Relevant bibliographies by topics / Alzheimer's disease

Academic literature on the topic 'Alzheimer's disease'

Author: Grafiati
Published: 4 June 2021
Last updated: 31 July 2024

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Journal articles on the topic "Alzheimer's disease"

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Zarrouk, Amira, Meryam Debbabi, Maryem Bezine, El Mostafa Karym, Asmaa Badreddine, Olivier Rouaud, Thibault Moreau, et al. "Lipid Biomarkers in Alzheimer's Disease." Current Alzheimer Research 15, no. 4 (February 22, 2018): 303–12. http://dx.doi.org/10.2174/1567205014666170505101426.

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Background: There are now significant evidences that lipid metabolism is affected in numerous neurodegenerative diseases including Alzheimer’s disease. These dysfunctions lead to abnormal levels of certain lipids in the brain, cerebrospinal fluid and plasma. It is consequently of interest to establish lipid profiles in neurodegenerative diseases. This approach, which can contribute to identify lipid biomarkers of Alzheimers' disease, can also permit to identify new therapeutic targets. It was therefore of interest to focus on central and peripheral biomarkers in Alzheimer's disease. Methods: A review of the literature on 148 papers was conducted. Based on this literature, the involvement of lipids (cholesterol and oxysterols, fatty acids, phospholipids) in Alzheimer's disease has been proposed. Results: Of the 148 references cited for lipid biomarkers for Alzheimer's disease, 65 refer to cholesterol and oxysterols, 35 to fatty acids and 40 to phospholipids. Among these lipids, some of them such as 24S-hydroxyckolesterol, open up new therapeutic perspectives in gene therapy, in particular. The results on the very long-chain fatty acids suggest the potential of peroxisomal dysfunctions in Alzheimer's disease. As for the phospholipids, they could constitute interesting biomarkers for detecting the disease at the prodromal stage. Conclusion: There are now several lines of evidence that lipids play fundamental roles in the pathogenesis of AD and that some of them have a prognostic and diagnosis value. This may pave the way for the identification of new therapeutic targets, new effective drugs and / or new treatments.
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Graham, Nori. "Alzheimer's Disease International." International Psychogeriatrics 9, no. 1 (March 1997): 5–6. http://dx.doi.org/10.1017/s1041610297004146.

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Alzheimer's Disease International (ADI) aims to promote and support the work of national Alzheimer associations. Their main purpose is to support carers of people with Alzheimer's disease and related dementias, and to raise awareness of the impact of the disease on the individual and the carer.
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BAR, Hassan. "Various Infections and Alzheimer's Disease." Virology & Immunology Journal 7, no. 3 (July 7, 2023): 1–3. http://dx.doi.org/10.23880/vij-16000317.

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Alzheimer's disease (AD) is a major contributor to the worldwide prevalence of dementia. Extracellular-amyloid (A) senile plaques (SP) and intracellular neurofibrillary tangles (NFT) are the neuropathological hallmarks of Alzheimer's disease. Currently, it is believed that both hereditary and environmental variables interact to contribute to the pathophysiology of AD. Despite significant investments in neurological research, the precise molecular basis of AD pathogenesis remains unknown. Multiple studies point to the possibility that pathogenic microorganisms contribute to the development of AD. Microbes were formerly thought to have no connection to Alzheimer's disease, but a rising body of research suggests otherwise. Evidence that these microbes cause AD-specific cognitive and neuropathological deficits and changes is lacking, casting doubt on the hypothesis that AD is an infectious neurological illness. In addition, the gut flora may have a role in AD progression in humans.
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Zhao, Bin. "Statistical analysis on Alzheimer's disease." Journal of Infectious Diseases & Travel Medicine 7, no. 2 (October 31, 2023): 1–18. http://dx.doi.org/10.23880/jidtm-16000177.

