Purpose: To explore the contributions of fundus autofluorescence (FAF) topographic imaging features to the performance of convolutional neural network-based deep learning (DL) algorithms in predicting geographic atrophy (GA) growth rate.
Methods: Retrospective study with data from study eyes from three clinical trials (NCT02247479, NCT02247531, NCT02479386) in GA. The algorithm was initially trained with full FAF images, and its performance was considered benchmark.
Introduction: Further evidence is needed to support the use of plasma amyloid β (Aβ) biomarkers as Alzheimer's disease prescreening tools. This study evaluated the clinical performance and robustness of plasma Aβ /Aβ for amyloid positivity prescreening.
Methods: Data were collected from 333 BioFINDER and 121 Alzheimer's Disease Neuroimaging Initiative study participants.
The original version of this article unfortunately contained a mistake. A few entries were incorrect in Table 2.
View Article and Find Full Text PDFBackground And Objective: Current pain therapies often do not provide adequate pain relief and have dose-limiting adverse effects. Genetic evidence indicates that Na1.7 sodium channels are required for pain transduction and therefore represent an important therapeutic target.
View Article and Find Full Text PDFBackground: We investigated the effect of crenezumab, a humanized anti-amyloid-beta (Aβ) immunoglobulin (Ig)G4 monoclonal antibody, on biomarkers of amyloid pathology, neurodegeneration, and disease progression in patients with mild-to-moderate Alzheimer's disease (AD).
Methods: This double-blind, placebo-controlled, randomized phase II study enrolled patients with mild-to-moderate AD and a Mini-Mental State Examination (MMSE) score of 18-26. In part 1 of the study, patients were 2:1 randomized to receive low-dose subcutaneous (SC) 300 mg crenezumab every 2 weeks (q2w) or placebo for 68 weeks; in part 2, patients were 2:1 randomized to receive high-dose intravenous (IV) 15 mg/kg crenezumab every 4 weeks (q4w) or placebo for 68 weeks.