Yanmei Li^1,*, Jinghong Tang¹, Weiwu Ding¹, Jian Luo², Naveed Ahmad³, Rajesh Kumar⁴

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 713-733, 2024, DOI:10.32604/cmc.2023.046872

Abstract Alzheimer’s disease (AD) is a complex, progressive neurodegenerative disorder. The subtle and insidious onset of its pathogenesis makes early detection of a formidable challenge in both contemporary neuroscience and clinical practice. In this study, we introduce an advanced diagnostic methodology rooted in the Med-3D transfer model and enhanced with an attention mechanism. We aim to improve the precision of AD diagnosis and facilitate its early identification. Initially, we employ a spatial normalization technique to address challenges like clarity degradation and unsaturation, which are commonly observed in imaging datasets. Subsequently, an attention mechanism is incorporated to selectively focus on the salient… More >

YAFEI WANG^1,2,#, JIELEI NI^1,#, YUHAN LIU², DINGYING LIAO³, QIANWEN ZHOU¹, XIAOYANG JI², GANG NIU², YANXIANG NI^1,*

BIOCELL, Vol.47, No.12, pp. 2567-2578, 2023, DOI:10.32604/biocell.2023.043781

Abstract Down syndrome (DS) is a genetic condition characterized by intellectual disability, delayed brain development, and early onset Alzheimer’s disease. The use of primary neural cells and tissues is important for understanding this disease, but there are ethical and practical issues, including availability from patients and experimental manipulability. Moreover, there are significant genetic and physiological differences between animal models and humans, which limits the translation of the findings in animal studies to humans. Advancements in induced pluripotent stem cells (iPSC) technology have revolutionized DS research by providing a valuable tool for studying the cellular and molecular pathologies associated with DS. Induced… More >

XIANGYU QUAN¹, XUETING MA¹, GUODONG LI², XUEQI FU¹, JIANGTAO LI¹, LINLIN ZENG^1,*

BIOCELL, Vol.47, No.10, pp. 2163-2176, 2023, DOI:10.32604/biocell.2023.031226

Abstract Exosomes are extracellular vesicles with a 30–150 nm diameter originating from endosomes. In recent years, scientists have regarded exosomes as an ideal small molecule carrier for the targeted treatment of Alzheimer’s disease (AD) across the blood-brain barrier due to their nanoscale size and low immunogenicity. A large amount of evidence shows that exosomes are rich in biomarkers, and it has been found that the changes in biomarker content in blood, cerebrospinal fluid, and urine are often associated with the onset of AD patients. In this paper, some recent advances in the use of exosomes in the treatment of AD are… More > Graphic Abstract

S M Hasan Mahmud^1,2, Md Mamun Ali³, Mohammad Fahim Shahriar¹, Fahad Ahmed Al-Zahrani⁴, Kawsar Ahmed^5,6,*, Dip Nandi¹, Francis M. Bui⁵

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3933-3948, 2023, DOI:10.32604/cmc.2023.039020

Abstract Alzheimer’s disease (AD) is a neurodevelopmental impairment that results in a person’s behavior, thinking, and memory loss. The most common symptoms of AD are losing memory and early aging. In addition to these, there are several serious impacts of AD. However, the impact of AD can be mitigated by early-stage detection though it cannot be cured permanently. Early-stage detection is the most challenging task for controlling and mitigating the impact of AD. The study proposes a predictive model to detect AD in the initial phase based on machine learning and a deep learning approach to address the issue. To build… More >

Athena George¹, Bejoy Abraham², Neetha George³, Linu Shine³, Sivakumar Ramachandran^4,*

Computer Systems Science and Engineering, Vol.47, No.2, pp. 2097-2118, 2023, DOI:10.32604/csse.2023.039262

Abstract Neurodegeneration is the gradual deterioration and eventual death of brain cells, leading to progressive loss of structure and function of neurons in the brain and nervous system. Neurodegenerative disorders, such as Alzheimer’s, Huntington’s, Parkinson’s, amyotrophic lateral sclerosis, multiple system atrophy, and multiple sclerosis, are characterized by progressive deterioration of brain function, resulting in symptoms such as memory impairment, movement difficulties, and cognitive decline. Early diagnosis of these conditions is crucial to slowing down cell degeneration and reducing the severity of the diseases. Magnetic resonance imaging (MRI) is widely used by neurologists for diagnosing brain abnormalities. The majority of the research… More >

