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disease</title> <meta name="description" content="Search results for: Alzheimer’s disease"> <meta name="keywords" content="Alzheimer’s disease"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none 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action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="Alzheimer’s disease"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 3817</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: Alzheimer’s disease</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3817</span> Alzheimer’s Disease Measured in Work Organizations</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Katherine%20Denise%20Queri">Katherine Denise Queri</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The effects of sick workers have an impact in administration of labor. This study aims to provide knowledge on the disease that is Alzheimer’s while presenting an answer to the research question of when and how is the disease considered as a disaster inside the workplace. The study has the following as its research objectives: 1. Define Alzheimer’s disease, 2. Evaluate the effects and consequences of an employee suffering from Alzheimer’s disease, 3. Determine the concept of organizational effectiveness in the area of Human Resources, and 4. Identify common figures associated with Alzheimer’s disease. The researcher gathered important data from books, video presentations, and interviews of workers suffering from Alzheimer’s disease and from the internet. After using all the relevant data collection instruments mentioned, the following data emerged: 1. Alzheimer’s disease has certain consequences inside the workplace, 2. The occurrence of Alzheimer’s Disease in an employee’s life greatly affects the company where the worker is employed, and 3. The concept of workplace efficiency suggests that an employer must prepare for such disasters that Alzheimer’s disease may bring to the company where one is employed. Alzheimer’s disease can present disaster in any workplace. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=administration" title="administration">administration</a>, <a href="https://publications.waset.org/abstracts/search?q=Alzheimer%27s%20disease" title=" Alzheimer's disease"> Alzheimer's disease</a>, <a href="https://publications.waset.org/abstracts/search?q=conflict" title=" conflict"> conflict</a>, <a href="https://publications.waset.org/abstracts/search?q=disaster" title=" disaster"> disaster</a>, <a href="https://publications.waset.org/abstracts/search?q=employment" title=" employment"> employment</a> </p> <a href="https://publications.waset.org/abstracts/33630/alzheimers-disease-measured-in-work-organizations" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/33630.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">445</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3816</span> Molecular Interaction of Acetylcholinesterase with Flavonoids Involved in Neurodegenerative Diseases</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=W.%20Soufi">W. Soufi</a>, <a href="https://publications.waset.org/abstracts/search?q=F.%20Boukli%20Hacene"> F. Boukli Hacene</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Ghalem"> S. Ghalem</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Alzheimer's disease (AD) is a neurodegenerative disease that leads to a progressive and permanent deterioration of nerve cells. This disease is progressively accompanied by an intellectual deterioration leading to psychological manifestations and behavioral disorders that lead to a loss of autonomy. It is the most frequent of degenerative dementia. Alzheimer's disease (AD), which affects a growing number of people, has become a major public health problem in a few years. In the context of the study of the mechanisms governing the evolution of AD disease, we have found that natural flavonoids are good acetylcholinesterase inhibitors that reduce the rate of ßA secretion in neurons. This work is to study the inhibition of acetylcholinesterase (AChE) which is an enzyme involved in Alzheimer's disease, by methods of molecular modeling. These results will probably help in the development of an effective therapeutic tool in the fight against the development of Alzheimer's disease. Our goal of the research is to study the inhibition of acetylcholinesterase (AChE) by molecular modeling methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alzheimer%27s%20disease" title="Alzheimer's disease">Alzheimer's disease</a>, <a href="https://publications.waset.org/abstracts/search?q=acetylcholinesterase" title=" acetylcholinesterase"> acetylcholinesterase</a>, <a href="https://publications.waset.org/abstracts/search?q=flavonoids" title=" flavonoids"> flavonoids</a>, <a href="https://publications.waset.org/abstracts/search?q=molecular%20modeling" title=" molecular modeling"> molecular modeling</a> </p> <a href="https://publications.waset.org/abstracts/156249/molecular-interaction-of-acetylcholinesterase-with-flavonoids-involved-in-neurodegenerative-diseases" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/156249.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">105</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3815</span> Synthesis of Metal Curcumin Complexes with Iron(III) and Manganese(II): The Effects on Alzheimer's Disease</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Emel%20Yildiz">Emel Yildiz</a>, <a href="https://publications.waset.org/abstracts/search?q=Nurcan%20Bi%C3%A7er"> Nurcan Biçer</a>, <a href="https://publications.waset.org/abstracts/search?q=Fazilet%20Aksu"> Fazilet Aksu</a>, <a href="https://publications.waset.org/abstracts/search?q=Arash%20Alizadeh%20Yegani"> Arash Alizadeh Yegani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Plants provide the wealth of bioactive compounds, which exert a substantial strategy for the treatment of neurological disorders such as Alzheimer's disease. Recently, a lot of studies have explored the medicinal properties of curcumin, including antitumoral, antimicrobial, anti-inflammatory, antioxidant, antiviral, and anti-Alzheimer's disease effects. Metal complexes of curcumin (1,7-bis(4-hydroxy-3-methoxyphenyl)-1,6-heptadiene-3,5-dione) were synthesized with Mn(II) and Fe(III). The structures of synthesized metal complexes have been characterized by using spectroscopic and analytic methods such as elemental analysis, magnetic susceptibility, FT-IR, AAS, TG and argentometric titration. It was determined that the complexes have octahedral geometry. The effects of the metal complexes on the disorder of memory, which is an important symptom of Alzheimer's Disease were studied on lab rats with Plus-Maze Tests at Behavioral Pharmacology Laboratory. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=curcumin" title="curcumin">curcumin</a>, <a href="https://publications.waset.org/abstracts/search?q=Mn%28II%29" title=" Mn(II)"> Mn(II)</a>, <a href="https://publications.waset.org/abstracts/search?q=Fe%28III%29" title=" Fe(III)"> Fe(III)</a>, <a href="https://publications.waset.org/abstracts/search?q=Alzheimer%20disease" title=" Alzheimer disease"> Alzheimer disease</a>, <a href="https://publications.waset.org/abstracts/search?q=beta%20amyloid%2025-35" title=" beta amyloid 25-35"> beta amyloid 25-35</a> </p> <a href="https://publications.waset.org/abstracts/60623/synthesis-of-metal-curcumin-complexes-with-ironiii-and-manganeseii-the-effects-on-alzheimers-disease" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/60623.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">301</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3814</span> 3 Dimensional (3D) Assesment of Hippocampus in Alzheimer’s Disease</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mehmet%20Bulent%20Ozdemir">Mehmet Bulent Ozdemir</a>, <a href="https://publications.waset.org/abstracts/search?q=Sultan%20%C3%87agirici"> Sultan Çagirici</a>, <a href="https://publications.waset.org/abstracts/search?q=Sahika%20Pinar%20Akyer"> Sahika Pinar Akyer</a>, <a href="https://publications.waset.org/abstracts/search?q=Fikri%20Turk"> Fikri Turk</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Neuroanatomical appearance can be correlated with clinical or other characteristics of illness. With the introduction of diagnostic imaging machines, producing 3D images of anatomic structures, calculating the correlation between subjects and pattern of the structures have become possible. The aim of this study is to examine the 3D structure of hippocampus in cases with Alzheimer disease in different dementia severity. For this purpose, 62 female and 38 male- 68 patients’s (age range between 52 and 88) MR scanning were imported to the computer. 3D model of each right and left hippocampus were developed by a computer aided propramme-Surf Driver 3.5. Every reconstruction was taken by the same investigator. There were different apperance of hippocampus from normal to abnormal. In conclusion, These results might improve the understanding of the correlation between the morphological changes in hippocampus and clinical staging in Alzheimer disease. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alzheimer%20disease" title="Alzheimer disease">Alzheimer disease</a>, <a href="https://publications.waset.org/abstracts/search?q=hippocampus" title=" hippocampus"> hippocampus</a>, <a href="https://publications.waset.org/abstracts/search?q=computer-assisted%20anatomy" title=" computer-assisted anatomy"> computer-assisted anatomy</a>, <a href="https://publications.waset.org/abstracts/search?q=3D" title=" 3D "> 3D </a> </p> <a href="https://publications.waset.org/abstracts/34377/3-dimensional-3d-assesment-of-hippocampus-in-alzheimers-disease" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/34377.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">481</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3813</span> Neural Network Based Decision Trees Using Machine Learning for Alzheimer's Diagnosis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=P.%20S.