Zeitschriftenaufsätze

Introduction:Adolescents exhibit high rates of suicide attempts but comparatively low rates of suicides. While many studies focus on suicide attempts, it is unclear if findings apply to suicides. [...]

Background:Multiple sclerosis (MS) is influenced by age-related brain alterations and affects cellular aging mechanisms. Machine-learning models can estimate brain-predicted age from magnetic resonance imaging (MRI) to quantify these aging-related changes.Objectives:This study examines whether the difference between predicted and chronological age (BrainAGE) relates to clinical disability and biomarkers of neuro-axonal injury in MS.Design:This study analyzed brain-predicted age from structural 3D T1-weighted MRI in 82 patients with relapsing MS enrolled in three prospective clinical trials and 30 healthy controls.Methods:BrainAGE, calculated as MRI-predicted minus chronological age, was correlated with the Expanded Disability Status Scale (EDSS), MS Functional Composite subtests, and serum neurofilament light chain and glial fibrillary acidic protein..

Characterized by recurrent fluctuations in mood states, bipolar disorder (BD) is widely conceptualized as a disconnection syndrome associated with dysregulated brain dynamics. Nevertheless, the molecular mechanisms underlying this aberrant connectivity dynamics in BD remain elusive. [...]