English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Currently, many studies of Alzheimer's disease (AD) are investigating theneurobiological factors behind the acquisition of beta-amyloid (A), pathologictau (T), and neurodegeneration ([N]) biomarkers from neuroimages. However, asystem-level mechanism of how these neuropathological burdens promoteneurodegeneration and why AD exhibits characteristic progression is largelyelusive. In this study, we combined the power of systems biology and networkneuroscience to understand the dynamic interaction and diffusion process ofAT[N] biomarkers from an unprecedented amount of longitudinal Amyloid PET scan,MRI imaging, and DTI data. Specifically, we developed a network-guidedbiochemical model to jointly (1) model the interaction of AT[N] biomarkers ateach brain region and (2) characterize their propagation pattern across thefiber pathways in the structural brain network, where the brain resilience isalso considered as a moderator of cognitive decline. Our biochemical modeloffers a greater mathematical insight to understand the physiopathologicalmechanism of AD progression by studying the system dynamics and stability.Thus, an in-depth system-level analysis allows us to gain a new understandingof how AT[N] biomarkers spread throughout the brain, capture the early sign ofcognitive decline, and predict the AD progression from the preclinical stage.

A Network-Guided Reaction-Diffusion Model of AT[N] Biomarkers in Alzheimer's Disease