%20Jagadeesh%20Kumar">P. S. Jagadeesh Kumar</a>, <a href="https://publications.waset.org/abstracts/search?q=Tracy%20Lin%20Huan"> Tracy Lin Huan</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Meenakshi%20Sundaram"> S. Meenakshi Sundaram</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Alzheimer’s disease is one of the prevalent kind of ailment, expected for impudent reconciliation or an effectual therapy is to be accredited hitherto. Probable detonation of patients in the upcoming years, and consequently an enormous deal of apprehension in early discovery of the disorder, this will conceivably chaperon to enhanced healing outcomes. Complex impetuosity of the brain is an observant symbolic of the disease and a unique recognition of genetic sign of the disease. Machine learning alongside deep learning and decision tree reinforces the aptitude to absorb characteristics from multi-dimensional data’s and thus simplifies automatic classification of Alzheimer’s disease. Susceptible testing was prophesied and realized in training the prospect of Alzheimer’s disease classification built on machine learning advances. It was shrewd that the decision trees trained with deep neural network fashioned the excellent results parallel to related pattern classification. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alzheimer%27s%20diagnosis" title="Alzheimer's diagnosis">Alzheimer's diagnosis</a>, <a href="https://publications.waset.org/abstracts/search?q=decision%20trees" title=" decision trees"> decision trees</a>, <a href="https://publications.waset.org/abstracts/search?q=deep%20neural%20network" title=" deep neural network"> deep neural network</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a>, <a href="https://publications.waset.org/abstracts/search?q=pattern%20classification" title=" pattern classification"> pattern classification</a> </p> <a href="https://publications.waset.org/abstracts/77725/neural-network-based-decision-trees-using-machine-learning-for-alzheimers-diagnosis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/77725.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">297</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3812</span> Reminiscence Therapy for Alzheimer’s Disease Restrained on Logistic Regression Based Linear Bootstrap Aggregating</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=P.%20S.%20Jagadeesh%20Kumar">P. S. Jagadeesh Kumar</a>, <a href="https://publications.waset.org/abstracts/search?q=Mingmin%20Pan"> Mingmin Pan</a>, <a href="https://publications.waset.org/abstracts/search?q=Xianpei%20Li"> Xianpei Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Yanmin%20Yuan"> Yanmin Yuan</a>, <a href="https://publications.waset.org/abstracts/search?q=Tracy%20Lin%20Huan"> Tracy Lin Huan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Researchers are doing enchanting research into the inherited features of Alzheimer’s disease and probable consistent therapies. In Alzheimer’s, memories are extinct in reverse order; memories formed lately are more transitory than those from formerly. Reminiscence therapy includes the conversation of past actions, trials and knowledges with another individual or set of people, frequently with the help of perceptible reminders such as photos, household and other acquainted matters from the past, music and collection of tapes. In this manuscript, the competence of reminiscence therapy for Alzheimer’s disease is measured using logistic regression based linear bootstrap aggregating. Logistic regression is used to envisage the experiential features of the patient’s memory through various therapies. Linear bootstrap aggregating shows better stability and accuracy of reminiscence therapy used in statistical classification and regression of memories related to validation therapy, supportive psychotherapy, sensory integration and simulated presence therapy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alzheimer%E2%80%99s%20disease" title="Alzheimer’s disease">Alzheimer’s disease</a>, <a href="https://publications.waset.org/abstracts/search?q=linear%20bootstrap%20aggregating" title=" linear bootstrap aggregating"> linear bootstrap aggregating</a>, <a href="https://publications.waset.org/abstracts/search?q=logistic%20regression" title=" logistic regression"> logistic regression</a>, <a href="https://publications.waset.org/abstracts/search?q=reminiscence%20therapy" title=" reminiscence therapy"> reminiscence therapy</a> </p> <a href="https://publications.waset.org/abstracts/79402/reminiscence-therapy-for-alzheimers-disease-restrained-on-logistic-regression-based-linear-bootstrap-aggregating" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/79402.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">309</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3811</span> Trigonelline: A Promising Compound for The Treatment of Alzheimer's Disease</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mai%20M.%20Farid">Mai M. Farid</a>, <a href="https://publications.waset.org/abstracts/search?q=Ximeng%20Yang"> Ximeng Yang</a>, <a href="https://publications.waset.org/abstracts/search?q=Tomoharu%20Kuboyama"> Tomoharu Kuboyama</a>, <a href="https://publications.waset.org/abstracts/search?q=Chihiro%20Tohda"> Chihiro Tohda</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Trigonelline is a major alkaloid component derived from Trigonella foenum-graecum L. (fenugreek) and has been reported before as a potential neuroprotective agent, especially in Alzheimer’s disease (AD). However, the previous data were unclear and used model mice were not well established. In the present study, the effect of trigonelline on memory function was investigated in Alzheimer’s disease transgenic model mouse, 5XFAD which overexpresses the mutated APP and PS1 genes. Oral administration of trigonelline for 14 days significantly enhanced object recognition and object location memories. Plasma and cerebral cortex were isolated at 30 min, 1h, 3h, and 6 h after oral administration of trigonelline. LC-MS/MS analysis indicated that trigonelline was detected in both plasma and cortex from 30 min after, suggesting good penetration of trigonelline into the brain. In addition, trigonelline significantly ameliorated axonal and dendrite atrophy in Amyloid β-treated cortical neurons. These results suggest that trigonelline could be a promising therapeutic candidate for AD. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=alzheimer%E2%80%99s%20disease" title="alzheimer’s disease">alzheimer’s disease</a>, <a href="https://publications.waset.org/abstracts/search?q=cortical%20neurons" title=" cortical neurons"> cortical neurons</a>, <a href="https://publications.waset.org/abstracts/search?q=LC-MS%2FMS%20analysis" title=" LC-MS/MS analysis"> LC-MS/MS analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=trigonelline" title=" trigonelline"> trigonelline</a> </p> <a href="https://publications.waset.org/abstracts/116264/trigonelline-a-promising-compound-for-the-treatment-of-alzheimers-disease" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/116264.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">147</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3810</span> Development of a Delivery System for Statin Targeted Spray is a Breakthrough Therapy in Alzheimer’s Prevention</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fakhr%20Eddin%20Alnaal">Fakhr Eddin Alnaal</a>, <a href="https://publications.waset.org/abstracts/search?q=Angela%20Dahdal"> Angela Dahdal</a>, <a href="https://publications.waset.org/abstracts/search?q=Duaa%20Aladib"> Duaa Aladib</a>, <a href="https://publications.waset.org/abstracts/search?q=Sabeen%20Ibrahim"> Sabeen Ibrahim</a>, <a href="https://publications.waset.org/abstracts/search?q=Ibrahim%20Ghoraibi"> Ibrahim Ghoraibi</a>, <a href="https://publications.waset.org/abstracts/search?q=Bissan%20Ahmed"> Bissan Ahmed</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Dementia is one of the diseases which had several stages and Alzheimer’s term was selected in respect for the first doctor Alzheimer who defined the first symptoms of this diseases in a woman whom was well treated by him. The fact that this is a type of a silent disease on which you have a long-term process of neurological degradation and suddenly gives symptoms which are most often irreversible, on clinical level likely we can consider it as a malignancy, one in terms of that it is sudden shocking irreversible and on the level of behavior and some mortality beside the lack of early detection tools for diagnosis. Therefore, the goal of our project is to test the concept of the ability of Statin in prevention of such disease and we investigated that both on experimental level and most importantly on clinical one, the clinical part was performed in a recognized house of aged people who had accidently a high cholesterol and were for years given Statin to treat that elevation, however after the symptoms of Alzheimer’s appeared and when diagnosed, they were well treated and rapidly recovered compared to Alzheimer’s patients in the same house who did not receive Statin had a mild improvement in their symptoms after the therapy, on the other hand we confirmed such observation by a well-organized experimental work. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alzheimer%27s" title="Alzheimer's">Alzheimer's</a>, <a href="https://publications.waset.org/abstracts/search?q=dementia" title=" dementia"> dementia</a>, <a href="https://publications.waset.org/abstracts/search?q=silent%20disease" title=" silent disease"> silent disease</a>, <a href="https://publications.waset.org/abstracts/search?q=statin" title=" statin"> statin</a> </p> <a href="https://publications.waset.org/abstracts/156124/development-of-a-delivery-system-for-statin-targeted-spray-is-a-breakthrough-therapy-in-alzheimers-prevention" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/156124.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">133</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3809</span> Predicting the Diagnosis of Alzheimer’s Disease: Development and Validation of Machine Learning Models</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jay%20L.