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Women's reproductive factors predict local brain aging profiles mapped using deep neural networks
Deep neural networks (DNNs) trained on magnetic resonance images can estimate global brain age (GBA), which reflects women's neurological disease risk. GBA gap (GBAG), the difference between GBA and chronological age (CA), quantifies excessive global aging; local BAG (LBAG) has not been examined despite allowing voxelwise resolution. Using a novel DNN architecture, we estimate LBAG for 12,284 UK Biobank females with chronological ages (CAs) ranging between 46 and 82 years (y) and quantify how it...
Behavioral deficits and exacerbated neural and hemodynamic odor responses during lifespan of a mouse model of late onset Alzheimer's disease expressing humanized APOEepsilon4 and Trem2*R47H
Alzheimer's disease (AD) poses a significant global health challenge, being the most prominent cause of dementia with prevalence increasing as the population ages. While the majority of AD cases are late-onset (LOAD), current animal models predominantly represent the more aggressive, faster progressing early-onset AD (EOAD), limiting their ability in assessing early biomarkers and gaining deeper understanding of LOAD progression. This study explores a promising translatable model, the...