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Alzheimer's disease is a progressive neurodegenerative disease that occurs mostly in the elderly and has memory impairment as the main clinical symptom. There is no ideal treatment for Alzheimer's disease, so early prevention is important. In this paper, we use brain structural information to diagnose Alzheimer's disease features and cognitive-behavioral characteristics, which is important for early and accurate diagnosis of mild cognitive impairment. To investigate the factors influencing Alzheimer's disease, a correlation analysis model was developed after preprocessing the missing values of the data. First, the data features were viewed, the missing values of the data were analyzed, and the useless features were removed and the missing values of the remaining features were filled with the average value. To verify the accuracy of the subsequent intelligent diagnosis model and clustering model, this paper divides the training set and test set according to PTID. Finally, the top ten important features are selected and the Spearman coefficients are chosen according to the distribution of the features for correlation analysis. Machine learning methods were utilized to build an Alzheimer's classification model to solve the problem of intelligent diagnosis of Alzheimer's disease. The pre-processed dataset in the above paper was trained with the model, and five methods of logistic regression, support vector machine, KNN classification, decision tree classification and XGB were utilized to build the classification model, and the accuracy, recall and F1 value of each model were visualized and compared, among which the accuracy of XGB model reached 83%, which is reasonable for the intelligent diagnosis of the disease. A K-Means-based clustering model for disease types was established using the K-Means clustering algorithm, clustering CN, MCI and AD into three major classes, and then refining MCI into three subclasses. The optimal K-values and random seeds were firstly found using the elbow principle, then the cluster analysis was performed using the feature values and data sets selected after preprocessing, and finally the MCI in MCI was extracted and sub-clustered into three subclasses SMC, EMCI and LMCI. In order to investigate the evolution pattern of different categories of diseases over time, patients with 3 categories of diseases are screened separately for analysis in this paper. Firstly, by combining the results above and reviewing the data, the features irrelevant to this task and columns containing a large number of missing values were removed, the remaining features were selected and probability density plots were drawn, and all discrete features and all features that were essentially zero were continued to be screened out. After that, the 15 features of CN, MCI and AD diseases were plotted separately over time to reveal their evolution patterns over time. We reviewed the relevant literature, sorted out and summarized the existing studies at home and abroad, and summarized the criteria for determining the five stages of Alzheimer's disease and the early intervention of the disease.
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Rajesh, Ravula, Singadi Akhil Reddy, Gandikota Varma Devraj, Raghuram Bhukya, Harika Dasari, and Naaram Srichandana. "Region-based Convolutional Neural Network Driven Alzheimer’s Severity Prediction." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 6 (August 8, 2023): 465–70. http://dx.doi.org/10.17762/ijritcc.v11i6.7784.

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It's important to note that Alzheimer's disease can also affect individuals over the age of 60, and in fact, the risk of developing Alzheimer's increases with age. Additionally, while deep learning approaches have shown promising results in detecting Alzheimer's disease, they are not the only techniques available for diagnosis and treatment. That being said, using Region-based Convolutional Neural Network (RCNN) for efficient feature extraction and classification can be a valuable tool in detecting Alzheimer's disease. This new approach to identifying Alzheimer's disease could lead to a more accurate and personalized diagnosis. It can also help in early treatment and intervention. However, it's still important to continue developing new methods and techniques for this disorder. Considering this our work proposes an innovative Region-based Convolutional Neural Network Driven Alzheimer’s Severity Prediction approach in this paper. The exhaustive experimental result carried out, which proves the efficacy of our Alzheimer prediction system.
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VanDongen, Antonius M. "Arc: A new target for treating alzheimer's disease." Open Access Government 43, no. 1 (July 8, 2024): 160–61. http://dx.doi.org/10.56367/oag-043-11454.

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Arc: A new target for treating alzheimer's disease Antonius M. VanDongen, Associate Professor from Duke University, walks us through Arc, a new target for treating Alzheimer’s disease. Alois Alzheimer is a German psychiatrist credited with identifying the first case of the debilitating disease named after him. In 1906, he described neurofibrillary tangles and amyloid plaques in his patient’s brain as unique hallmarks of her dementia. Advances in neuroimaging, genetics, and molecular biology have expanded our understanding of the mechanisms underlying Alzheimer’s disease (AD) significantly. But despite heroic efforts to find a cure, there is currently no therapy that prevents, stabilizes or reverses the progression of this disorder that is poised to take on epidemic proportions as the world ages.
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Rimmer, Elizabeth. "Alzheimer's Disease International." International Psychiatry 3, no. 4 (October 2006): 22–23. http://dx.doi.org/10.1192/s1749367600004999.

