Alzheimer's disease (AD), the most prevalent form of dementia, is pathologically defined by amyloid-β (Aβ) plaques, neurofibrillary tangles, synaptic loss, and progressive neuronal degeneration. Increasing evidence highlights neuroinflammation as a central and modifiable factor in AD pathogenesis. This review critically explores the roles of microglia and astrocytes in mediating neuroinflammatory cascades, emphasizing their dual protective and detrimental functions. Microglial activation and astrocytic polarization into A1 (neurotoxic) and A2 (neuroprotective) subtypes are discussed alongside their contributions to Aβ clearance, tau pathology propagation, and synaptic dysfunction. The disruption of the blood–brain barrier, activation of inflammasome pathways such as NLRP3, and release of cytokines and chemokines exacerbate chronic inflammation and neurodegeneration. Advances in single-cell transcriptomics and lipidomics have revealed glial heterogeneity and novel molecular targets, including disease-associated microglia. Genetic risk factors like apolipoprotein E ( APOE ) and TREM2 variants further modulate inflammatory responses. Emerging therapeutic strategies, including non-steroidal anti-inflammatory drugs, monoclonal antibodies, and targeted immunomodulators, hold promise for modifying disease progression. Overall, precise targeting of neuroinflammatory pathways offers a compelling avenue for future AD therapies.

Alzheimer’s disease (AD) is a chronic neurodegenerative disorder and the leading cause of dementia, primarily affecting the elderly. This review expl

Purpose: To compare the characteristics, treatment and outcomes of asymptomatic vs symptomatic patients with newly diagnosed nonvalvular atrial fibrillation (NVAF).

Background: The recommended doses for a NOAC to prevent stroke and systemic embolism (SE) in patients with non-valvular atrial fibrillation (AF) are specified in the prescribing information. Prospective observational studies provide an opportunity to evaluate whether the actual dosing of these drugs in real-life conforms with the approved dosing.

Recent advances in artificial intelligence (AI) for the diagnosis, treatment, and management of neurological disorders are revolutionizing the world of neurology. This review discusses the current state of AI in neurology in terms of enhanced diagnostic accuracy and disease monitoring, as well as new personalized strategies for diagnosis and treatment. AI-driven models analyze vast amounts of healthcare data, including genetic information and brain scans, to identify patterns and biomarkers that may be overlooked using traditional methods. Machine learning and deep learning algorithms have shown promise in predicting the onset and progression of conditions, such as epilepsy, multiple sclerosis, Parkinson’s disease, and Alzheimer’s disease. AI-based neuroimaging analysis also enables more precise characterization of brain structure, facilitating early detection and intervention. Furthermore, AI-powered tools improve patient care by enabling remote monitoring and supporting rehabilitation, thereby enhancing the quality of life of individuals with chronic neurological conditions. Despite these advancements, challenges remain, including concerns about algorithmic bias, data security, and the need for rigorous clinical validation. This paper provides a comprehensive overview of AI-driven innovations in neurology, addressing both their practical implications and ethical considerations while highlighting future research opportunities. The ultimate goal is to illustrate AI’s transformative impact on neurology, contributing to better patient outcomes and a deeper understanding of complex neurological disorders.