Mogad Current Knowledge And Future Trends
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MOGAD, Current Knowledge and Future Trends
Author: Sasitorn Siritho
language: en
Publisher: Frontiers Media SA
Release Date: 2024-02-14
Myelin oligodendrocyte glycoprotein (MOG) antibody disease (MOGAD) is a neurological, immune-mediated disorder targeting MOG protein, located on the outermost myelin sheaths in the central nervous system. The diagnosis is confirmed when serum MOG antibody is found in patients in the context of inflammatory attacks of the central nervous system, usually with the brain, brainstem, optic nerve, and spinal cord. Although MOGAD manifestations can fulfill diagnostic criteria for Neuromyelitis optica disorder (NMOSD), evidence suggests that they have distinct immunological mechanisms. Similar to NMOSD, patients with persistent MOG antibodies are at risk for recurrent events. Recovery of MOGAD is generally reasonable. However, some patients get disability after a severe acute attack. Treatment for an acute attack is typically intravenous high-dose steroids, plasma exchange (PLEX), or intravenous immunoglobulin (IVIG). Maintenance therapy with immunosuppressants, i.e., azathioprine, mycophenolate, rituximab, etc., usually prevents future attacks, although they have long-term side effects. Therefore, it is still controversial how long treatment should be continued.
Exploring the Effects of Diet on the Development and Prognosis of Multiple Sclerosis (MS)
This book offers an insightful exploration into the relationship between diet and Multiple Sclerosis (MS), aiming to address a crucial question: Can dietary interventions serve as effective preventative and therapeutic measures for patients with MS? Delving into this question, the book examines various nutritional components and regimens, shedding light on their potential impacts on the progression, relapse rate, and development of MS. It offers readers valuable insights into how dietary choices can influence the management of this condition. Backed up by evidence gathered from review and clinical trial papers, the book discusses the role of vitamins such as A, B, and D, as well as dietary supplements like caffeine, carnitine, and lipoic acid in benefiting patients with MS. Particular attention is given to the significance of vitamin D in lowering the risk of developing MS and its immunomodulatory effects on the inflammatory processes associated with the disease. In parallel, the book also addresses the detrimental effects of diets such as the Western or high salt diet (HSD) on MS prognosis, emphasizing how these dietary regimens can harm the gut microbiome and exacerbate inflammatory responses, ultimately promoting demyelination of the central nervous system (CNS). The book then explores alternative dietary approaches that confer a protective effect on the gut microbiome and the CNS, including whole grain, fasting, Mediterranean, and ketogenic diets. This comprehensive resource is an essential reading for patients with MS seeking to understand the potential impacts of diet on their overall health, as well as healthcare professionals and researchers interested in exploring dietary interventions for MS management.
Deep Learning Approaches for Early Diagnosis of Neurodegenerative Diseases
Author: Rodriguez, Raul Villamarin
language: en
Publisher: IGI Global
Release Date: 2024-02-14
Within the context of global health challenges posed by intractable neurodegenerative diseases like Alzheimer's and Parkinson's, the significance of early diagnosis is critical for effective intervention, and scientists continue to discover new methods of detection. However, actual diagnosis goes beyond detection to include a significant analysis of combined data for many cases, which presents a challenge of several complicated calculations. Deep Learning Approaches for Early Diagnosis of Neurodegenerative Diseases stands as a groundbreaking work at the intersection of artificial intelligence and neuroscience. The book orchestrates a symphony of cutting-edge techniques and progressions in early detection by assembling eminent experts from the domains of deep learning and neurology. Through a harmonious blend of research areas and pragmatic applications, this monumental work charts the transformative course to revolutionize the landscape of early diagnosis and management of neurodegenerative disorders. Within the pages, readers will embark through the intricate landscape of neurodegenerative diseases, the fundamental underpinnings of deep learning, the nuances of neuroimaging data acquisition and preprocessing, the alchemy of feature extraction and representation learning, and the symphony of deep learning models tailored for neurodegenerative disease diagnosis. The book also delves into integrating multimodal data to augment diagnosis, the imperative of rigorously evaluating and validating deep learning models, and the ethical considerations and challenges entwined with deep learning for neurodegenerative diseases.