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Alzheimer's Disease International (ADI) is the international federation of 75 Alzheimer associations throughout the world and is in official relations with the World Health Organization. ADI was established to raise awareness about dementia, strengthen Alzheimer associations and provide a platform for the exchange of knowledge with the ultimate goal of improving the quality of life of people with dementia and their families.
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Conte, G. L., and M. Pomponi. "Alzheimer's or alzheimer-perusini's disease?" European Psychiatry 22 (March 2007): S297. http://dx.doi.org/10.1016/j.eurpsy.2007.01.1008.

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Corriveau, Roderick A., Walter J. Koroshetz, Jordan T. Gladman, Sophia Jeon, Debra Babcock, David A. Bennett, S. Thomas Carmichael, et al. "Alzheimer's Disease–Related Dementias Summit 2016: National research priorities." Neurology 89, no. 23 (November 8, 2017): 2381–91. http://dx.doi.org/10.1212/wnl.0000000000004717.

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Goal 1 of the National Plan to Address Alzheimer’s Disease is to prevent and effectively treat Alzheimer disease and Alzheimer disease–related dementias by 2025. To help inform the research agenda toward achieving this goal, the NIH hosts periodic summits that set and refine relevant research priorities for the subsequent 5 to 10 years. This proceedings article summarizes the 2016 Alzheimer's Disease–Related Dementias Summit, including discussion of scientific progress, challenges, and opportunities in major areas of dementia research, including mixed-etiology dementias, Lewy body dementia, frontotemporal degeneration, vascular contributions to cognitive impairment and dementia, dementia disparities, and dementia nomenclature.
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Ojetunde, Ayodeji Oluwatobi. "The Neuroprotective and Therapeutic Effects of Medicinal Plants and Natural Products against Aluminium Chloride-Induced Alzheimer’s Disease: Recent Update." Biology, Medicine, & Natural Product Chemistry 13, no. 1 (May 2, 2024): 7–33. http://dx.doi.org/10.14421/biomedich.2024.131.7-33.

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Alzheimer's disease currently affects more than 35 million individuals worldwide. Aluminium has been implicated in the pathogenesis of various cognitive disorders. Meanwhile, aluminium chloride (AlCl3) has a significant impact on the progression of neurodegenerative diseases including Alzheimer's disease. The majority of Alzheimer's disease medications now on the market are cholinesterase inhibitors. However, the effectiveness of these drugs is limited because they can't totally arrest the progression of the disease. The utilization of medicinal plants and natural products may present excellent prospective options for Alzheimer's disease prevention and therapy. This study summarized medicinal plants and natural products for the prevention and treatment of AlCl3-induced Alzheimer’s disease as an alternative therapy using published data in the literature from the years 2021-2023. The medicinal plants and natural products help to reduce Alzheimer’s disease pathogenesis by controlling different pathways and could be used as a therapeutic agent against the symptoms. The majority of the medicinal plants and natural products discussed in this review have been shown to have neuroprotective, antioxidant, anti-amyloid, anti-inflammatory, anticholinesterase, anti-apoptotic, and therapeutic actions. Therefore, medicinal plants and natural products may offer neuroprotective and therapeutic effects in the treatment of Alzheimer’s disease.
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Dissertations / Theses on the topic "Alzheimer's disease"

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Russell, Teresa. "Alzheimer's disease : expressed concern for problem behaviors /." free to MU campus, to others for purchase, 1997. http://wwwlib.umi.com/cr/mo/fullcit?p1390668.

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Navaratnam, Dasakumar Selveraj. "Cholinesterases in Alzheimer's disease." Thesis, University of Oxford, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.306734.

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Newman, Tracey Anne. "Ageing and Alzheimer's disease." Thesis, University of Southampton, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.246220.

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Montacute, Rebecca. "Infection in Alzheimer's disease." Thesis, University of Manchester, 2017. https://www.research.manchester.ac.uk/portal/en/theses/infection-in-alzheimers-disease(a69fbf77-1455-4a78-a700-54815cad926d).html.

