Biomarkers.

Background: Specific PSEN1 mutations cause early-onset AD but their effects on blood biomarker levels are unknown. We evaluated autopsy-confirmed individuals affected by six different PSEN1 mutations; two of known (L381V, C410Y) and three (A426P/E318G, M233L, and V261I) of unknown pathogenic status. The sixth patient had Autosomal Dominant AD (ADAD) not yet genotyped.

Biomarkers.

Background: Alzheimer disease (AD) related cognitive decline occurs at relatively young ages in individuals with Down syndrome (DS, early-mid 50s) and in those with autosomal dominant mutations (ADAD, 40-50s). Both groups show similar patterns of amyloid accumulation. We examined if brain volumes are similarly affected by AD pathology in individuals with DS and ADAD.

Biomarkers.

Background: Amyloid β (Aβ) deposition in the brain is a pathological hallmark of Alzheimer's disease (AD). While immunoprecipitation-mass spectrometry (IP-MS) stands out as an accurate method for quantifying blood-based Aβ peptides, its major limitations such as prolonged sample preparation, extensive analysis time, large specimen volume, and high costs, present opportunities for improvement. Consequently, we aimed to develop a novel plasma IP-MS Aβ assay that employs simplified and significantly shorter analytical procedures, along with much-reduced sample volumes.

Biomarkers.

Background: Synuclein Aggregate Assays (SAA) in cerebrospinal fluid (CSF) and in skin biopsy have been shown to successfully identify underlying synuclein (Lewy body) pathology in patients with Parkinson's disease. Data in Lewy Body Dementia (LBD) is limited, particularly with pathologic confirmation and staging of underlying Lewy body pathology, and other co-pathologies.

Method: Utilizing data and biofluids from participants in the U.

Pharmacists' perceptions of artificial intelligence: A national survey.

Background: Artificial intelligence (AI) is a rapidly growing and evolving field impacting pharmacy research, education, and professional practice. The development and adaptation of AI technologies have the potential to radically shape the future of the pharmacy profession. However, it remains unclear how aware pharmacists are of these technologies or their perceptions regarding current and future utilization.