XIRU XU^1,#, YUAN FANG^1,#, BIAO ZHANG^1,*, SHICHAO TENG¹, XIANG WU¹, JING ZHANG¹, XIAOQUN GU², MEIXIA MA³

BIOCELL, Vol.47, No.7, pp. 1595-1609, 2023, DOI:10.32604/biocell.2023.027697

Abstract Background: While the Bushen Yizhi Formula can treat Alzheimer’s disease (AD), the yet to be ascertained specific mechanism of action was explored in this work. Methods: Different concentrations of the Bushen Yizhi Formula and amyloid-beta peptide (Aβ) were used to treat rat pheochromocytoma cells (P12) and human neuroblastoma cells (SH-SY5Y). Cell morphological changes were observed to determine the in vitro cell damage. Cell Counting Kit (CCK)-8 assay and flow cytometry were employed to identify cell viability and apoptosis/cell cycle, respectively. Western blotting and immunohistochemistry were employed to measure the expressions of endoplasmic reticulum stress (ERS)-related proteins (GRP78 and CHOP), p-IRE1α,… More >

Jayashree Shetty¹, Nisha P. Shetty^1,*, Hrushikesh Kothikar¹, Saleh Mowla¹, Aiswarya Anand¹, Veeraj Hegde²

Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1345-1362, 2023, DOI:10.32604/iasc.2023.039206

Abstract Alzheimer’s disease (AD) is an intensifying disorder that causes brain cells to degenerate early and destruct. Mild cognitive impairment (MCI) is one of the early signs of AD that interferes with people’s regular functioning and daily activities. The proposed work includes a deep learning approach with a multimodal recurrent neural network (RNN) to predict whether MCI leads to Alzheimer’s or not. The gated recurrent unit (GRU) RNN classifier is trained using individual and correlated features. Feature vectors are concatenated based on their correlation strength to improve prediction results. The feature vectors generated are given as the input to multiple different… More >

Deepthi K. Oommen^*, J. Arunnehru

CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 793-811, 2023, DOI:10.32604/cmc.2023.038640

Abstract Alzheimer’s Disease (AD) is a progressive neurological disease. Early diagnosis of this illness using conventional methods is very challenging. Deep Learning (DL) is one of the finest solutions for improving diagnostic procedures’ performance and forecast accuracy. The disease’s widespread distribution and elevated mortality rate demonstrate its significance in the older-onset and younger-onset age groups. In light of research investigations, it is vital to consider age as one of the key criteria when choosing the subjects. The younger subjects are more susceptible to the perishable side than the older onset. The proposed investigation concentrated on the younger onset. The research used… More >

QIAN CHEN^1,#, XIN LEI^1,#, GUANHUA HU^1,#, YAN WANG², ZHENGQING FANG¹, GUOQUAN WANG¹, HANG SONG¹, SHU YE^1,*, BIAO CAI^1,*

BIOCELL, Vol.47, No.6, pp. 1265-1277, 2023, DOI:10.32604/biocell.2023.028811

Abstract Background: Huang-Pu-Tong-Qiao formula (HPTQ), a traditional Chinese herbal formula, has a variety of pharmacological effects. It has been used to treat Alzheimer’s disease (AD) for decades. This study aimed to screen differentially expressed proteins in the hippocampus of AD model rats treated with HPTQ. Proteomic studies of the effects of HPTQ on AD are key to understanding the therapeutic mechanisms of HPTQ and identifying potential therapeutic targets. Methods: We hence used the isobaric tags for relative and absolute quantification (ITRAQ) approach to investigate the differentially expressed proteins in the hippocampus of AD model rats before and after HPTQ administration and… More >

Amer Alsaraira^1,*, Samer Alabed¹, Eyad Hamad¹, Omar Saraereh²

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 165-177, 2023, DOI:10.32604/iasc.2023.036950

Abstract Alzheimer’s disease (AD) is a kind of progressive dementia that is frequently accompanied by brain shrinkage. With the use of the morphological characteristics of MRI brain scans, this paper proposed a method for diagnosing moderate cognitive impairment (MCI) and AD. The anatomical features of 818 subjects were calculated using the FreeSurfer software, and the data were taken from the ADNI dataset. These features were first removed from the dataset after being preprocessed with an age correction algorithm using linear regression to estimate the effects of normal aging. With these preprocessed characteristics, the extreme learning machine served as a classifier for… More >