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Infections are a common co-morbidity in Alzheimer's disease (AD), and evidence suggests that infections can exacerbate neuroinflammation and increase cognitive decline in AD patients. In AD, immune changes are observed both in the central nervous system (CNS) and in the rest of the body. However, only a few studies have investigated immune responses to infection in AD. Here, two extensively studied infections, Toxoplasma gondii (T. gondii) and Trichuris muris (T. muris) were used to investigate infection in AD. T. gondii is a protozoan parasite which is common globally, including in the developed world where AD cases are increasing dramatically. Infection with T. gondii starts in the gut, before becoming systemic and then infecting the CNS, where the parasite forms a chronic cyst infection. In contrast, T. muris is a nematode parasite, which remains localised to the gut. Notably, T. gondii is known to alter neuroinflammation and behaviour. T. gondii forms cysts preferentially in the areas of the brain commonly affected by AD, such as the hippocampus, which therefore makes it an interesting model to study co-morbidity. AD is often associated with advanced age. As we age, our immune system declines, and an important unanswered question is whether age impacts on the immune response to infection. This is of particular significance when considering chronic infections such as T. gondii, which require immune surveillance to prevent parasite recrudescence. Therefore, the aim of this thesis was to investigate infection in AD by determining: whether the immune response to an infection is altered in AD; whether the immune response to an infection in AD differs with age; what the effects of infection are on neuroinflammation, pathology and behaviour in AD; what are the effects of chronic infection with T. gondii. Immune responses to infection were altered in both the 3xTg-AD and the APP PS1 mouse models of AD, including increased inflammation and weight loss in AD mice following infection. Although older (eleven to twelve-month-old) 3xTg-AD mice showed some alterations in cytokine responses following infection, overall there were no major difference compared to younger (five to six-month-old) animals. Additionally, infection was found to alter neuroinflammation in both 3xTg-AD and APP PS1 mice, though differently. In 3xTg-AD mice, microglia activation increased following infection with T. gondii and T. muris, showing that infection did not need to be in the brain to alter neuroinflammation. In APP PS1 mice, a decrease in microglia activation occurred after infection with T. gondii, which was accompanied by an increase in IL-1alpha production and increased amyloid beta levels in APP PS1 mice following infection. However, no changes were found in behaviour following infection with T. gondii or T. muris in AD mouse models. Finally, chronic T. gondii infection was investigated in the TgF344-AD rat, which was established as a suitable AD model with both amyloid and tau pathology in which to study chronic infection. This work adds to a growing body of literature to suggest that infections are detrimental to AD patients, and that future measures to decrease morbidity could focus on further study of infections in AD, and the development of strategies to better prevent infections in AD patients.
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Zubair, Mohammed. "Metabolomics in Alzheimer's disease." Thesis, University of Manchester, 2013. https://www.research.manchester.ac.uk/portal/en/theses/metabolomics-in-alzheimers-disease(0872757b-d25a-4c43-bd52-915d4cad21c6).html.

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Metabolites are a potentially useful source of detecting and identifying disease specific biomarkers. This thesis investigates the possibility of using metabolomics applications to detect Alzheimer’s disease associated metabolite peaks in patients and to detect longitudinal changes of the disease. Serum samples and clinical data were collected from 60 healthy controls and 60 Alzheimer’s disease patients (60 at baseline and 60 at 12 month follow-up). The metabolic fingerprinting of serum samples using the FT-IR lacked discriminatory power to discriminate Alzheimer’s disease and non-disease samples due to the similar magnitude of biological and analytical variation. The metabolic profiling of serum samples using the GC-ToF-MS did not reveal any significantly altered metabolite peaks between the Alzheimer’s disease and non-disease groups. Metabolic profiling of serum samples using the UPLC-LTQ/Orbitrap-MS operated in the positive ionisation mode did not reveal any significantly altered metabolite peaks between the disease and non-disease groups. Up to twelve metabolite peaks were significantly altered in the Alzheimer’s disease baseline and follow-up samples, indicating a potential association with disease progression. Metabolic profiling of serum samples using the UPLC-LTQ/Orbitrap-MS operated in the negative ionisation mode did not reveal any significantly altered metabolite peaks between Alzheimer’s disease and non-disease groups. Three metabolite peaks were significantly altered in the Alzheimer’s disease baseline and follow-up samples, indicating a potential association with disease progression. Metabolic profiling of serum samples with the UPLC-LTQ/Orbitrap-MS may potentially be used to detect disease and disease progression associated metabolite peaks. The metabolite peaks require identification followed by a validation experiment.
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Shie, Feng-Shiun. "Cholesterol and Alzheimer's disease /." Thesis, Connect to this title online; UW restricted, 2000. http://hdl.handle.net/1773/6604.

