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http://dx.doi.org/10.2337/dc12-1218 | DOI Listing |
Urology
January 2025
David Geffen School of Medicine at University of California, Los Angeles, CA. Electronic address:
J Diabetes Complications
December 2023
School of Medicine, Promise Department, University of Palermo, Italy; School of Medicine, Mohammed Bin Rashid University, Dubai, United Arab Emirates.
JAMA Ophthalmol
August 2024
Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston.
Importance: Anecdotal experience raised the possibility that semaglutide, a glucagon-like peptide 1 receptor agonist (GLP-1 RA) with rapidly increasing use, is associated with nonarteritic anterior ischemic optic neuropathy (NAION).
Objective: To investigate whether there is an association between semaglutide and risk of NAION.
Design, Setting, And Participants: In a retrospective matched cohort study using data from a centralized data registry of patients evaluated by neuro-ophthalmologists at 1 academic institution from December 1, 2017, through November 30, 2023, a search for International Statistical Classification of Diseases and Related Health Problems, Tenth Revision code H47.
JAMA Neurol
June 2024
Department of Neurology, Washington University School of Medicine, St Louis, Missouri.
Importance: Effects of antiamyloid agents, targeting either fibrillar or soluble monomeric amyloid peptides, on downstream biomarkers in cerebrospinal fluid (CSF) and plasma are largely unknown in dominantly inherited Alzheimer disease (DIAD).
Objective: To investigate longitudinal biomarker changes of synaptic dysfunction, neuroinflammation, and neurodegeneration in individuals with DIAD who are receiving antiamyloid treatment.
Design, Setting, And Participants: From 2012 to 2019, the Dominantly Inherited Alzheimer Network Trial Unit (DIAN-TU-001) study, a double-blind, placebo-controlled, randomized clinical trial, investigated gantenerumab and solanezumab in DIAD.
Background: The Critical Assessment of Genome Interpretation (CAGI) aims to advance the state-of-the-art for computational prediction of genetic variant impact, particularly where relevant to disease. The five complete editions of the CAGI community experiment comprised 50 challenges, in which participants made blind predictions of phenotypes from genetic data, and these were evaluated by independent assessors.
Results: Performance was particularly strong for clinical pathogenic variants, including some difficult-to-diagnose cases, and extends to interpretation of cancer-related variants.
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