%20Fu">Jay L. Fu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Patients with Alzheimer's disease progressively lose their memory and thinking skills and, eventually, the ability to carry out simple daily tasks. The disease is irreversible, but early detection and treatment can slow down the disease progression. In this research, publicly available MRI data and demographic data from 373 MRI imaging sessions were utilized to build models to predict dementia. Various machine learning models, including logistic regression, k-nearest neighbor, support vector machine, random forest, and neural network, were developed. Data were divided into training and testing sets, where training sets were used to build the predictive model, and testing sets were used to assess the accuracy of prediction. Key risk factors were identified, and various models were compared to come forward with the best prediction model. Among these models, the random forest model appeared to be the best model with an accuracy of 90.34%. MMSE, nWBV, and gender were the three most important contributing factors to the detection of Alzheimer’s. Among all the models used, the percent in which at least 4 of the 5 models shared the same diagnosis for a testing input was 90.42%. These machine learning models allow early detection of Alzheimer’s with good accuracy, which ultimately leads to early treatment of these patients. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alzheimer%27s%20disease" title="Alzheimer's disease">Alzheimer's disease</a>, <a href="https://publications.waset.org/abstracts/search?q=clinical%20diagnosis" title=" clinical diagnosis"> clinical diagnosis</a>, <a href="https://publications.waset.org/abstracts/search?q=magnetic%20resonance%20imaging" title=" magnetic resonance imaging"> magnetic resonance imaging</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning%20prediction" title=" machine learning prediction"> machine learning prediction</a> </p> <a href="https://publications.waset.org/abstracts/131623/predicting-the-diagnosis-of-alzheimers-disease-development-and-validation-of-machine-learning-models" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/131623.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">143</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3808</span> Brain Atrophy in Alzheimer's Patients</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tansa%20Nisan%20Gunerhan">Tansa Nisan Gunerhan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Dementia comes in different forms, including Alzheimer's disease. The most common dementia diagnosis among elderly individuals is Alzheimer's disease. On average, for patients with Alzheimer’s, life expectancy is around 4-8 years after the diagnosis; however, expectancy can go as high as twenty years or more, depending on the shrinkage of the brain. Normally, along with aging, the brain shrinks at some level but doesn’t lose a vast amount of neurons. However, Alzheimer's patients' neurons are destroyed rapidly; hence problems with loss of memory, communication, and other metabolic activities begin. The toxic changes in the brain affect the stability of the neurons. Beta-amyloid and tau are two proteins that are believed to play a role in the development of Alzheimer's disease through their toxic changes. Beta-amyloid is a protein that is produced in the brain and is normally broken down and removed from the body. However, in people with Alzheimer's disease, the production of beta-amyloid increases, and it begins to accumulate in the brain. These plaques are thought to disrupt communication between nerve cells and may contribute to the death of brain cells. Tau is a protein that helps to stabilize microtubules, which are essential for the transportation of nutrients and other substances within brain cells. In people with Alzheimer's disease, tau becomes abnormal and begins to accumulate inside brain cells, forming neurofibrillary tangles. These tangles disrupt the normal functioning of brain cells and may contribute to their death, forming amyloid plaques which are deposits of a protein called amyloid-beta that build up between nerve cells in the brain. The accumulation of amyloid plaques and neurofibrillary tangles in the brain is thought to contribute to the shrinkage of brain tissue. As the brain shrinks, the size of the brain may decrease, leading to a reduction in brain volume. Brain atrophy in Alzheimer's disease is often accompanied by changes in the structure and function of brain cells and the connections between them, leading to a decline in brain function. These toxic changes that accumulate can cause symptoms such as memory loss, difficulty with thinking and problem-solving, and changes in behavior and personality. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alzheimer" title="Alzheimer">Alzheimer</a>, <a href="https://publications.waset.org/abstracts/search?q=amyloid-beta" title=" amyloid-beta"> amyloid-beta</a>, <a href="https://publications.waset.org/abstracts/search?q=brain%20atrophy" title=" brain atrophy"> brain atrophy</a>, <a href="https://publications.waset.org/abstracts/search?q=neuron" title=" neuron"> neuron</a>, <a href="https://publications.waset.org/abstracts/search?q=shrinkage" title=" shrinkage"> shrinkage</a> </p> <a href="https://publications.waset.org/abstracts/161073/brain-atrophy-in-alzheimers-patients" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/161073.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">95</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3807</span> Family Satisfaction with Neuro-Linguistic Care for Patients with Alzheimer’s Disease</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sara%20Sahraoui">Sara Sahraoui</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This research studied the effect of Alzheimer's disease (AD) on language information processing in subjects with Alzheimer’s disease (AD) who were bilingual (French and dialectical Arabic). The results show a disorder of certain semantic aspects of their mother tongue (L1). On the other hand, grammatical levels appeared to be relatively unaffected in oral speech in L1 but were disturbed in the second language (L2). In consequence, we constructed a cognitive-language stimulation protocol for bilingual patients (PSCLAB) to respond to this disorder. The efficacy of this protocol in terms of rehabilitation was assessed in 30 such patients through discourse analysis carried out before and after initiating the protocol. The results show that cognitive/language training using the PSCLAB appears to improve the language behaviour of bilingual patients with AD. However, this survey study aims to verify the satisfaction of patients’ relatives with the results of cognitive language training by PSCLAB. We developed a brief instrument to measure the satisfaction of family members. The results report that the patient's relatives are satisfied with the results of cognitive training by PSCLAB. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=satisfaction" title="satisfaction">satisfaction</a>, <a href="https://publications.waset.org/abstracts/search?q=Alzheimer%27s%20disease" title=" Alzheimer's disease"> Alzheimer's disease</a>, <a href="https://publications.waset.org/abstracts/search?q=rehabilitation" title=" rehabilitation"> rehabilitation</a>, <a href="https://publications.waset.org/abstracts/search?q=levels%20language" title=" levels language"> levels language</a> </p> <a href="https://publications.waset.org/abstracts/176377/family-satisfaction-with-neuro-linguistic-care-for-patients-with-alzheimers-disease" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/176377.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">79</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3806</span> An Overview of Structure Based Activity Outcomes of Pyran Derivatives Against Alzheimer’s Disease</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Faisal%20Almalki">Faisal Almalki</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Pyran is a heterocyclic group containing oxygen that possesses a variety of pharmacological effects. Pyran is also one of the most prevalent structural subunits in natural products, such as xanthones, coumarins, flavonoids, benzopyrans, etc. Additionally demonstrating the neuroprotective properties of pyrans is the fact that this heterocycle has recently attracted the attention of scientists worldwide. Alzheimer's Disease (AD) treatment and diagnosis are two of the most critical research objectives worldwide. Increased amounts of extracellular senile plaques, intracellular neurofibrillary tangles, and a progressive shutdown of cholinergic basal forebrain neuron transmission are often related with cognitive impairment. This review highlights the various pyran scaffolds of natural and synthetic origin that are effective in the treatment of AD. For better understanding synthetic compounds are categorized as different types of pyran derivatives like chromene, flavone, xanthone, xanthene, etc. The discussion encompasses both the structure-activity correlations of these compounds as well as their activity against AD. Because of the intriguing actions that were uncovered by these pyran-based scaffolds, there is no question that they are at the forefront of the search for potential medication candidates that could treat Alzheimer's disease. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=alzheimer%E2%80%99s%20disease" title="alzheimer’s disease">alzheimer’s disease</a>, <a href="https://publications.waset.org/abstracts/search?q=pyran" title=" pyran"> pyran</a>, <a href="https://publications.waset.org/abstracts/search?q=coumarin" title=" coumarin"> coumarin</a>, <a href="https://publications.waset.org/abstracts/search?q=xanthone" title=" xanthone"> xanthone</a> </p> <a href="https://publications.waset.org/abstracts/174335/an-overview-of-structure-based-activity-outcomes-of-pyran-derivatives-against-alzheimers-disease" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/174335.