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梁欣珮 and Yan-pui Irene Leung. "Potential impact of alzheimer's disease on retina." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2009. http://hub.hku.hk/bib/B42905059.

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Hynd, Matthew. "Excitotoxic neurodegeneration in Alzheimer's disease /." [St. Lucia, Qld.], 2004. http://www.library.uq.edu.au/pdfserve.php?image=thesisabs/absthe18145.pdf.

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Blom, Elin. "Genetic Studies of Alzheimer's Disease." Doctoral thesis, Uppsala universitet, Institutionen för folkhälso- och vårdvetenskap, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-9397.

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Patients with Alzheimer's disease (AD) often have a family history of the disease, implicating genetics as a major risk factor. Three genes are currently known to cause familial early-onset AD (<65 years): the amyloid precursor protein (APP) and the presenilins (PSEN1 and PSEN2). For the much more common late-onset disease (>65 years), only the APOE gene has repeatedly been associated to AD, where the ε4 allele increases disease risk and decreases age at onset. As APOE ε4 only explains part of the total estimated disease risk, more genes are expected to contribute to AD. This thesis has focused on the study of genetic risk factors involved in AD. In the first study, we conducted a linkage analysis of six chromosomes previously implicated in AD in a collection of affected relative pairs from Sweden, the UK and the USA. An earlier described linkage peak on chromosome 10q21 could not be replicated in the current sample, while significant linkage was demonstrated to chromosome 19q13 where the APOE gene is located. The linkage to 19q13 was further analyzed in the second study, demonstrating no significant evidence of genes other than APOE contributing to this peak. In the third study, the prevalence of APP duplications, a recently reported cause of early-onset AD, was investigated. No APP duplications were identified in 141 Swedish and Finnish early-onset AD patients, implying that this is not a common disease mechanism in the Scandinavian population. In the fourth study, genes with altered mRNA levels in the brain of a transgenic AD mouse model (tgAPP-ArcSwe) were identified using microarray analysis. Differentially expressed genes were further analyzed in AD brain. Two genes from the Wnt signaling pathway, TCF7L2 and MYC, had significantly increased mRNA levels in both transgenic mice and in AD brains, implicating cell differentiation and possibly neurogenesis in AD.
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Bakerink, Ronda Ann. "Semantic memory in Alzheimer's Disease." Thesis, University of British Columbia, 1988. http://hdl.handle.net/2429/27795.

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Alzheimer's Disease is characterized by a general decline in cognitive functioning. Although phonology are relatively unaffected, patients with Alzheimer's Disease have been reported to have deficits of semantic memory. Thirteen patients with dementia, five of whom had a confirmed diagnosis of dementia, participated in the study. The purpose of this investigation was to replicate a study performed by Mark Byrd (1984), using Alzheimer's Disease patients. Subjects were presented with category-word decision pairs, for which the task was to decide if the word was an exemplar of the category, and category-letter decision pairs for which the task was to generate an exemplar of the category beginning with the letter. The dependent variable was reaction time. Results indicated that Alzheimer's Disease patients and dementia patients had longer reaction times than a group of age-matched control subjects, and that the Alzheimer's Disease and dementia patients showed a pattern of responses similar to that of the control subjects. All groups showed longer reaction times for the generation trials than the decision trials. The results are consistent with the existence of a semantic memory deficit in Alzheimer's Disease, but other interpretations were discussed.
Medicine, Faculty of
Audiology and Speech Sciences, School of
Graduate
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Books on the topic "Alzheimer's disease"

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1936-, Wurtman Richard J., ed. Alzheimer's disease. New York: Raven Press, 1990.

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Dempsey, Denise P. Alzheimer's disease. Washington, D.C. (101 Independence Ave., S.E., Washington 20540: Science Reference Section, Science and Technology Division, Library of Congress, 1997.

