Latin America (LATAM) is a diverse region with more than 30 countries, each varying in cultural, economic, and social aspects. While multiple sclerosis (MS) care in LATAM has improved, there are still challenges to address. Epidemiologic studies have shown varying incidence rates of MS in the region, influenced by factors such as genetics, environmental conditions, and regional diversity. Scientific research on MS in LATAM has increased, with publications and consensus guidelines emerging. However, access to disease-modifying treatments remains a significant challenge in many countries due to affordability issues and limited availability of certain therapies. The region also faces obstacles in providing comprehensive MS care, including rehabilitation programs and diagnosis tools. There are collaborative efforts and initiatives in LATAM that are working toward overcoming these challenges and improving the overall quality of care for people with MS in the region.
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http://dx.doi.org/10.7224/1537-2073.2024-085 | DOI Listing |
Int J MS Care
December 2024
Clinica Colombia, Hospital San Jose, Bogotá, Colombia.
Latin America (LATAM) is a diverse region with more than 30 countries, each varying in cultural, economic, and social aspects. While multiple sclerosis (MS) care in LATAM has improved, there are still challenges to address. Epidemiologic studies have shown varying incidence rates of MS in the region, influenced by factors such as genetics, environmental conditions, and regional diversity.
View Article and Find Full Text PDFTob Induc Dis
March 2025
Department of Anatomy and Neurobiology, Xiangya School of Basic Medical Sciences, Central South University, Changsha, China.
Introduction: Tobacco use is as a major public health concern around the world, adversely impacting quality of life. Our study aims to analyze the trends in the burden of tobacco-related neurological disorders (ND) at global, regional, and national levels from 1990 to 2021, as well as potential future trends.
Methods: We performed a secondary dataset analysis for the assessment of mortality and disability-adjusted life years (DALYs) using data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021, to explore the burden of tobacco-related ND.
Nutrients
March 2025
Lymphatic Vasculature and Inflammation Research Laboratory, Instituto de Ciencias Biomédicas, Facultad de Ciencias de la Salud, Universidad Autónoma de Chile, Talca 3467987, Chile.
In Latin America, yerba mate (YM) is a popular infusion processed from the leaves and stems of . YM has been shown to have anti-inflammatory properties in several studies, although the effect of YM on multiple sclerosis (MS) remains elusive. The purpose of this study was to examine the effect of YM on the development of MS, by using the experimental autoimmune encephalomyelitis (EAE) mouse model while also evaluating its effect over infiltration of immune cells into the central nervous system (CNS) and regulatory T cell (Treg) function.
View Article and Find Full Text PDFInt J Mol Sci
February 2025
Neuroimmunology Group, Department of Medicine, University of Lleida-IRBLleida, 25198 Lleida, Spain.
Multiple sclerosis (MS) is characterized by demyelination and neuroinflammation, with oxidative stress playing a pivotal role in lesion pathology. This study aimed to investigate the differential cellular responses to myelin debris under varying oxidative states. Myelin oxidation was induced using a Cu-peroxide system, confirmed by elevated TBARS levels and autofluorescence.
View Article and Find Full Text PDFInt J Mol Sci
February 2025
Centre for Human Technologies, Istituto Italiano di Tecnologia, Via Enrico Melen, 83, 16152 Genova, Italy.
Complex diseases pose challenges in prediction due to their multifactorial and polygenic nature. This study employed machine learning (ML) to analyze genomic data from the UK Biobank, aiming to predict the genomic predisposition to complex diseases like multiple sclerosis (MS) and Alzheimer's disease (AD). We tested logistic regression (LR), ensemble tree methods, and deep learning models for this purpose.
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