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40 articles for “Alzheimer's Disease (AD)”
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An Integrated Study to Extrapolate the Interaction of NMDAR with Potential Ligands for the Treatment of Alzheimer’s Disease Symptoms
Abstract: Objective: Alzheimer’s disease (AD) is the most common neurodegenerative disease affecting the health status of older adults especially those above the age of 60 years. As an outcome, two types of medications have been developed for the treatment of its symptoms which are acetylcholinesterase (AChE) and N-methyl-D-aspartate receptor (NMDAR) antagonist. This paper uses the computational approach to understand the interaction of NMDAR with four major phytocompounds (curcumin, L-epicatechin, ginsenosides, and …
Published in International Journal of Biochemistry and Biomolecule Research · Vol. 1, Issue 1, 2023 · pp. 15–27 Read article
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Non-Enzymatic Glycation in Alzheimer’s and Parkinson’s Disease: A Molecular Approach to Pathology and Recent Advances
Abstract: Non-enzymatic glycation, a biochemical process by which reducing sugars spontaneously bind to proteins, leads to the formation of advanced glycation end-products (AGEs), which have emerged as critical contributors to the pathogenesis of several neurodegenerative diseases, particularly Alzheimer’s disease (AD) and Parkinson’s disease (PD). The accumulation of AGEs can significantly alter protein structure, stability, and function, triggering a cascade of detrimental effects, including increased oxidative stress, heightened neuroinflammation, and the promotion …
Published in International Journal of Molecular Biotechnological Research · Vol. 2, Issue 2, 2024 · pp. 36–41 Read article
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A Comprehensive Review on Neturaceuticals in Alzheimer's and Neurodegenerative Disease an Cognitive Enhancement
Abstract: Neurodegenerative diseases, including Alzheimers disease (AD), Parkinsons disease (PD), and related cognitive disorders, represent a significant and growing public health challenge, particularly in aging populations. Despite advances in pharmacological treatments, therapeutic options for cognitive decline and neurodegeneration remain limited. Recent interest has shifted towards nutraceuticals— bioactive compounds derived from food or natural sources—as promising adjuncts or alternatives in the management of these conditions. This review examines how nutraceuticals can help …
Published in International Journal of Brain Sciences · Vol. 2, Issue 1, 2025 · pp. 1–9 Read article
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In Silico Analysis and Docking Study of the Active Phyto Compounds of Ginkgo Biloba Against Alzheimer's Amyloid-Beta Protein
Abstract: Objective: Alzheimer's disease, an age-related progressive neurological condition, arises due to the accumulation of amyloid-beta protein within the brain. In this study, an attempt was made to explore the potential of natural compounds derived from Ginkgo, known for their diverse medicinal properties, in the prevention of the disorder by employing molecular docking techniques, conducting drug-likeness prediction assessments, and performing ADME analysis. Methods: Amyloid beta protein was retrieved from the PDB …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 1, Issue 2, 2023 Read article
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Study on Chemical Insights into Alzheimer's Disease: Amyloid Beta and Tau Protein Interactions
Abstract: Background: Alzheimers disease (AD) is the most prevalent form of dementia, affecting millions of individuals worldwide and posing significant challenges to healthcare systems. The disease is characterized by a gradual decline in cognitive functions, particularly memory, reasoning, and the ability to perform daily activities. Aim & objective: To study chemical insights in alzheimers disease, especially amyloid beta and tau protein interactions Results & discussion: The results of this review highlight …
Published in International Journal of Brain Sciences · Vol. 2, Issue 1, 2025 · pp. 37–46 Read article
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Alzheimer’s Disease Classification Based on Transfer Learning of New-CNN Model
Abstract: The long-term, irreversible brain disorder “Alzheimer’s disease (AD)” currently has no known cure. Nonetheless, current medications may impede their advancement. Globally, those over 65 are the primary population affected by Alzheimer’s disease. Accurate detection of this condition requires early diagnosis. Because there are so many people who come with an ailment, manual diagnosis by health specialists is laborious and prone to error. Early detection of AD is a difficult undertaking …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 3, 2025 · pp. 16–23 Read article
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Analysis of White Matter, Gray Matter, and Cerebrospinal Fluid Alterations in Neurological Disorders: A Deep Learning Approach
