Abstract
The rapid pattern of population ageing in recent years increases the risk of appearance of associated neurodegenerative diseases. Dementias are one of the most feared disorders, and although not necessarily all elderly people have dementia, the number of people with this disease is increasing rapidly. The causes of dementia are multiple, and the diagnosis of the different types of dementia is complicated since most patients display mixed dementias and symptoms overlapping. Personalized diagnosis and treatments would be desirable, but this requires a deep knowledge of each type of dementia where a multidisciplinary approach would be ideal. Thus, the aim of this review is to summarize the features of the main types of dementia as well as to compilate the more recent findings on this subject, ranging from genetic and molecular studies to animal models, including the use of omics platforms based on powerful hybrid instrumental techniques, and neuroimage techniques. On the other hand, we consider the aspects that can prevent these disorders and depend on modifiable factors, such as diet, among others. Finally, new technologies, such as nanotechnology can provide novel strategies for the administration of effective treatments. In this regard, our purpose is to provide the most updated and complete overview of state of the art about characteristics of these disorders.
Keywords: Dementia, genetic studies, analytical chemistry, neuroimage techniques, rodent models, preventive strategies, nanotechnology.
Current Pharmaceutical Design
Title:Neurodegenerative Diseases: A Multidisciplinary Approach
Volume: 27 Issue: 30
Author(s): Pilar Marcos-Rabal*, Joaquín González-Fuentes, Lucía Castro-Vázquez, María V. Lozano, Virginia Rodríguez-Robledo, Manuel J. Santander-Ortega, Jorge Selva-Clemente, Noemí Villaseca-González and María del Mar Arroyo-Jiménez
Affiliation:
- Cellular Neurobiology and Molecular Chemistry of the Central Nervous System Group, Faculty of Medicine, Faculty of Pharmacy, and Regional Centre of Biomedical Research (CRIB), University of Castilla-La Mancha, Albacete,Spain
Keywords: Dementia, genetic studies, analytical chemistry, neuroimage techniques, rodent models, preventive strategies, nanotechnology.
Abstract: The rapid pattern of population ageing in recent years increases the risk of appearance of associated neurodegenerative diseases. Dementias are one of the most feared disorders, and although not necessarily all elderly people have dementia, the number of people with this disease is increasing rapidly. The causes of dementia are multiple, and the diagnosis of the different types of dementia is complicated since most patients display mixed dementias and symptoms overlapping. Personalized diagnosis and treatments would be desirable, but this requires a deep knowledge of each type of dementia where a multidisciplinary approach would be ideal. Thus, the aim of this review is to summarize the features of the main types of dementia as well as to compilate the more recent findings on this subject, ranging from genetic and molecular studies to animal models, including the use of omics platforms based on powerful hybrid instrumental techniques, and neuroimage techniques. On the other hand, we consider the aspects that can prevent these disorders and depend on modifiable factors, such as diet, among others. Finally, new technologies, such as nanotechnology can provide novel strategies for the administration of effective treatments. In this regard, our purpose is to provide the most updated and complete overview of state of the art about characteristics of these disorders.
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Cite this article as:
Marcos-Rabal Pilar*, González-Fuentes Joaquín, Castro-Vázquez Lucía, Lozano V. María, Rodríguez-Robledo Virginia , Santander-Ortega J. Manuel, Selva-Clemente Jorge, Villaseca-González Noemí and del Mar Arroyo-Jiménez María , Neurodegenerative Diseases: A Multidisciplinary Approach, Current Pharmaceutical Design 2021; 27 (30) . https://dx.doi.org/10.2174/1381612827666210608152745
DOI https://dx.doi.org/10.2174/1381612827666210608152745 |
Print ISSN 1381-6128 |
Publisher Name Bentham Science Publisher |
Online ISSN 1873-4286 |
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