Emerging Technologies for Diagnosing Alzheimer's Disease
Emerging Technologies for Diagnosing Alzheimer's Disease

Author: Marianne Boenink

Publisher: Springer

Published: 2016-09-13

Total Pages: 300

ISBN-13: 1137540974

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This book explores international biomedical research and development on the early diagnosis of Alzheimer's disease. It offers timely, multidisciplinary reflections on the social and ethical issues raised by promises of early diagnostics and asks under which conditions emerging diagnostic technologies can be considered a responsible innovation. The initial chapters in this edited volume provide an overview and a critical discussion of recent developments in biomedical research on Alzheimer's disease. Subsequent contributions explore the values at stake in current practices of dealing with Alzheimer's disease and dementia, both within and outside the biomedical domain. Novel diagnostic technologies for Alzheimer's disease emerge in a complex and shifting field, full of controversies. Innovating with care requires a precise mapping of how concepts, values and responsibilities are filled in through the confrontation of practices. In doing so, the volume offers a practice-based approach of responsible innovation that is also applicable to other fields of innovation.

Alzheimer's Disease
Alzheimer's Disease

Author: Harald Hampel

Publisher: Karger Medical and Scientific Publishers

Published: 2012

Total Pages: 200

ISBN-13: 3805598025

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How current biomarkers are modernizing the diagnosis of Alzheimer's disease Expanding knowledge on genetic and epigenetic risk factors is rapidly enhancing our understanding of the complex molecular interactions and systems involved in the pathogenesis of Alzheimer's disease. In this publication, leading experts discuss emerging novel conceptual models of the disease along with advances in the development of surrogate markers that will not only improve the accuracy of diagnostic technologies but also improve the prospects of developing disease-modifying interventions. The novel framework of the disease presented here highlights research on biological markers as well as efforts to validate technologies for early and accurate detection. It also introduces notion of a complex systems dysfunction that extends beyond prevailing ideas derived from the amyloid' or tau' hypotheses. This outstanding publication provides researchers, clinicians, students and other professionals interested in neurodegenerative disorders with a comprehensive update on current trends and future directions in therapy development, with special focus on advances in clinical trial designs.

Neurology in Clinical Practice
Neurology in Clinical Practice

Author: Walter George Bradley

Publisher:

Published: 2004

Total Pages: 1672

ISBN-13: 9780750674690

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New edition, completely rewritten, with new chapters on endovascular surgery and mitochrondrial and ion channel disorders.

Early Diagnosis of Alzheimer's Disease
Early Diagnosis of Alzheimer's Disease

Author: Leonard F. M. Scinto

Publisher: Springer Science & Business Media

Published: 2000-02-09

Total Pages: 384

ISBN-13:

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The three major approaches to diagnosis of AD -- radiological, biological, and neurophysiological -- are discussed in detail with chapters highlighting the most promising technologies within these approaches. The leading authors, all of whom are intimately involved with these emerging technologies, have developed this as an essential reference for neuropathologists, clinicians and researchers of Alzheimer's disease.

Alzheimer's Disease
Alzheimer's Disease

Author: Renee D. Wegrzyn

Publisher: CRC Press

Published: 2012-04-26

Total Pages: 308

ISBN-13: 1439827087

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In recent years, a tremendous amount of effort has been focused on better understanding the fundamentals of Alzheimer’s disease (AD) to facilitate early and accurate diagnosis and appropriately targeted therapeutic treatments. Alzheimer’s Disease: Targets for New Clinical, Diagnostic, and Therapeutic Strategies provides a detailed synopsis of the current state of the art of diagnostics and therapeutics and identifies emerging technologies and molecules that show promise in the management and treatment of AD. With contributions from experts drawn from academia, clinical practice, and the biotechnology and pharmaceutical industries, the book explores: The basis of AD and the role of Aβ oligomers in development of disease Existing and emerging in vitro biomarker-based methodologies for the diagnosis of AD, focusing on genetic, biochemical, and conformational strategies In vivo imaging diagnostic approaches Evolving diagnostic criteria, health regulatory guidelines, biomarkers in clinical trials, and available and emerging therapies Recent progress in small-molecule disease-modifier drug discovery efforts for AD, specifically in the areas of Aβ, tau, and emerging neuroprotective/neurorepair approaches How a case study of AD raises issues regarding clinical and pathologic criteria, risk factors, and the amyloid hypothesis The molecular conformational factors that govern the pathogenicity of aggregating proteins, and how these factors could represent new targets for disease-modifying therapies The latest epidemiological, pathological, biochemical, and behavioral studies that may shed some light on the risk of developing AD and similar dementias after traumatic brain injury Examining current hypotheses and suggesting possible new approaches to therapeutic clinical applications, this volume paves the way for a robust pipeline of therapeutics to combat not only AD, but a whole host of other neurodegenerative diseases.

Handbook of Research on Innovations in the Diagnosis and Treatment of Dementia
Handbook of Research on Innovations in the Diagnosis and Treatment of Dementia

Author: Bamidis, Panagiotis D.

Publisher: IGI Global

Published: 2015-03-31

Total Pages: 539

ISBN-13: 1466682353

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Technology is playing an increasing role in the lives of the elderly. One of the most prevalent developments for the aging population is the use of technological innovations for intervention and treatment of individuals with mental impairments. The Handbook of Research on Innovations in the Diagnosis and Treatment of Dementia offers empirical research and theoretical analyses on the cognitive impairment of the aging. Featuring studies in gerotechnology, this book is an essential resource for researchers, students, and practitioners in the field of geriatrics who are interested in the emerging research, clinical practices, therapy, and technological innovations concerning the development and treatment of dementia.