Abstract: This paper investigates the role of white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) alterations in the pathophysiology of neurological disorders, including Alzheimer’s disease, Parkinson’s disease, schizophrenia, and epilepsy. By leveraging advanced deep learning methodologies, we aim to automate the segmentation and analysis of brain structures from MRI scans, enabling a more detailed and precise evaluation of their roles in disease progression. These techniques allow for the identification …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 14, Issue 3, 2024 · pp. 21–27 Read article
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In Silico Analysis and Docking Study of the Active Phytocompounds of Bacopa monnieri Against Alzheimer Disease
Abstract: Objective: Alzheimer’s is a neurodegenerative disease and is the cause of 60–70% of cases of dementia. It infected a million people worldwide. An effort was undertaken to explore the potential of natural compounds found in Bacopa monnieri, a plant renowned for its extensive medicinal properties in Indian Ayurveda, to combat the disease. This was achieved through molecular docking studies, evaluation of drug-likeness, and comprehensive ADME (absorption, distribution, metabolism, and excretion) …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 2, 2024 · pp. 1–13 Read article
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An Overview of Artificially Generated Neural Networks Inside the Brain’s Structure in an Alzheimer’s Disease Patient
Abstract: Alzheimer’s disease produces significant neuronal loss, while the precise mechanisms and timing are yet unknown. Other types of cell death, such necroptosis, parthanatosis, ferroptosis, and cuproptosis, need further investigation. Based on brain images of people with mild cognitive impairment, this study assesses artificial neural networks (ANNs) used to diagnose and predict Alzheimer’s disease (AD). This research was conducted considering growing recognition among researchers and medical professionals regarding the importance of …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 2, 2025 Read article
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High-Definition Electroencephalography: A New Horizon in Neurological Pathology Research
Abstract: The advent of high-density electroencephalography (HD-EEG) has catalyzed a paradigm shift in the exploration of neurological pathologies. This editorial underscore its transformative potential in elucidating brain dynamics and refining diagnostic approaches for a spectrum of conditions, spanning from epilepsy and dementia to cognitive impairments in preterm infants. Our objective is to optimize the utility of HD-EEG by emphasizing the imperative for methodological homogenization and fostering collaborative endeavors. The remarkable spatial …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 14, Issue 2, 2024 · pp. 15–21 Read article
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Detection and Classification of Alzheimer’s Disease Using Deep Learning Technique
Abstract: It is crucial that people with Alzheimer's disease (AD) receive a proper diagnosis to begin preventative action before irreparable brain damage develops. Most people who suffer from Alzheimer's disease (AD), a neurological condition that progresses, are older than 65. The area of interest (ROI) in the hippocampus has been extensively studied for several purposes, including neurological illness research, stress development monitoring, and memory function analysis. Moreover, a connection between Alzheimer's …
Published in Recent Trends in Sensor Research & Technology · Vol. 12, Issue 1, 2025 · pp. 15–20 Read article
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Artificial Intelligence in Early Diagnosis and Personalized Treatment of Alzheimer’s Disease
Abstract: Artificial intelligence (AI) has become a disruptive technology in the medical care industry, with potential solutions to early diagnosis and customized treatment of Alzheimer’s disease (AD), a progressive neurodegenerative disease and the most prevalent cause of dementia globally. Conventional diagnostic techniques, such as cognitive, neuroimaging and biomarker techniques, are usually limited in the ability to detect disease at its most susceptible stage when treatment interventions are most effective. The recent …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 · pp. 15–27 Read article
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Samelisant, an H3 Receptor Agonist as an Anti-Alzheimer Potential – A Pilot Study on Molecular Docking
Abstract: Neurodegenerative diseases have become more prevalent and about 55 million of the population are affected by dementia globally. One of the most important neurodegenerative diseases is Alzheimer’s disease which is known for its effect on memory and cognitive impairment. Alzheimer’s disease (AD) is an area of intense scientific investigation due to its high prevalence and the lack of a definitive cure. Amyloid precursor protein plays a central role in Alzheimer’s …
Published in International Journal of Brain Sciences · Vol. 3, Issue 1, 2026 · pp. 15–26 Read article
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Deep Learning-Based Alzheimer’s Disease Detection: A CNN Approach