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">74</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3805</span> Using Speech Emotion Recognition as a Longitudinal Biomarker for Alzheimer’s Diseases</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yishu%20Gong">Yishu Gong</a>, <a href="https://publications.waset.org/abstracts/search?q=Liangliang%20Yang"> Liangliang Yang</a>, <a href="https://publications.waset.org/abstracts/search?q=Jianyu%20Zhang"> Jianyu Zhang</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhengyu%20Chen"> Zhengyu Chen</a>, <a href="https://publications.waset.org/abstracts/search?q=Sihong%20He"> Sihong He</a>, <a href="https://publications.waset.org/abstracts/search?q=Xusheng%20Zhang"> Xusheng Zhang</a>, <a href="https://publications.waset.org/abstracts/search?q=Wei%20Zhang"> Wei Zhang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that affects millions of people worldwide and is characterized by cognitive decline and behavioral changes. People living with Alzheimer’s disease often find it hard to complete routine tasks. However, there are limited objective assessments that aim to quantify the difficulty of certain tasks for AD patients compared to non-AD people. In this study, we propose to use speech emotion recognition (SER), especially the frustration level, as a potential biomarker for quantifying the difficulty patients experience when describing a picture. We build an SER model using data from the IEMOCAP dataset and apply the model to the DementiaBank data to detect the AD/non-AD group difference and perform longitudinal analysis to track the AD disease progression. Our results show that the frustration level detected from the SER model can possibly be used as a cost-effective tool for objective tracking of AD progression in addition to the Mini-Mental State Examination (MMSE) score. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alzheimer%E2%80%99s%20disease" title="Alzheimer’s disease">Alzheimer’s disease</a>, <a href="https://publications.waset.org/abstracts/search?q=speech%20emotion%20recognition" title=" speech emotion recognition"> speech emotion recognition</a>, <a href="https://publications.waset.org/abstracts/search?q=longitudinal%20biomarker" title=" longitudinal biomarker"> longitudinal biomarker</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a> </p> <a href="https://publications.waset.org/abstracts/161096/using-speech-emotion-recognition-as-a-longitudinal-biomarker-for-alzheimers-diseases" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/161096.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">113</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3804</span> DNAJB6 Chaperone Prevents the Aggregation of Intracellular but not Extracellular Aβ Peptides Associated with Alzheimer’s Disease</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rasha%20M.%20Hussein">Rasha M. Hussein</a>, <a href="https://publications.waset.org/abstracts/search?q=Reem%20M.%20Hashem"> Reem M. Hashem</a>, <a href="https://publications.waset.org/abstracts/search?q=Laila%20A.%20Rashed"> Laila A. Rashed</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Alzheimer’s disease is the most common dementia disease in the elderly. It is characterized by the accumulation of extracellular amyloid β (Aβ) peptides and intracellular hyper-phosphorylated tau protein. In addition, recent evidence indicates that accumulation of intracellular amyloid β peptides may play a role in Alzheimer’s disease pathogenesis. This suggests that intracellular Heat Shock Proteins (HSP) that maintain the protein quality control in the cell might be potential candidates for disease amelioration. DNAJB6, a member of DNAJ family of HSP, effectively prevented the aggregation of poly glutamines stretches associated with Huntington’s disease both in vitro and in cells. In addition, DNAJB6 was found recently to delay the aggregation of Aβ42 peptides in vitro. In the present study, we investigated the ability of DNAJB6 to prevent the aggregation of both intracellular and extracellular Aβ peptides using transfection of HEK293 cells with Aβ-GFP and recombinant Aβ42 peptides respectively. We performed western blotting and immunofluorescence techniques. We found that DNAJB6 can prevent Aβ-GFP aggregation, but not the seeded aggregation initiated by extracellular Aβ peptides. Moreover, DNAJB6 required interaction with HSP70 to prevent the aggregation of Aβ-GFP protein and its J-domain was essential for this anti-aggregation activity. Interestingly, overexpression of other DNAJ proteins as well as HSPB1 suppressed Aβ-GFP aggregation efficiently. Our findings suggest that DNAJB6 is a promising candidate for the inhibition of Aβ-GFP mediated aggregation through a canonical HSP70 dependent mechanism. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=A%CE%B2" title="Aβ">Aβ</a>, <a href="https://publications.waset.org/abstracts/search?q=Alzheimer%E2%80%99s%20disease" title=" Alzheimer’s disease"> Alzheimer’s disease</a>, <a href="https://publications.waset.org/abstracts/search?q=chaperone" title=" chaperone"> chaperone</a>, <a href="https://publications.waset.org/abstracts/search?q=DNAJB6" title=" DNAJB6"> DNAJB6</a>, <a href="https://publications.waset.org/abstracts/search?q=aggregation" title=" aggregation"> aggregation</a> </p> <a href="https://publications.waset.org/abstracts/35650/dnajb6-chaperone-prevents-the-aggregation-of-intracellular-but-not-extracellular-av-peptides-associated-with-alzheimers-disease" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/35650.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">512</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3803</span> Trigonella foenum-graecum Seeds Extract as Therapeutic Candidate for Treatment of Alzheimer's Disease</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mai%20M.%20Farid">Mai M. Farid</a>, <a href="https://publications.waset.org/abstracts/search?q=Ximeng%20Yang"> Ximeng Yang</a>, <a href="https://publications.waset.org/abstracts/search?q=Tomoharu%20Kuboyama"> Tomoharu Kuboyama</a>, <a href="https://publications.waset.org/abstracts/search?q=Yuna%20Inada"> Yuna Inada</a>, <a href="https://publications.waset.org/abstracts/search?q=Chihiro%20Tohda"> Chihiro Tohda</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Intro: Trigonella foenum-graecum (Fenugreek), from Fabaceae family is a well-known plant traditionally used as food and medicine. Many pharmacological effects of Trigonella foenum- graecum seeds extract (TF extract) were evaluated such as anti-diabetic, anti-tumor and anti-dementia effects using in vivo models. Regarding the anti-dementia effects of TF extract, diabetic rats, aluminum chloride-induced amnesia rats and scopolamine-injected mice were used previously for evaluation, which are not well established as Alzheimer’s disease models. In addition, those previous studies, active constituents in TF extract for memory function were not identified. Method: This study aimed to clarify the effect of TF extract on Alzheimer’s disease model, 5XFAD mouse that overexpresses mutated APP and PS1 genes and determine the major active constituent in the brain after oral intake of TF extract. Results: Trigonelline was detected in the cerebral cortex of 5XFAD mice after 24 hours of oral administration of TF extract by LC-MS/MS. Oral administration of TF extract for 17 days improved object location memory in 5XFAD mice. Conclusion: These results suggest that TF extract and its active constituents could be an expected therapeutic candidate for Alzheimer’s disease. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alzheimer%27s%20disease" title="Alzheimer's disease">Alzheimer's disease</a>, <a href="https://publications.waset.org/abstracts/search?q=LC-MS%2FMS" title=" LC-MS/MS"> LC-MS/MS</a>, <a href="https://publications.waset.org/abstracts/search?q=memory%20recovery" title=" memory recovery"> memory recovery</a>, <a href="https://publications.waset.org/abstracts/search?q=Trigonella%20foenum-graecum%20Seeds" title=" Trigonella foenum-graecum Seeds"> Trigonella foenum-graecum Seeds</a>, <a href="https://publications.waset.org/abstracts/search?q=5XFAD%20mice" title=" 5XFAD mice"> 5XFAD mice</a> </p> <a href="https://publications.waset.org/abstracts/131399/trigonella-foenum-graecum-seeds-extract-as-therapeutic-candidate-for-treatment-of-alzheimers-disease" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/131399.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">147</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3802</span> Combined Use of FMRI and Voxel-Based Morphometry in Assessment of Memory Impairment in Alzheimer's Disease Patients</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=A.%20V.%20Sokolov">A. V. Sokolov</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20V.%20Vorobyev"> S. V. Vorobyev</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Yu.%20Efimtcev"> A. Yu. Efimtcev</a>, <a href="https://publications.waset.org/abstracts/search?q=V.%20Yu.%20Lobzin"> V. Yu. Lobzin</a>, <a href="https://publications.waset.org/abstracts/search?q=I.%20A.%20Lupanov"> I. A. Lupanov</a>, <a href="https://publications.waset.org/abstracts/search?q=O.%20A.%20Cherdakov"> O. A. Cherdakov</a>, <a href="https://publications.waset.org/abstracts/search?q=V.%20A.%20Fokin"> V. A. Fokin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Alzheimer’s disease (AD) is the most common form of dementia. Different brain regions are involved to the pathological process of AD. The purpose of this study was to evaluate brain activation by visual memory task in patients with Alzheimer's disease and determine correlation between memory impairment and atrophy of memory specific brain regions of frontal and medial temporal lobes. To investigate the organization of memory and localize cortical areas activated by visual memory task we used functional magnetic resonance imaging and to evaluate brain atrophy of patients with Alzheimer's disease we used voxel-based morphometry. FMRI was performed on 1.5 T MR-scanner Siemens Magnetom Symphony with BOLD (Blood Oxygenation Level Dependent) technique, based on distinctions of magnetic properties of hemoglobin. For test stimuli we used series of 12 not related images for "Baseline" and 12 images with 6 presented before for "Active". Stimuli were presented 3 times with reduction of repeated images to 4 and 2. Patients with Alzheimer's disease showed less activation in hippocampal formation (HF) region and parahippocampal gyrus then healthy persons of control group (p<0.05). The study also showed reduced activation in posterior cingulate cortex (p<0.001). Voxel-based morphometry showed significant atrophy of grey matter in Alzheimer’s disease patients, especially of both temporal lobes (fusiform and parahippocampal gyri); frontal lobes (posterior cingulate and superior frontal gyri). The study showed correlation between memory impairment and atrophy of memory specific brain regions of frontal and medial temporal lobes. Thus, reduced activation in hippocampal formation and parahippocampal gyri, in posterior cingulate gyrus in patients with Alzheimer's disease correlates to significant atrophy of these regions, detected by voxel-based morphometry, and to deterioration of specific cognitive functions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alzheimer%E2%80%99s%20disease" title="Alzheimer’s disease">Alzheimer’s disease</a>, <a href="https://publications.waset.org/abstracts/search?q=functional%20MRI" title=" functional MRI"> functional MRI</a>, <a href="https://publications.waset.org/abstracts/search?q=voxel-based%20morphometry" title=" voxel-based morphometry"> voxel-based morphometry</a> </p> <a href="https://publications.waset.org/abstracts/18475/combined-use-of-fmri-and-voxel-based-morphometry-in-assessment-of-memory-impairment-in-alzheimers-disease-patients" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/18475.