Enhancing home-based physical activity for neurodivergent children: adapting the program with AI and universal design.

Purpose: While it is common practice for schools across the United States to include neurodivergent children in physical education classes, many programs outside of school-such as those at home or in the community-are not effectively tailored to meet their support needs. This gap contributes to lower levels of physical activity among neurodivergent children. Our objective was to address this issue by systematically adapting the program to enable neurodivergent children to safely engage in physical activity at home.

Characterizing substructure via mixture modeling in large-scale genetic summary statistics.

Genetic summary data are broadly accessible and highly useful, including for risk prediction, causal inference, fine mapping, and incorporation of external controls. However, collapsing individual-level data into summary data, such as allele frequencies, masks intra- and inter-sample heterogeneity, leading to confounding, reduced power, and bias. Ultimately, unaccounted-for substructure limits summary data usability, especially for understudied or admixed populations.

Virginia Memory Project: Using the Healthy Brain Initiative Roadmap to design a statewide dementia registry.

Introduction: The Virginia Memory Project (VMP) is a statewide epidemiological registry for Alzheimer's disease and related disorders (ADRD) and other neurodegenerative conditions. It aims to support dementia research, policy, and care by leveraging the Centers for Disease Control (CDC) Healthy Brain Initiative (HBI) Roadmap.

Methods: To capture comprehensive data, the VMP integrates self-enrollment and automatic enrollment using Virginia's All-Payer Claims Database (APCD).