deep sparse graph functional connectivity analysis in AD patients using fMRI data
, Article Computer Methods and Programs in Biomedicine ; Volume 201 , 2021 ; 01692607 (ISSN) ; Fatemizadeh, E ; Motie Nasrabadi, A ; Sharif University of Technology
Elsevier Ireland Ltd
2021
Abstract
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...
Deep sparse graph functional connectivity analysis in AD patients using fMRI data
, Article Computer Methods and Programs in Biomedicine ; Volume 201 , 2021 ; 01692607 (ISSN) ; Fatemizadeh, E ; Motie Nasrabadi, A ; Sharif University of Technology
Elsevier Ireland Ltd
2021
Abstract
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...
Directed functional networks in Alzheimer's disease: disruption of global and local connectivity measures
, Article IEEE Journal of Biomedical and Health Informatics ; Volume 21, Issue 4 , 2017 , Pages 949-955 ; 21682194 (ISSN) ; Jalili, M ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2017
Abstract
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...
Recent advances in the design and applications of amyloid-β peptide aggregation inhibitors for Alzheimer’s disease therapy
, Article Biophysical Reviews ; Volume 11, Issue 6 , 2019 , Pages 901-925 ; 18672450 (ISSN) ; Khazaei, S ; Behnammanesh, H ; Shamloo, A ; Erfani, M ; Beiki, D ; Bavi, O ; Sharif University of Technology
Springer
2019
Abstract
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...
Review on alzheimer's disease: inhibition of amyloid beta and tau tangle formation
, Article International Journal of Biological Macromolecules ; Volume 167 , 2021 , Pages 382-394 ; 01418130 (ISSN) ; Hadi Zadeh, E ; Hasan Khan, R ; Sharif University of Technology
Elsevier B.V
2021
Abstract
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,...