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">320</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3801</span> Diagnosis of Alzheimer Diseases in Early Step Using Support Vector Machine (SVM)</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Amira%20Ben%20Rabeh">Amira Ben Rabeh</a>, <a href="https://publications.waset.org/abstracts/search?q=Faouzi%20Benzarti"> Faouzi Benzarti</a>, <a href="https://publications.waset.org/abstracts/search?q=Hamid%20Amiri"> Hamid Amiri</a>, <a href="https://publications.waset.org/abstracts/search?q=Mouna%20Bouaziz"> Mouna Bouaziz</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Alzheimer is a disease that affects the brain. It causes degeneration of nerve cells (neurons) and in particular cells involved in memory and intellectual functions. Early diagnosis of Alzheimer Diseases (AD) raises ethical questions, since there is, at present, no cure to offer to patients and medicines from therapeutic trials appear to slow the progression of the disease as moderate, accompanying side effects sometimes severe. In this context, analysis of medical images became, for clinical applications, an essential tool because it provides effective assistance both at diagnosis therapeutic follow-up. Computer Assisted Diagnostic systems (CAD) is one of the possible solutions to efficiently manage these images. In our work; we proposed an application to detect Alzheimer’s diseases. For detecting the disease in early stage we used the three sections: frontal to extract the Hippocampus (H), Sagittal to analysis the Corpus Callosum (CC) and axial to work with the variation features of the Cortex(C). Our method of classification is based on Support Vector Machine (SVM). The proposed system yields a 90.66% accuracy in the early diagnosis of the AD. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alzheimer%20Diseases%20%28AD%29" title="Alzheimer Diseases (AD)">Alzheimer Diseases (AD)</a>, <a href="https://publications.waset.org/abstracts/search?q=Computer%20Assisted%20Diagnostic%28CAD%29" title=" Computer Assisted Diagnostic(CAD)"> Computer Assisted Diagnostic(CAD)</a>, <a href="https://publications.waset.org/abstracts/search?q=hippocampus" title=" hippocampus"> hippocampus</a>, <a href="https://publications.waset.org/abstracts/search?q=Corpus%20Callosum%20%28CC%29" title=" Corpus Callosum (CC)"> Corpus Callosum (CC)</a>, <a href="https://publications.waset.org/abstracts/search?q=cortex" title=" cortex"> cortex</a>, <a href="https://publications.waset.org/abstracts/search?q=Support%20Vector%20Machine%20%28SVM%29" title=" Support Vector Machine (SVM)"> Support Vector Machine (SVM)</a> </p> <a href="https://publications.waset.org/abstracts/43182/diagnosis-of-alzheimer-diseases-in-early-step-using-support-vector-machine-svm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/43182.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">384</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3800</span> Network Pharmacological Evaluation of Holy Basil Bioactive Phytochemicals for Identifying Novel Potential Inhibitors Against Neurodegenerative Disorder</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bhuvanesh%20Baniya">Bhuvanesh Baniya</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Alzheimer disease is illnesses that are responsible for neuronal cell death and resulting in lifelong cognitive problems. Due to their unclear mechanism, there are no effective drugs available for the treatment. For a long time, herbal drugs have been used as a role model in the field of the drug discovery process. Holy basil in the Indian medicinal system (Ayurveda) is used for several neuronal disorders like insomnia and memory loss for decades. This study aims to identify active components of holy basil as potential inhibitors for the treatment of Alzheimer disease. To fulfill this objective, the Network pharmacology approach, gene ontology, pharmacokinetics analysis, molecular docking, and molecular dynamics simulation (MDS) studies were performed. A total of 7 active components in holy basil, 12 predicted neurodegenerative targets of holy basil, and 8063 Alzheimer-related targets were identified from different databases. The network analysis showed that the top ten targets APP, EGFR, MAPK1, ESR1, HSPA4, PRKCD, MAPK3, ABL1, JUN, and GSK3B were found as significant target related to Alzheimer disease. On the basis of gene ontology and topology analysis results, APP was found as a significant target related to Alzheimer’s disease pathways. Further, the molecular docking results to found that various compounds showed the best binding affinities. Further, MDS top results suggested could be used as potential inhibitors against APP protein and could be useful for the treatment of Alzheimer’s disease. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=holy%20basil" title="holy basil">holy basil</a>, <a href="https://publications.waset.org/abstracts/search?q=network%20pharmacology" title=" network pharmacology"> network pharmacology</a>, <a href="https://publications.waset.org/abstracts/search?q=neurodegeneration" title=" neurodegeneration"> neurodegeneration</a>, <a href="https://publications.waset.org/abstracts/search?q=active%20phytochemicals" title=" active phytochemicals"> active phytochemicals</a>, <a href="https://publications.waset.org/abstracts/search?q=molecular%20docking%20and%20simulation" title=" molecular docking and simulation"> molecular docking and simulation</a> </p> <a href="https://publications.waset.org/abstracts/162002/network-pharmacological-evaluation-of-holy-basil-bioactive-phytochemicals-for-identifying-novel-potential-inhibitors-against-neurodegenerative-disorder" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/162002.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">101</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3799</span> Nanoparticles in Drug Delivery and Therapy of Alzeheimer's Disease</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nirupama%20Dixit">Nirupama Dixit</a>, <a href="https://publications.waset.org/abstracts/search?q=Anyaa%20Mittal"> Anyaa Mittal</a>, <a href="https://publications.waset.org/abstracts/search?q=Neeru%20Sood"> Neeru Sood</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Alzheimer’s disease (AD) is a progressive form of dementia, contributing to up to 70% of cases, mostly observed in elderly but is not restricted to old age. The pathophysiology of the disease is characterized by specific pathological changes in brain. The changes (i.e. accumulation of metal ions in brain, formation of extracellular β-amyloid (Aβ) peptide aggregates and tangle of hyper phosphorylated Tau protein inside neurons) damage the neuronal connections irreversibly. The current issues in improvement of life quality of Alzheimer's patient lies in the fact that the diagnosis is made at a late stage of the disease and the medications do not treat the basic causes of Alzheimer's. The targeted delivery of drug through the blood brain barrier (BBB) poses several limitations via traditional approaches for treatment. To overcome these drug delivery limitation, nanoparticles provide a promising solution. This review focuses on current strategies for efficient targeted drug delivery using nanoparticles and improving the quality of therapy provided to the patient. Nanoparticles can be used to encapsulate drug (which is generally hydrophobic) to ensure its passage to brain; they can be conjugated to metal ion chelators to reduce the metal load in neural tissue thus lowering the harmful effects of oxidative damage; can be conjugated with drug and monoclonal antibodies against BBB endogenous receptors. Finally this review covers how the nanoparticles can play a role in diagnosing the disease. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alzheimer%27s%20disease" title="Alzheimer's disease">Alzheimer's disease</a>, <a href="https://publications.waset.org/abstracts/search?q=%CE%B2-amyloid%20plaques" title=" β-amyloid plaques"> β-amyloid plaques</a>, <a href="https://publications.waset.org/abstracts/search?q=blood%20brain%20barrier" title=" blood brain barrier"> blood brain barrier</a>, <a href="https://publications.waset.org/abstracts/search?q=metal%20chelators" title=" metal chelators"> metal chelators</a>, <a href="https://publications.waset.org/abstracts/search?q=nanoparticles" title=" nanoparticles"> nanoparticles</a> </p> <a href="https://publications.waset.org/abstracts/27642/nanoparticles-in-drug-delivery-and-therapy-of-alzeheimers-disease" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/27642.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">490</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3798</span> Early Diagnosis of Alzheimer's Disease Using a Combination of Images Processing and Brain Signals</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=E.%20Irankhah">E. Irankhah</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Zarif"> M. Zarif</a>, <a href="https://publications.waset.org/abstracts/search?q=E.