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Dempsey, Denise P. Alzheimer's disease. Washington, D.C: Science Reference Section, Science and Technology Division, Library of Congress, 1997.

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D, Terry Robert, Katzman Robert, and Bick Katherine L, eds. Alzheimer disease. New York: Raven Press, 1993.

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D, Terry Robert, Katzman Robert, and Bick Katherine L, eds. Alzheimer disease. New York: Raven Press, 1994.

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Molloy, William. Alzheimer's disease. Buffalo, N.Y: Firefly Books, 2003.

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Molloy, William. Alzheimer's disease. Toronto, Ont: Key Porter Books, 1998.

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Hooper, Nigel M. Alzheimer's Disease. New Jersey: Humana Press, 1999. http://dx.doi.org/10.1385/1592591957.

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Richter, Ralph W., and Brigitte Zoeller Richter. Alzheimer's Disease. New Jersey: Humana Press, 2003. http://dx.doi.org/10.1385/1592596614.

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Strock, Margaret. Alzheimer's disease. [Washington, D.C.?]: National Institutes of Health, National Institute of Mental Health, 1994.

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Book chapters on the topic "Alzheimer's disease"

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Hort, J., J. T. O'Brien, G. Gainotti, T. Pirttila, B. O. Popescu, I. Rektorova, S. Sorbi, and P. Scheltens. "Alzheimer's Disease." In European Handbook of Neurological Management, 269–82. Oxford, UK: Wiley-Blackwell, 2010. http://dx.doi.org/10.1002/9781444328394.ch16.

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Khan, Qurat ul Ain, and Neill R. Graff-Radford. "Alzheimer's Disease." In Neurodegeneration, 102–14. Oxford, UK: John Wiley & Sons, Ltd, 2017. http://dx.doi.org/10.1002/9781118661895.ch11.

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Mandell, Alan M., and Robert C. Green. "Alzheimer's Disease." In The Handbook of Alzheimer's Disease and Other Dementias, 1–91. Oxford, UK: Wiley-Blackwell, 2011. http://dx.doi.org/10.1002/9781444344110.ch1.

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Böning, Dieter, Michael I. Lindinger, Damian M. Bailey, Istvan Berczi, Kameljit Kalsi, José González-Alonso, David J. Dyck, et al. "Alzheimer's Disease." In Encyclopedia of Exercise Medicine in Health and Disease, 57. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-540-29807-6_2076.

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Galvin, James E. "Alzheimer's Disease." In Pathy's Principles and Practice of Geriatric Medicine, 865–80. Chichester, UK: John Wiley & Sons, Ltd, 2012. http://dx.doi.org/10.1002/9781119952930.ch73.

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Reddy, K. Jayasankara. "Alzheimer's Disease." In Essentials of Neuropsychology, 169–82. London: Routledge, 2023. http://dx.doi.org/10.4324/9781032640839-17.

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Shigeta, Masahiro, and Akira Homma. "Alzheimer's Disease." In Handbook of Gerontology, 333–66. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2012. http://dx.doi.org/10.1002/9781118269640.ch13.

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Salmon, David P. "Alzheimer's disease." In Encyclopedia of psychology, Vol. 1., 130–33. Washington: American Psychological Association, 2000. http://dx.doi.org/10.1037/10516-044.

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Werhane, Madeleine L., David P. Sheppard, Kathleen F. Pagulayan, Mark W. Bondi, and Lisa Delano-Wood. "Alzheimer's Disease." In A Handbook of Geriatric Neuropsychology, 9–37. 2nd ed. New York: Routledge, 2022. http://dx.doi.org/10.4324/9781003100058-4.

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Chaudhary, Raushan Kumar, Uday Venkat Mateti, Pukar Khanal, Kala Bahadur Rawal, Praneetha Jain, Vishal S. Patil, Amit Kumar Shrivastava, and B. M. Patil. "Alzheimer's Disease." In Computational and Experimental Studies in Alzheimer's Disease, 1–14. Boca Raton: CRC Press, 2024. http://dx.doi.org/10.1201/9781003412069-1.

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Conference papers on the topic "Alzheimer's disease"

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Rumao, Priti, and Mamta Padole. "Alzheimer's Disease." In DSMLAI '21': International Conference on Data Science, Machine Learning and Artificial Intelligence. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3484824.3484886.

