Zeitschriftenaufsätze

Background: Susac syndrome is a rare autoimmune endotheliopathy that affects the central nervous system, retina, and inner ear, characterized by encephalopathy, branch retinal artery occlusions, and sensorineural hearing loss. Due to the heterogeneity of its presentation, early diagnosis, and treatment remain challenging.Objective/methods: To evaluate the clinical outcomes and radiological responses in two patients with Susac syndrome treated with natalizumab in an off-label therapeutic approach, clinical assessments and serial magnetic resonance imaging (MRI) were performed over a follow-up period of up to 22 months to monitor disease progression and treatment response.Results: Both patients demonstrated clinical stabilization with reduced MRI and retinal angiography disease activity. [...]

BackgroundSerum neurofilament light chain (sNfL) is an established biomarker of disease activity and progression in persons with multiple sclerosis (PwMS), with studies showing elevated sNfL levels during relapses and positive associations with disability scores.Objective To assess sNfL levels in PwMS receiving different disease-modifying therapies (DMTs), with a particular focus on extended-interval dosing (EID) regimens in real-world clinical practice.MethodsIn this two-center cross-sectional study, 172 PwMS without relapses in the preceding three months were included (University Hospital Cologne, n = 125; University Hospital Mainz, n = 47). Patients were categorized into the following groups: (1) low-efficacy DMT (leDMT; n = 8), (2) natalizumab standard-interval dosing (SID; every 4 weeks; n = 7), (3) natalizumab EID (every 6–8 weeks; n = 53), (4) ofatumumab (n = 17), (5) ocrelizumab SID (every 6 months; n = 48), (6) ocrelizumab EID (every 9 months; n = 17), and (7) no DMT (n = 19). [...]

Substantial brain volume loss is well-documented during acute anorexia nervosa (AN); however, longitudinal outcomes are unclear. Our comprehensive meta-analysis investigated global and regional structural brain alterations in adult and adolescent individuals with AN by extracting reported brain volume scores and neuroimaging coordinates from the literature. [...]

Machine learning (ML) is transforming atmospheric chemistry, offering powerful tools to address challenges in tropospheric ozone research, a critical area for climate resilience and public health. As in adjacent fields, ML approaches complement existing research by learning patterns from ever-increasing volumes of atmospheric and environmental data relevant to ozone. [...]