%20Mazrooei%20Rad"> E. Mazrooei Rad</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20Ghandehari"> K. Ghandehari </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Alzheimer's prevalence is on the rise, and the disease comes with problems like cessation of treatment, high cost of treatment, and the lack of early detection methods. The pathology of this disease causes the formation of protein deposits in the brain of patients called plaque amyloid. Generally, the diagnosis of this disease is done by performing tests such as a cerebrospinal fluid, CT scan, MRI, and spinal cord fluid testing, or mental testing tests and eye tracing tests. In this paper, we tried to use the Medial Temporal Atrophy (MTA) method and the Leave One Out (LOO) cycle to extract the statistical properties of the three Fz, Pz, and Cz channels of ERP signals for early diagnosis of this disease. In the process of CT scan images, the accuracy of the results is 81% for the healthy person and 88% for the severe patient. After the process of ERP signaling, the accuracy of the results for a healthy person in the delta band in the Cz channel is 81% and in the alpha band the Pz channel is 90%. In the results obtained from the signal processing, the results of the severe patient in the delta band of the Cz channel were 89% and in the alpha band Pz channel 92%. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alzheimer%27s%20disease" title="Alzheimer's disease">Alzheimer's disease</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20and%20signal%20processing" title=" image and signal processing"> image and signal processing</a>, <a href="https://publications.waset.org/abstracts/search?q=LOO%20cycle" title=" LOO cycle"> LOO cycle</a>, <a href="https://publications.waset.org/abstracts/search?q=medial%20temporal%20atrophy" title=" medial temporal atrophy"> medial temporal atrophy</a> </p> <a href="https://publications.waset.org/abstracts/77577/early-diagnosis-of-alzheimers-disease-using-a-combination-of-images-processing-and-brain-signals" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/77577.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">198</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3797</span> Expression of ACSS2 Genes in Peripheral Blood Mononuclear Cells of Patients with Alzheimer’s Disease </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ali%20Bayram">Ali Bayram</a>, <a href="https://publications.waset.org/abstracts/search?q=Burak%20Uz"> Burak Uz</a>, <a href="https://publications.waset.org/abstracts/search?q=Remzi%20Yi%C4%9Fiter"> Remzi Yiğiter</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The impairment of lipid metabolism in the central nervous system has been suggested as a critical factor of Alzheimer’s disease (AD) pathogenesis. Homo sapiens acyl-coenyme A synthetase short-chain family member 2 (ACSS2) gene encodes the enzyme acetyl-Coenzyme A synthetase (AMP forming; AceCS) providing acetyl-coenzyme A (Ac-CoA) for various physiological processes, such as cholesterol and fatty acid synthesis, as well as the citric acid cycle. We investigated ACSS2, transcript variant 1 (ACSS2*1), mRNA levels in the peripheral blood mononuclear cells (PBMC) of patients with AD and compared them with the controls. The study group comprised 50 patients with the diagnosis of AD who have applied to Gaziantep University Faculty of Medicine, and Department of Neurology. 49 healthy individuals without any neurodegenerative disease are included as controls. ACSS2 mRNA expression in PBMC of AD/control patients was 0.495 (95% confidence interval: 0.410-0.598), p= .000000001902). Further studies are needed to better clarify this association. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alzheimer%E2%80%99s%20disease" title="Alzheimer’s disease">Alzheimer’s disease</a>, <a href="https://publications.waset.org/abstracts/search?q=ACSS2%20Genes" title=" ACSS2 Genes"> ACSS2 Genes</a>, <a href="https://publications.waset.org/abstracts/search?q=mRNA%20expression" title=" mRNA expression"> mRNA expression</a>, <a href="https://publications.waset.org/abstracts/search?q=RT-PCR" title=" RT-PCR"> RT-PCR</a> </p> <a href="https://publications.waset.org/abstracts/30063/expression-of-acss2-genes-in-peripheral-blood-mononuclear-cells-of-patients-with-alzheimers-disease" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/30063.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">392</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3796</span> Calculating Ventricle’s Area Based on Clinical Dementia Rating Values on Coronal MRI Image</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Retno%20Supriyanti">Retno Supriyanti</a>, <a href="https://publications.waset.org/abstracts/search?q=Ays%20Rahmadian%20Subhi"> Ays Rahmadian Subhi</a>, <a href="https://publications.waset.org/abstracts/search?q=Yogi%20Ramadhani"> Yogi Ramadhani</a>, <a href="https://publications.waset.org/abstracts/search?q=Haris%20B.%20Widodo"> Haris B. Widodo</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Alzheimer is one type of disease in the elderly that may occur in the world. The severity of the Alzheimer can be measured using a scale called Clinical Dementia Rating (CDR) based on a doctor's diagnosis of the patient's condition. Currently, diagnosis of Alzheimer often uses MRI machine, to know the condition of part of the brain called Hippocampus and Ventricle. MRI image itself consists of 3 slices, namely Coronal, Sagittal and Axial. In this paper, we discussed the measurement of the area of the ventricle especially in the Coronal slice based on the severity level referring to the CDR value. We use Active Contour method to segment the ventricle’s region, therefore that ventricle’s area can be calculated automatically. The results show that this method can be used for further development in the automatic diagnosis of Alzheimer. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alzheimer" title="Alzheimer">Alzheimer</a>, <a href="https://publications.waset.org/abstracts/search?q=CDR" title=" CDR"> CDR</a>, <a href="https://publications.waset.org/abstracts/search?q=coronal" title=" coronal"> coronal</a>, <a href="https://publications.waset.org/abstracts/search?q=ventricle" title=" ventricle"> ventricle</a>, <a href="https://publications.waset.org/abstracts/search?q=active%20contour" title=" active contour"> active contour</a> </p> <a href="https://publications.waset.org/abstracts/91350/calculating-ventricles-area-based-on-clinical-dementia-rating-values-on-coronal-mri-image" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/91350.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">266</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3795</span> Identification of Blood Biomarkers Unveiling Early Alzheimer's Disease Diagnosis Through Single-Cell RNA Sequencing Data and Autoencoders</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hediyeh%20Talebi">Hediyeh Talebi</a>, <a href="https://publications.waset.org/abstracts/search?q=Shokoofeh%20Ghiam"> Shokoofeh Ghiam</a>, <a href="https://publications.waset.org/abstracts/search?q=Changiz%20Eslahchi"> Changiz Eslahchi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Traditionally, Alzheimer’s disease research has focused on genes with significant fold changes, potentially neglecting subtle but biologically important alterations. Our study introduces an integrative approach that highlights genes crucial to underlying biological processes, regardless of their fold change magnitude. Alzheimer's Single-cell RNA-seq data related to the peripheral blood mononuclear cells (PBMC) was extracted from the Gene Expression Omnibus (GEO). After quality control, normalization, scaling, batch effect correction, and clustering, differentially expressed genes (DEGs) were identified with adjusted p-values less than 0.05. These DEGs were categorized based on cell-type, resulting in four datasets, each corresponding to a distinct cell type. To distinguish between cells from healthy individuals and those with Alzheimer's, an adversarial autoencoder with a classifier was employed. This allowed for the separation of healthy and diseased samples. To identify the most influential genes in this classification, the weight matrices in the network, which includes the encoder and classifier components, were multiplied, and focused on the top 20 genes. The analysis revealed that while some of these genes exhibit a high fold change, others do not. These genes, which may be overlooked by previous methods due to their low fold change, were shown to be significant in our study. The findings highlight the critical role of genes with subtle alterations in diagnosing Alzheimer's disease, a facet frequently overlooked by conventional methods. These genes demonstrate remarkable discriminatory power, underscoring the need to integrate biological relevance with statistical measures in gene prioritization. This integrative approach enhances our understanding of the molecular mechanisms in Alzheimer’s disease and provides a promising direction for identifying potential therapeutic targets. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=alzheimer%27s%20disease" title="alzheimer's disease">alzheimer's disease</a>, <a href="https://publications.waset.org/abstracts/search?q=single-cell%20RNA-seq" title=" single-cell RNA-seq"> single-cell RNA-seq</a>, <a href="https://publications.waset.org/abstracts/search?q=neural%20networks" title=" neural networks"> neural networks</a>, <a href="https://publications.waset.org/abstracts/search?q=blood%20biomarkers" title=" blood biomarkers"> blood biomarkers</a> </p> <a href="https://publications.waset.org/abstracts/179335/identification-of-blood-biomarkers-unveiling-early-alzheimers-disease-diagnosis-through-single-cell-rna-sequencing-data-and-autoencoders" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/179335.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">66</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3794</span> Neuroprotective Effects of Dehydroepiandrosterone (DHEA) in Rat Model of Alzheimer’s Disease</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hanan%20F.%20Aly">Hanan F. Aly</a>, <a href="https://publications.waset.org/abstracts/search?q=Fateheya%20M.%20Metwally"> Fateheya M. Metwally</a>, <a href="https://publications.waset.org/abstracts/search?q=Hanaa%20H.