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Costa, Pedro Araujo. "Construction of an educational manual for caregivers of elderly people with Alzheimer's disease." In IV Seven International Congress of Health. Seven Congress, 2024. http://dx.doi.org/10.56238/homeivsevenhealth-010.

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Population aging has been occurring progressively and in Brazil there is an accelerating growth curve. According to the World Health Organization, dementia is one of the greatest public health challenges of the current generation, in which the Alzheimer's disease subtype accounts for the majority of diagnosed cases. In this context, this study aimed to describe the construction of an educational manual to support family caregivers of elderly people diagnosed with Alzheimer's disease. This is a descriptive, methodological study. Initially, a bibliographic survey was carried out on the subject in the following databases: CINAHL, SCOPUS/ Elsevier and Pubmed-Medline; using the descriptors “elderly”, “Alzheimer” and “caregiver”. The educational manual was developed on the Figma platform, structured on the basis of the aspects that emerged from the bibliographic survey, considering aspects of language, illustration and layout/design. A group of researchers specializing in the subject was selected for convenience to support the construction of the educational manual. The contents chosen for the educational manual were: What is Alzheimer's disease (AD)?; What causes Alzheimer's disease (AD); The stages of Alzheimer's disease (AD); The symptoms of Alzheimer's disease (AD); How to deal with behavioral changes in Alzheimer's disease (AD); Tips on hygiene, bathing, eating, the environment, cognitive and memory activities; Bibliographical references. The aim of this study was achieved, since the manual entitled “Caring for elderly people with Alzheimer's disease (AD)” was created by selecting content from the main sources on the subject. The limitations of this study are that the subject is not exhausted by the topics covered; however, too much content could make the educational material long and tiring, which is why it was decided to cover the main topics on the subject.
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Collar, Giovanna Carello, Marco Antônio De Bastiani, and Eduardo R. Zimmer. "HUNTINGTON’S DISEASE AND EARLYONSET ALZHEIMER’S DISEASE SHARE A TRANSCRIPTOMIC SIGNATURE." In XIII Meeting of Researchers on Alzheimer's Disease and Related Disorders. Zeppelini Editorial e Comunicação, 2021. http://dx.doi.org/10.5327/1980-5764.rpda082.

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Background: Neurodegenerative diseases share progressive loss of neurons and protein misfolding, which ultimately culminates in dementia; many diseases have been identified as causes of early-onset dementia (< 65 years of age) such as Huntington’s disease (HD) and early-onset Alzheimer’s disease (EOAD). Importantly, disease-specific genetic mutations have already been identified for HD and EOAD. Thus, one could suggest that the molecular link between these diseases may arise from alterations at the transcriptomic level, which is yet to be determined. Objective: We aimed at identifying transcriptome similarities between HD and EOAD. Methods: We collected data of the postmortem cerebral cortex from 1 HD and 6 AD microarray studies in the Gene Expression Omnibus. Of note, only subjects with age at death under 65 were selected (HD: n = 158, controls: n = 158; EOAD: n = 65, controls: n = 266). Differential expression and functional enrichment analyses were performed. Results: We identified 1,260 differentially expressed genes and 675 enriched gene ontology terms between HD and EOAD. Conclusion: Our results demonstrate a transcriptomic signature shared by HD and EOAD. Unveiling the similarities between these diseases at the transcriptomic level could advance our knowledge about pathogenesis and may help to develop therapeutic strategies targeting early-onset dementias.
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Poland, Bradley W., Panayiotis Zagouras, Snehal Naik, Eric Fauman, Karl Richter, and Robert M. Peitzsch. "Alzheimer's disease target selection." In the First ACM International Conference. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1854776.1854870.

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Brown, Anne, Nicholas Polys, David Bevan, and Ayat Mohammed. "Insights into Alzheimer's Disease." In XSEDE16: Diversity, Big Data, and Science at Scale. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2949550.2952773.

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Mao, Wenlu. "Overview of Alzheimer's Disease." In ICBBE '20: 2020 7th International Conference on Biomedical and Bioinformatics Engineering. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3444884.3444900.

