We developed a machine learning framework grounded in a computational model of brain function and FDG-PET imaging to predict Alzheimer’s disease (AD)-type tau across AD and related disorders (ADRD). The model was trained on 1088 research participants spanning normal aging and ADRD with FDG-PET and flortaucipir-PET...
Nick Corriveau-Lecavalier, Ge-Meng Zhang, H. Botha et al.· Nature Communications· 0 citations
Anterior opercular syndrome (Foix-Chavany-Marie syndrome) is characterized by severe dysarthria, impaired voluntary orofacial and pharyngolingual movements, and preserved automatic or emotional movements (automatic-voluntary dissociation). Although classically associated with stroke, its progressive neurodegenerative f...
Hiroyuki Watanabe, Etsuro Mori, K. Josephs· Neurocase· 0 citations
TAR DNA-binding protein of 43 kDa (TDP-43) is often found in the brains of patients with Alzheimer’s disease (AD), where it co-occurs with amyloid β plaques and tau neurofibrillary tangles, and associates with accelerated cognitive decline and brain atrophy. TDP-43’s function of repressing the inclusion of cryptic exon...
Madison M. Reeves, Sara Aviles Carpintero, M. Zanovello et al.· Alzheimer's Research & Thera...· 0 citations
Background/Objectives: The role of iron in Alzheimer’s disease (AD) and frontotemporal lobar degeneration (FTLD) has been debated. However, the effects of iron on protein burden in these diseases remain poorly elucidated. We hypothesized that there is an association between iron deposition and tau and beta-amyloid depo...
Rodolfo Gabriel Gatto, Hossam Youssef, Gökhan Uruk et al.· Brain Science· 0 citations
Co‐pathologies – including Lewy body, vascular, and TDP‐43 lesions – are common in Alzheimer's disease (AD), contributing to its clinical and pathological heterogeneity. Genetic risk factors may drive mixed pathology presentation, but their influence on the development of specific co‐pathologies remains unclear.
Madison M. Reeves, Anna Calliari, Tiffany W. Todd et al.· Alzheimer's & Dementia· 0 citations
White matter microstructural disruption is a dominant imaging signature of CBS and is more closely linked to gray matter volume loss than to measurable uptake on tau PET, while dMRI, particularly MD and ICVF, may provide greatest sensitivity for detecting disease-related changes in CBS.
Yu-Qi Tian, Ryota Satoh, V. Lowe et al.· medRxiv· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