%20Ahmed"> Hanaa H. Ahmed</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The current study is undertaken to elucidate a possible neuroprotective role of dehydroepiandrosterone (DHEA) against the development of Alzheimer’s disease in experimental rat model. Alzheimer’s disease was produced in young female ovariectomized rats by intraperitoneal administration of AlCl3 (4.2 mg/kg body weight) daily for 12 weeks. Half of these animals also received orally DHEA (250 mg/kg body weight, three times weekly) for 18 weeks. Control groups of animals received either DHAE alone, or no DHEA, or were not ovariectomized. After such treatment the animals were analyzed for oxidative stress biomarkers such as hydrogen peroxide, nitric oxide and malondialdehyde, total antioxidant capacity, reduced glutathione, glutathione peroxidase, glutathione reductase, superoxide dismutase and catalase activities, antiapoptotic marker Bcl-2 and brain derived neurotrophic factor. Also, brain cholinergic markers (acetylcholinesterase and acetylcholine) were determined. The results revealed significant increase in oxidative stress parameters associated with significant decrease in the antioxidant enzyme activities in Al-intoxicated ovariectomized rats. Significant depletion in brain Bcl-2 and brain-derived neurotrophic factor levels were also detected. Moreover, significant elevations in brain acetylcholinesterase activity accompanied with significant reduction in acetylcholine level were recorded. Significant amelioration in all investigated parameters was detected as a result of treatment of Al-intoxicated ovariectomized rats with DHEA. These results were confirmed by histological examination of brain sections. These results clearly indicate a neuroprotective effect of DHEA against Alzheimer’s disease. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alzheimer%E2%80%99s%20disease" title="Alzheimer’s disease">Alzheimer’s disease</a>, <a href="https://publications.waset.org/abstracts/search?q=oxidative%20stress" title=" oxidative stress"> oxidative stress</a>, <a href="https://publications.waset.org/abstracts/search?q=apoptosis" title=" apoptosis"> apoptosis</a>, <a href="https://publications.waset.org/abstracts/search?q=dehydroepiandrosterone" title=" dehydroepiandrosterone"> dehydroepiandrosterone</a> </p> <a href="https://publications.waset.org/abstracts/10530/neuroprotective-effects-of-dehydroepiandrosterone-dhea-in-rat-model-of-alzheimers-disease" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/10530.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">323</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3793</span> The Effect of the COVID-19 on Alzheimer’s Disease</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ay%C5%9Fe%20Defne%20%C3%96z">Ayşe Defne Öz</a>, <a href="https://publications.waset.org/abstracts/search?q=%C3%96zlem%20Bozkurt"> Özlem Bozkurt</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Alzheimer's Disease (AD) is counted as one of the most important global health problems and the main cause of dementia. The term dementia refers to a wide spectrum of disorders characterized by global, chronic, and generally irreversible cognitive deterioration. It is estimated that %60 % to 80 of the cases of dementia are because of AD. Alzheimer's is a slowly progressive brain disease. The reason for AD is unknown to the author's best knowledge, yet it is one of the topics that is most researched. AD shows the histopathologically abnormal accumulation of the protein beta-amyloid (plague) outside neurons and twisted strands of the protein tau (tangles) inside neurons in the brain. These changes are accompanied by damage to the brain tissue and the death of neurons. AD causes people to have difficulty remembering names or conversations. Some of the later symptoms are difficulty in talking and walking. Alzheimer's Disease is elevated by the illness and mortality of COVID-19. COVID-19 has affected many lives globally and had profound effects on human lives. COVID-19 is caused by SARS-CoV-2, which is a virus that attacks the respiratory and central nervous system and has neuroinvasive potential. More than %80 of COVID-19 patients have ageusia or anosmia, representing the pathognomic features of the disease. Patients with dementia are frail, and with the COVID-19 pandemic, including isolation, cognitive decline may exacerbate. Furthermore, patients with AD can be unable to follow the directions, such as covering their mouth and nose while coughing and can live in nursing homes which makes them more open to being infected. As COVID-19 is highly infectious and its management requires isolation and quarantine, the need for caregivers for AD management conflicts with that of COVID-19 and adds an extra burden on AD patients, caregivers, families, society, and the economy. Due to the entry of SARS-CoV-2 into the central nervous system, inflammation caused by COVID-19, prolonged hospitalization, and delirium, it has been reported that COVID-19 causes many neurological disorders and predisposition to AD. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alzheimer%27s%20disease" title="Alzheimer's disease">Alzheimer's disease</a>, <a href="https://publications.waset.org/abstracts/search?q=COVID-19" title=" COVID-19"> COVID-19</a>, <a href="https://publications.waset.org/abstracts/search?q=dementia" title=" dementia"> dementia</a>, <a href="https://publications.waset.org/abstracts/search?q=SARS-CoV-2" title=" SARS-CoV-2"> SARS-CoV-2</a> </p> <a href="https://publications.waset.org/abstracts/161071/the-effect-of-the-covid-19-on-alzheimers-disease" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/161071.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">76</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3792</span> Transcranial Electric Field Treatments on Redox-Toxic Iron Deposits in Transgenic Alzheimer’s Disease Mouse Models: The Electroceutical Targeting of Alzheimer’s Disease</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Choi%20Younshick">Choi Younshick</a>, <a href="https://publications.waset.org/abstracts/search?q=Lee%20Wonseok"> Lee Wonseok</a>, <a href="https://publications.waset.org/abstracts/search?q=Lee%20Jaemeun"> Lee Jaemeun</a>, <a href="https://publications.waset.org/abstracts/search?q=Park%20Sun-Hyun"> Park Sun-Hyun</a>, <a href="https://publications.waset.org/abstracts/search?q=Kim%20Sunwoung"> Kim Sunwoung</a>, <a href="https://publications.waset.org/abstracts/search?q=Park%20Sua"> Park Sua</a>, <a href="https://publications.waset.org/abstracts/search?q=Kim%20Eun%20Ho"> Kim Eun Ho</a>, <a href="https://publications.waset.org/abstracts/search?q=Kim%20Jong-Ki"> Kim Jong-Ki</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Iron accumulation in the brain accelerates Alzheimer’s disease progression. To cure iron toxicity, we assessed the therapeutic effects of noncontact transcranial electric field stimulation to the brain on toxic iron deposits in either the Aβ-fibril structure or the Aβ plaque in a mouse model of Alzheimer’s disease (AD). A capacitive electrode-based alternating electric field (AEF) was applied to a suspension of magnetite (Fe₃O₄) to measure the field-sensitized electro-Fenton effect and resultant reactive oxygen species (ROS) generation. The increase in ROS generation compared to the untreated control was both exposure-time and AEF-frequency dependent. The frequency-specific exposure of AEF to 0.7–1.4 V/cm on a magnetite-bound Aβ-fibril or a transgenic Alzheimer’s disease (AD) mouse model revealed the removal of intraplaque ferrous magnetite iron deposit and Aβ-plaque burden together at the same time compared to the untreated control. The results of the behavioral tests show an improvement in impaired cognitive function following AEF treatment on the AD mouse model. Western blot assay found some disease-modifying biological responses, including down-regulating ferroptosis, neuroinflammation and reactive astrocytes that eventually made cognitive improvement feasible. Tissue clearing and 3D-imaging analysis revealed no induced damage to the neuronal structures of normal brain tissue following AEF treatment. In conclusion, our results suggest that the effective degradation of magnetite-bound amyloid fibrils or plaques in the AD brain by the electro-Fenton effect from electric field-sensitized magnetite offers a potential electroceutical treatment option for AD. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=electroceutical" title="electroceutical">electroceutical</a>, <a href="https://publications.waset.org/abstracts/search?q=intraplaque%20magnetite" title=" intraplaque magnetite"> intraplaque magnetite</a>, <a href="https://publications.waset.org/abstracts/search?q=alzheimer%E2%80%99s%20disease" title=" alzheimer’s disease"> alzheimer’s disease</a>, <a href="https://publications.waset.org/abstracts/search?q=transcranial%20electric%20field" title=" transcranial electric field"> transcranial electric field</a>, <a href="https://publications.waset.org/abstracts/search?q=electro-fenton%20effect" title=" electro-fenton effect"> electro-fenton effect</a> </p> <a href="https://publications.waset.org/abstracts/168507/transcranial-electric-field-treatments-on-redox-toxic-iron-deposits-in-transgenic-alzheimers-disease-mouse-models-the-electroceutical-targeting-of-alzheimers-disease" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/168507.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">71</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3791</span> The Role of Inflammasomes for aβ Microglia Phagocytosis in Alzheimer Disease</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Francesca%20La%20Rosa">Francesca La Rosa </a>, <a href="https://publications.waset.org/abstracts/search?q=Marina%20Saresella"> Marina Saresella</a>, <a href="https://publications.waset.org/abstracts/search?q=Mario%20Clerici"> Mario Clerici</a>, <a href="https://publications.waset.org/abstracts/search?q=Michael%20Heneka"> Michael Heneka </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Neuroinflammation plays a key role in the modulation of the pathogenesis of neurodegenerative disorder such as Alzheimer's Disease (AD). Microglia, the main immune effector of the brain, are able to migrate to sites of Amyloid-beta (Aβ) deposition to eliminate Aβ phagocytosis upon activation by multiple receptors: Toll like receptors and scavenger receptors. The issue of whether microglia are able to eliminate pathological lesions such as neurofibrillary tangles or senile plaques from AD brain still remains the matter of controversy. Recent data suggest that the Nod Like Receptor 3 (NLRP3), multiprotein inflammasome complexes, plays a role in AD, as its activation in the microglia by Aβ triggers. IL-1β is produced as a biologically inactive pro-form and requires caspase-1 for activation and secretion. Caspase-1 activity is controlled by inflammasomes. We investigate about the importance of inflammasomes complex in the Aβ phagocytosis and its degradation. The preliminary results of phagocytosis assay and immunofluorescent experiment on primary Microglia cells to lipopolysaccharide (LPS) an Aβ exposure show that a previous treatment with LPS reduce Aβ phagocytosis. Different results were obtained in Primary Microglia wild type, NLRP3 and ASC Knockout suggesting a real inflammasomes involvement in Alzheimer's pathology. Inflammasomes inactivation reduces the production of inflammatory cytokines prolonging the protective activity of microglia and Aβ clearance, featuring a typical microglia phenotype of the early stage of AD disease. