About
Multiple Sclerosis (MS) is a complex, chronic neurological condition that affects the central nervous system, primarily the brain and spinal cord. Characterized by immune-mediated attacks on the protective myelin sheath covering nerve fibers, MS disrupts communication between the brain and the body, leading to a wide range of physical, cognitive, and emotional symptoms. This multifaceted disease manifests differently in each individual, making its diagnosis and management a significant challenge for healthcare providers.
Advancements in research and treatment have transformed the landscape of MS care, offering hope to patients through improved diagnostic tools, disease-modifying therapies, and rehabilitative strategies. MS is at the forefront of neuroimmunology, driving innovations in understanding autoimmune processes and neuroprotection. Collaborative efforts across neurology, physiotherapy, and mental health disciplines are essential in empowering individuals living with MS to maintain quality of life and functional independence.
Why publish with us?
Global Visibility – Indexed in major databases
Fast Peer Review – Decision within 14–21 days
Open Access – Maximize readership and citation
Multidisciplinary Scope – Biology, Medicine and Engineering
Editorial Board Excellence – Global experts involved
University Library Indexing – Via OCLC
Permanent Archiving – CrossRef DOI
APC – Affordable APCs with discounts
Citation – High Citation Potential
Which articles are now trending?
Research Articles
- Clinical MLOps: A Framework for Responsible Deployment and Observability of AI Systems in Cloud-Native Healthcare
- Efficacy of Alternative Insecticides against Dusky Cotton Bug (Oxycarenus laetus) to Improve Yield Losses in Cotton Crops through Residue-based Bioassay
- Abrasive Wear in Some High Fe-Cr-C Alloy in Cement Powder
- Designing a Compact High-precision Positioner with Large Stroke Capability for Nanoindentation Devices
- Unraveling Cognitive Aging: A Comprehensive Narrative Review of the Seattle Longitudinal Study and Recent Breakthroughs
- Clustering of Three-dimensional (3-D) Objects by Means of Phase- only Digital Holographic Information using Machine Learning
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