Abstract: Alzheimer’s disease (AD) is a neurological condition that worsens with time and impairs a patient’s quality of life by causing cognitive loss. For prompt intervention and management of AD, early identification is essential. In this work, we propose a deep learning-based method for automatically classifying Alzheimer’s disease from medical imaging data using convolutional neural networks (CNNs). Our algorithm is intended to evaluate brain MRI images and detect anatomical variations suggestive …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 3, 2025 Read article
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Early Detection of Alzheimer’s Disease Using Machine Learning Techniques
Abstract: Alzheimer's Disease (AD) is a progressive neurodegenerative condition impacting a large global population. Detecting AD early is critical for timely intervention and effective management. Conventional diagnostic approaches involve cognitive assessments and neuroimaging, which are often lengthy, costly, and prone to human error. In this paper, we propose a novel approach for early detection of AD using machine learning techniques applied to multimodal data, including neuroimaging, cognitive assessments, and biomarkers. Our …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 14, Issue 2, 2024 · pp. 32–43 Read article
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Early Alzheimer’s Disease Prediction Using Vision Transformers and Attention-Guided MRI Analysis
Abstract: Alzheimer’s Disease (AD) continues to be a major global health concern, with early detection being crucial for effective intervention. While conventional machine learning and convolutional neural network (CNN) approaches have made notable progress in automated AD diagnosis using MRI data, they often struggle with capturing long-range dependencies and maintaining spatial contextual awareness. In this research, we propose a novel framework using Vision Transformers (ViTs) for early Alzheimer’s prediction from 3D …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 30–40 Read article
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Kisunla (Donanemab): A Novel Breakthrough Illuminating a Path to Better Alzheimer’s Outcomes
Abstract: Background: Alzheimer’s disease (AD) is a progressive neurodegenerative condition marked by cognitive decline, memory loss, and loss of independence. Despite decades of extensive research, disease-modifying treatments have been limited in success. Recent therapeutic advancements have led to the development of monoclonal antibodies targeting amyloid-beta (Aβ) plaques, particularly the pyroglutamate-modified variant, a key pathological hallmark of AD. Objectives: This review aims to explore the therapeutic potential of Donanemab (Kisunla), a novel …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 3, 2025 · pp. 37–45 Read article
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Neurodegeneration and Cognitive Decline: Causes, Consequences, and Treatment Approaches
Abstract: Neurodegenerative diseases gradually destroy nerve cells, often leading to fatal outcomes. The phrase includes a wide range of clinical problems, such as a variety of Neurological conditions include movement disorders, like Parkinson’s disease (PD) and progressive cognitive impairments, with Alzheimer’s disease (AD) being the most common among them. A loss of neurones and synaptic connections, typically in later life, is a prevalent feature of Usually, the onset and development of …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 3, Issue 1, 2025 · pp. 47–59 Read article
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A Dual-Model Deep Learning Framework for Early Alzheimer’s Detection Using Clinical Data and Neuroimaging with Architectural Performance Analysis
Abstract: Alzheimer’s disease (AD) poses a significant global health challenge due to its increasing prevalence and the absence of definitive cures. Early diagnosis is crucial for effective intervention and management. This study presents a dual-model deep learning framework for the early detection and classification of AD using both structured clinical data and neuroimaging datasets. Model 1 utilizes a greedy layer-wise autoencoder approach applied to structured data, achieving optimal binary classification accuracy …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 1–12 Read article
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Drugs for Alzheimer’s Disease from Salix Alba Discovered Computationally Utilizing Virtual Screening and Docking against 1b41 Protein
Abstract: Objective : The of this research is to evaluate the feasibility of using molecular docking techniques to identify novel acetylcholinesterase, a key enzyme implicated in the pathogenesis of Alzheimer’s disease, a neurodegenerative disorder with a gradual but steady progression to death, due to the gradual accumulation of beta-plaques and neurofibrillary tangles, as well as a decline in acetylcholine levels. Due to its function in converting acetylcholine into acyl and choline …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 1, Issue 2, 2023 · pp. 07–19 Read article