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alzheimer%20disease" title="Alzheimer disease">Alzheimer disease</a>, <a href="https://publications.waset.org/abstracts/search?q=innate%20immunity" title=" innate immunity"> innate immunity</a>, <a href="https://publications.waset.org/abstracts/search?q=neuroinflammation" title=" neuroinflammation"> neuroinflammation</a>, <a href="https://publications.waset.org/abstracts/search?q=NLRP3" title=" NLRP3"> NLRP3</a> </p> <a href="https://publications.waset.org/abstracts/30475/the-role-of-inflammasomes-for-av-microglia-phagocytosis-in-alzheimer-disease" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/30475.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">456</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3790</span> Language Processing of Seniors with Alzheimer’s Disease: From the Perspective of Temporal Parameters</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Lai%20Yi-Hsiu">Lai Yi-Hsiu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The present paper aims to examine the language processing of Chinese-speaking seniors with Alzheimer’s disease (AD) from the perspective of temporal cues. Twenty healthy adults, 17 healthy seniors, and 13 seniors with AD in Taiwan participated in this study to tell stories based on two sets of pictures. Nine temporal cues were fetched and analyzed. Oral productions in Mandarin Chinese were compared and discussed to examine to what extent and in what way these three groups of participants performed with significant differences. Results indicated that the age effects were significant in filled pauses. The dementia effects were significant in mean duration of pauses, empty pauses, filled pauses, lexical pauses, normalized mean duration of filled pauses and lexical pauses. The findings reported in the current paper help characterize the nature of language processing in seniors with or without AD, and contribute to the interactions between the AD neural mechanism and their temporal parameters. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=language%20processing" title="language processing">language processing</a>, <a href="https://publications.waset.org/abstracts/search?q=Alzheimer%E2%80%99s%20disease" title=" Alzheimer’s disease"> Alzheimer’s disease</a>, <a href="https://publications.waset.org/abstracts/search?q=Mandarin%20Chinese" title=" Mandarin Chinese"> Mandarin Chinese</a>, <a href="https://publications.waset.org/abstracts/search?q=temporal%20cues" title=" temporal cues"> temporal cues</a> </p> <a href="https://publications.waset.org/abstracts/62548/language-processing-of-seniors-with-alzheimers-disease-from-the-perspective-of-temporal-parameters" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/62548.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">446</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3789</span> Expression of ULK-1 mRNA in Human Peripheral Blood Mononuclear Cells from Patients with Alzheimer's Disease</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ali%20Bayram">Ali Bayram</a>, <a href="https://publications.waset.org/abstracts/search?q=Remzi%20Yi%C4%9Fiter"> Remzi Yiğiter</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Objective: Alzheimer's disease (AD), the most common cause of dementia, is a progressive neurodegenerative disease. At present, diagnosis of AD is rather late in the disease. Therefore, we attempted to find peripheral biomarkers for the early diagnosis of AD. Herein, we conducted a study to investigate the unc-51 like autophagy activating kinase-1 (ULK1) mRNA expression levels in human peripheral blood mononuclear cells from patients with Alzheimer's disease. Method: To determine whether ULK1 gene expression are altered in AD patients, we measured their gene expression in human peripheral blood cell in 50 patients with AD and 50 age and gender matched healthy controls by quantitative real-time PCR technique. Results: We found that both ULK1 gene expression in peripheral blood cell were significantly decreased in patients with AD as compared with controls (p <0.05). Lower levels of ULK1 gene expression were significantly associated with the increased risk for AD. Conclusions: Serine/threonine-protein kinase involved in autophagy in response to starvation. Acts upstream of phosphatidylinositol 3-kinase PIK3C3 to regulate the formation of autophagophores, the precursors of autophagosomes. Part of regulatory feedback loops in autophagy: acts both as a downstream effector and negative regulator of mammalian target of rapamycin complex 1 (mTORC1) via interaction with RPTOR. Activated via phosphorylation by AMPK and also acts as a regulator of AMPK by mediating phosphorylation of AMPK subunits PRKAA1, PRKAB2, and PRKAG1, leading to negatively regulate AMPK activity. May phosphorylate ATG13/KIAA0652 and RPTOR; however such data need additional evidences. Plays a role early in neuronal differentiation and is required for granule cell axon formation. Alzheimer is the most common neurodegenerative disease. Our results provide useful information that the ULK1 gene expression is decreased in the neurodegeneration and AD patients with, indicating their possible systemic involvement in AD. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alzheimer%E2%80%99s%20sisease" title="Alzheimer’s sisease">Alzheimer’s sisease</a>, <a href="https://publications.waset.org/abstracts/search?q=ULK1" title=" ULK1"> ULK1</a>, <a href="https://publications.waset.org/abstracts/search?q=mRNA%20expression" title=" mRNA expression"> mRNA expression</a>, <a href="https://publications.waset.org/abstracts/search?q=RT-PCR" title=" RT-PCR"> RT-PCR</a> </p> <a href="https://publications.waset.org/abstracts/20247/expression-of-ulk-1-mrna-in-human-peripheral-blood-mononuclear-cells-from-patients-with-alzheimers-disease" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/20247.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">398</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3788</span> A Comparison of Convolutional Neural Network Architectures for the Classification of Alzheimer’s Disease Patients Using MRI Scans</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tomas%20Premoli">Tomas Premoli</a>, <a href="https://publications.waset.org/abstracts/search?q=Sareh%20Rowlands"> Sareh Rowlands</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this study, we investigate the impact of various convolutional neural network (CNN) architectures on the accuracy of diagnosing Alzheimer’s disease (AD) using patient MRI scans. Alzheimer’s disease is a debilitating neurodegenerative disorder that affects millions worldwide. Early, accurate, and non-invasive diagnostic methods are required for providing optimal care and symptom management. Deep learning techniques, particularly CNNs, have shown great promise in enhancing this diagnostic process. We aim to contribute to the ongoing research in this field by comparing the effectiveness of different CNN architectures and providing insights for future studies. Our methodology involved preprocessing MRI data, implementing multiple CNN architectures, and evaluating the performance of each model. We employed intensity normalization, linear registration, and skull stripping for our preprocessing. The selected architectures included VGG, ResNet, and DenseNet models, all implemented using the Keras library. We employed transfer learning and trained models from scratch to compare their effectiveness. Our findings demonstrated significant differences in performance among the tested architectures, with DenseNet201 achieving the highest accuracy of 86.4%. Transfer learning proved to be helpful in improving model performance. We also identified potential areas for future research, such as experimenting with other architectures, optimizing hyperparameters, and employing fine-tuning strategies. By providing a comprehensive analysis of the selected CNN architectures, we offer a solid foundation for future research in Alzheimer’s disease diagnosis using deep learning techniques. Our study highlights the potential of CNNs as a valuable diagnostic tool and emphasizes the importance of ongoing research to develop more accurate and effective models. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alzheimer%E2%80%99s%20disease" title="Alzheimer’s disease">Alzheimer’s disease</a>, <a href="https://publications.waset.org/abstracts/search?q=convolutional%20neural%20networks" title=" convolutional neural networks"> convolutional neural networks</a>, <a href="https://publications.waset.org/abstracts/search?q=deep%20learning" title=" deep learning"> deep learning</a>, <a href="https://publications.waset.org/abstracts/search?q=medical%20imaging" title=" medical imaging"> medical imaging</a>, <a href="https://publications.waset.org/abstracts/search?q=MRI" title=" MRI"> MRI</a> </p> <a href="https://publications.waset.org/abstracts/176580/a-comparison-of-convolutional-neural-network-architectures-for-the-classification-of-alzheimers-disease-patients-using-mri-scans" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/176580.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">73</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=Alzheimer%E2%80%99s%20disease&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=Alzheimer%E2%80%99s%20disease&page=3">3</a></li> <li class="page-item"><a class="page-link" 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