Dementia

From Structure to Selectivity: Integrating CADD and AIDD in Rational Medicinal Chemistry Strategies for DYRK1A Inhibitor Discovery.

Dual specificity tyrosine phosphorylation-regulated kinase 1A (DYRK1A), a member of the CMGC kinase family, regulates diverse cellular processes and is implicated in Alzheimer's disease, Down syndrome, cancer, and diabetes. However, the clinical translation of DYRK1A inhibitors remains challenging due to limited selectivity arising from the high structural conservation of the ATP-binding pocket wi...

PatientSpace: A multimodal graph-based latent representation framework for modeling neurodegenerative disease heterogeneity.

Neurodegenerative diseases such as Alzheimer's disease (AD) and frontotemporal dementia (FTD) exhibit substantial biological and clinical heterogeneity, complicating diagnosis, subtype characterization, and prediction of disease progression. We introduce PatientSpace, a multimodal graph-based latent representation framework designed to model neurodegenerative disease heterogeneity using T1-weighte...

Multimodal molecular mapping of the vasculature in human cortex reveals lipid markers of cerebral amyloid angiopathy.

Cerebral amyloid angiopathy (CAA) commonly co-occurs with Alzheimer's disease (AD), yet the molecular changes that accompany vascular [Formula: see te...

The Science of Preventing Delirium: Trends, Knowledge Gaps, and Future Directions Revealed Through Bibliometric Insights.

PURPOSE: To examine global research trends in delirium prevention through a bibliometric analysis and provide a structured overview of its development...

Associations Between Interoception and Sensory Processing in Preschool Children.

This study examined how caregiver-reported interoceptive functioning relates to caregiver-reported sensory processing characteristics in typically dev...

Machine learning for predicting full-count FDG PET brain images from low-count acquisitions in suspected dementia: a clinical and quantitative evaluation.

Objective.Artificial intelligence methods for denoising low-count FDG PET brain images are usually evaluated using image quality metrics alone, with l...

Mapping Artificial Intelligence Applications in Dementia Caregiving: A Scoping Review of Technologies, Functions, and Evidence Gaps.

PURPOSE: As symptoms progress in people with Alzheimer's disease and related dementias (ADRD), caregivers assume increasing responsibility. The object...

Deep Model Families for EEG-Based Multi-Class Dementia Classification.

Deep learning (DL) has shown considerable promise for EEG-based dementia assessment; however, rigorous cross-family comparisons under leakage-free and...

Identifying sex-specific sub-phenotypes of Alzheimer's disease progression using longitudinal electronic health records.

BACKGROUND: Alzheimer's Disease (AD) is a complex neurodegenerative disorder, with women comprising nearly two-thirds of individuals with AD. However,...

Network-based discovery of regulatory drivers of cognitive decline in alzheimer's disease.

Alzheimer's disease (AD) is a multifactorial neurodegenerative disorder marked by progressive cognitive decline, yet its transcriptional regulatory ar...

Leveraging Advanced AI Frameworks for Dual PPAR α/γ Agonist Discovery in Alzheimer's Disease.

The dual activating potential of peroxisome proliferator-activated receptors (PPAR) α and γ offers a promising way to address metabolic issues, neuroi...

Feasibility Assessment of an Intelligent Agent to Assist Preserving Healthy Hearing.

Hearing loss is a rising health concern. The World Health Organization estimates that over 1.5 billion people worldwide are currently experiencing hea...

Amyloid-like nanofilm-decorated antifouling field effect transistor biosensor array for enhancing Alzheimer's disease diagnosis.

Alzheimer's disease (AD) is a common neurodegenerative disorder. Compared to the limited specificity of single-biomarker detection, the combined detec...

Interactions between minimal amount of exercise and low-density lipoprotein cholesterol on incident dementia after stroke.

Cognitive impairment often follows stroke. Regular physical activity has been shown to be associated with reduced dementia risk, while the association...

Interpretable machine learning models predict cognitive impairment in adults aged 50 and over with diabetes: influence of dietary nutrients.

Introduction: diabetes mellitus increases the risk of cognitive impairment, but the role of dietary nutrients remains unclear. Objectives: to develop ...

Patient- and Caregiver-Informed Considerations for the Design and Implementation of Generative AI-Supported Patient-Centered Clinical Decision Support: Qualitative Study.

BACKGROUND: Generative artificial intelligence (AI) has the potential to impact health care by transforming workflows and improving outcomes. Patient-...

User Acceptability and Adoption of AI-Generated Lifestyle Intervention Recommendations: Scoping Review and Theoretical Integration.

BACKGROUND: Artificial intelligence (AI)-generated lifestyle recommendations are increasingly used to support health behavior change. However, AI advi...

Nonverbal AI-Based Communication Robot for Staff in Disaster-Affected Care Facilities: Exploratory ABAB Intervention Study.

BACKGROUND: Medical and welfare facilities in the Noto region of Japan were severely affected by the 2024 Noto Peninsula earthquake and subsequent tor...

How Correct is AI for Infant Safe Sleep Advice? Evaluating Accuracy of ChatGPT, Gemini, and Claude Against AAP Guidelines.

OBJECTIVE: Since the 1994 "Back to Sleep" campaign, pediatricians have promoted evidence-based infant safe sleep practices to reduce sleep-related inf...

Estimating blood-brain barrier exchange rate using diffusion-weighted arterial spin labeling and physics-guided neural networks.

This study proposes physics-guided neural network (PgNN) approaches for estimating perfusion and blood-brain barrier (BBB) water permeability paramete...