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Zender, P. Mike, and Keith A. Crutcher. "Visualizing Alzheimer's disease research." In ACM SIGGRAPH 2004 Educators program. New York, New York, USA: ACM Press, 2004. http://dx.doi.org/10.1145/1186107.1186135.

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Zhao, Haozuo, Haitao Chu, Sicheng Zhou, Fang Yu, Xianghua Luo, and Rui Zhang. "Racial Disparities in Alzheimer's Disease and Alzheimer's Disease-Related Dementias from the Disease Progression Perspective." In 2022 IEEE 10th International Conference on Healthcare Informatics (ICHI). IEEE, 2022. http://dx.doi.org/10.1109/ichi54592.2022.00107.

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Shoaip, Nora, Sherif Barakat, and Mohammed Elmogy. "Alzheimer's Disease Integrated Ontology (ADIO)." In 2019 14th International Conference on Computer Engineering and Systems (ICCES). IEEE, 2019. http://dx.doi.org/10.1109/icces48960.2019.9068176.

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Bobkova, Natalia. "ALZHEIMER'S DISEASE: YESTERDAY, TODAY, TOMORROW." In XV International interdisciplinary congress "Neuroscience for Medicine and Psychology". LLC MAKS Press, 2019. http://dx.doi.org/10.29003/m647.sudak.ns2019-15/492-493.

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Reports on the topic "Alzheimer's disease"

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Huedepohl, Cole. Alzheimer's Disease & Gene Therapy. Ames (Iowa): Iowa State University, May 2023. http://dx.doi.org/10.31274/cc-20240624-149.

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Stevens, Brianna. Retinal Changes Associated with Alzheimer's Disease. Ames (Iowa): Iowa State University, January 2020. http://dx.doi.org/10.31274/cc-20240624-1231.

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Mehegan, Laura. Alzheimer's Disease and Dementia Awareness Poll 2018. AARP Research, June 2018. http://dx.doi.org/10.26419/res.00232.001.

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Chandra, Amitabh, Courtney Coile, and Corina Mommaerts. What Can Economics Say About Alzheimer's Disease? Cambridge, MA: National Bureau of Economic Research, August 2020. http://dx.doi.org/10.3386/w27760.

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Mintzer, Jacobo E., D. L. Bachman, M. Stuckey, M. Ebeling, M. T. Wagner, W. J. Evans, V. Hirth, A. Walker, R. Joglekar, and W. Faison. A State-Wide Research Network for Alzheimer's Disease. Office of Scientific and Technical Information (OSTI), March 2014. http://dx.doi.org/10.2172/1123171.

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Mehegan, Laura. Alzheimer's Disease and Dementia Awareness Poll 2018: Infographic. AARP Research, June 2018. http://dx.doi.org/10.26419/res.00232.002.

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Pericak-Vance, Margaret A. Whole Exome Analysis of Early Onset Alzheimer's Disease. Fort Belvoir, VA: Defense Technical Information Center, April 2013. http://dx.doi.org/10.21236/ada602412.

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Pericak-Vance, Margaret A. Whole Exome Analysis of Early Onset Alzheimer's Disease. Fort Belvoir, VA: Defense Technical Information Center, April 2014. http://dx.doi.org/10.21236/ada603027.

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Han, Nana, Yang Fang, Guozhen Zhao, and Bo Ji. The comparative efficacy and safety of acupuncture for mild and moderate Alzheimer's disease: A systematic review and network meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, November 2021. http://dx.doi.org/10.37766/inplasy2021.11.0014.

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Review question / Objective: According to the current randomized clinical trials (RCT) of acupuncture therapy for Alzheimer's disease (AD), to evaluate their methodology, the quality of evidence and the report are evaluated and summarize evidence of important outcomes of randomized clinical trials. We aim to provide accurate clinical decision-making for acupuncture treatment of Alzheimer's disease. Condition being studied: According to the current randomized clinical trials (RCT) of acupuncture therapy for Alzheimer's disease (AD), to evaluate their methodology, the quality of evidence and the report are evaluated and summarize evidence of important outcomes of randomized clinical trials. We aim to provide accurate clinical decision-making for acupuncture treatment of Alzheimer's disease.
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Duncan, Marie. Alzheimer's Disease Caregivers: The Transition from Home Care to Formal Care. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.3220.

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