Use of Machine Learning Technology in the Diagnosis of Alzheimer's Disease
Use of Machine Learning Technology in the Diagnosis of Alzheimer's Disease

Author: Noel O'Kelly

Publisher:

Published: 2016

Total Pages: 0

ISBN-13:

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Alzheimer's disease (AD) is thought to be the most common cause of dementia and it is estimated that only 1-in-4 people with Alzheimer's are correctly diagnosed in a timely fashion. While no definitive cure is available, when the impairment is still mild the symptoms can be managed and treatment is most effective when it is started before significant downstream damage occurs, i.e., at the stage of mild cognitive impairment (MCI) or even earlier. AD is clinically diagnosed by physical and neurological examination, and through neuropsychological and cognitive tests. There is a need to develop better diagnostic tools, which is what this thesis addresses. Dublin City University School of Nursing and Human Sciences runs a memory clinic, Memory Works where subjects concerned about possible dementia come to seek clarity. Data collected at interview is recorded and one aim of the work in this thesis is to explore the use of machine learning techniques to generate a classifier that can assist in screening new individuals for different stages of AD. However, initial analysis of the features stored in the Memory Works database indicated that there is an insufficient number of instances available (about 120 at this time) to train a machine learning model to accurately predict AD stage on new test cases. The National Azheimers Cordinating Center (NACC) in the U.S collects data from National Institute for Aging (NIA)-funded Alzheimer's Disease Centers (ADCs) and maintains a large database of standardized clinical and neuropathological research data from these ADCs. NACC data are freely available to researchers and we have been given access to 105,000 records from the NACC. We propose to use this dataset to test the hypothesis that a machine learning classifier can be generated to predict the dementia status for new, previously unseen subjects. We will also, by experiment, establish both the minimum number of instances required and the most important features from assessment interviews, to use for this prediction.

Microbes and Microstructure
Microbes and Microstructure

Author: Nicholas Vogt

Publisher:

Published: 2020

Total Pages: 0

ISBN-13:

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Alzheimer's disease (AD) currently has no prevention, treatment, or cure, and the etiology of this devasting neurodegenerative disease remains largely unclear, despite decades of research. In order to combat the significant challenges posed by AD, it will be critical to improve our understanding of factors that contribute to disease as well as to develop sensitive markers of early pathological changes. Towards this end, the work included in this dissertation focused on the role of the gut microbiome in AD, as well as the use of advanced multi-shell diffusion-weighted MRI to characterize cortical microstructural alterations in preclinical and clinical AD. In Chapter 1, we performed the first comprehensive survey of gut microbiota in individuals with AD and revealed broad-scale alterations in gut bacterial composition in individuals with AD. Moreover, we also found that gut bacterial taxa that are altered in AD correlate with cerebrospinal fluid (CSF) biomarkers of AD pathology, even in cognitively unimpaired individuals. In Chapter 2, we found that the gut microbiota-derived metabolite trimethylamine N-oxide (TMAO), which has been linked to brain aging and cognitive impairment in mice, is elevated in the CSF of individuals with AD and mild cognitive impairment (MCI), and that levels of CSF TMAO correlate with markers of AD pathology and neurodegeneration. In Chapter 3, we used neurite orientation dispersion and density imaging (NODDI), a multi-compartment diffusion-weighted imaging (DWI) model, to show that cortical NODDI metrics are altered in individuals with MCI and AD. Notably, for individuals with MCI, several key brain regions showed changes in cortical microstructure but not cortical thickness. In Chapter 4, we extended this work into the preclinical stage of AD and found a non-monotonic relationship between AD pathology and cortical neurite density, but not cortical thickness, suggesting that NODDI metrics are more sensitive markers of early neurodegenerative changes than conventional T1-weighted MRI measurements. Overall, the work included in this dissertation contributes to addressing the enormous problem of AD by furthering our growing understanding of the role of gut microbiota in AD, as well as highlighting the utility of NODDI metrics in detecting early cortical microstructural changes.

Early Detection in Alzheimer's Disease
Early Detection in Alzheimer's Disease

Author: Dennis Chan

Publisher: Academic Press

Published: 2023-12-01

Total Pages: 0

ISBN-13: 9780128222409

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Early Detection of Alzheimer's Disease: Biological and Technological Advances aims to introduce to a wide audience the high global priority problem of detecting AD prior to dementia onset. According to the Alzheimer's Association, 5.8 million Americans are living with Alzheimer's and care costs will cost the nation approximately $290 billion (2019 Alzheimer's Disease Facts and Figures). With the failure of recent AD drug trials, many hypothesize that by the time symptoms appear, it is too late to be treated. Early detection can offer benefits such as more choice of medications, ability to participate in clinical trials, more time for family and for care planning. This book outlines potential solutions to the above problem using opportunities arising from the technology revolution, advances in neuroscience, and molecular biology. Most importantly, it discusses a paradigm shift from a reactive to a proactive diagnostic approach, aiming to detect disease before occurrence of symptoms. Topics covered include the use of sensing technologies (e.g. smartphones, smartwatches, Internet of Things) to detect early disease-related changes, the application of data science (machine learning/AI) to extract otherwise invisible disease features from these datasets and the potential to personalize diagnosis based on tracking changes in individual behaviours. Advances in blood-based biomarkers, brain imaging, and the potential for early diagnosis to aid interventions (lifestyle, dietary, pharmacological) to delay future development of dementia are also discussed.