Alzheimer's Disease

Machine Learning-Driven Bioprospecting of Cholinergic Medicinal Plants for Putative Leads Against Butyrylcholinesterase Towards Alzheimer's Care.

Butyrylcholinesterase (BChE) plays a key role in preserving appropriate cholinergic neurotransmission that is essentially altered in the brains of advanced Alzheimer's disease (AD), hence a therapeutic target. This study employed a machine learning (ML) bioactivity predictive model to explore the chemical space of potential BChE inhibitors. A cheminformatics pipeline was explored to create a ML mo...

Gut microbiota and blood biomarkers as correlating factors in patients with postoperative delirium: analysis of three prospective observational studies.

Postoperative delirium is associated with both gut microbiota alterations and Tau phosphorylation; however, how these factors interact and jointly contribute to postoperative delirium remains poorly understood. This prospective observational cohort study screened 491 patients aged ≥65 years undergoing elective laminectomy or hip or knee replacement under general or spinal anesthesia at Massachuset...

The impact of frailty and its changes on the development of motoric cognitive risk syndrome in middle-aged and older adults.

BACKGROUND: Previous research links frailty to cognitive decline, but the relationship between frailty and motoric cognitive risk syndrome (MCR), a de...

Early Retinal UCHL1 Dysregulation Coupled With Synaptic Loss Reflects Alzheimer's Disease Severity.

Synaptic dysfunction is a major driver of cognitive decline in Alzheimer's disease (AD), yet its extent and molecular basis in the retina remain poorl...

Machine-Learning-Assisted Impedance Component Analysis Enables Standardizable Surface Protein Analysis of Extracellular Vesicles Using Engineered Nanovesicles.

Characterizing surface protein heterogeneity on extracellular vesicles remains challenging but essential for understanding their biological functions ...

Machine Learning-Driven Risk Prediction Model in Transthyretin Amyloid Cardiomyopathy.

IMPORTANCE: Transthyretin cardiac amyloidosis (ATTR-CM) is associated with poor prognosis and significant morbidity and mortality, yet existing stagin...

Electrocardiogram-Based Deep Learning to Prioritize Testing for Transthyretin Amyloid Cardiomyopathy.

IMPORTANCE: Transthyretin amyloid cardiomyopathy (ATTR-CM) is a treatable cause of heart failure, but diagnosis is often delayed. Accessible tools to ...

Infection with Western equine encephalitis virus causes severe regional glial reactivity and neurodegeneration in the hippocampus with progressive accumulation of amyloid-β.

Encephalitic alphaviruses such as Western equine encephalitis virus (WEEV) result in significant morbidity through acute viremia and postencephalitic ...

Learning precise segmentation of neurofibrillary tangles from rapid manual point annotations.

Accumulation of abnormal tau protein into neurofibrillary tangles (NFTs) is a pathologic hallmark of Alzheimer disease (AD). Accurate detection of NFT...

Innovations in dementia education in health sciences: curriculum design and partnerships across three countries.

As dementia prevalence rises globally, health sciences education must evolve to prepare future professionals across disciplines to provide person-cent...

Artificial Intelligence Chatbots and Large Language Models for Traumatic Dental Injury Management and Decision Support: A Systematic Review With Function-Based Narrative Synthesis and Exploratory Meta-Analysis.

Traumatic dental injuries require rapid, accurate, and context-sensitive decisions, particularly during emergencies such as tooth avulsion, luxation i...

A comparative study of vision transformer architectures for the detection of Alzheimer's disease using magnetic resonance images.

Alzheimer's disease is a neurodegenerative disease that affects millions of people worldwide. With the increasing global elderly population, early and...

Dementia Etiology Diagnosis via Collaborative Meta Knowledge Enhancement.

Although artificial intelligence (AI) has shown promising performance in several medical tasks, accurate dementia etiology diagnosis with AI remains c...

Deep learning-derived magnetic resonance imaging masseter muscle volume is associated with oral impairment and cognitive frailty in older Japanese adults.

BACKGROUND AND OBJECTIVES: The masseter muscle is associated with oral impairment and age-related functional decline, yet scalable and objective indic...

Manifold representation learning for Alzheimer's disease detection with EEG-based functional brain connectivity.

Alzheimer's disease (AD) is a common neurodegenerative disease characterized by severe cognitive dysfunctions and brain disorders. The emergence of de...

Explainable 3D deep learning from full-head MRI suggests scalp and skull involvement in Alzheimer's disease.

BackgroundEmerging evidence suggests that extracranial tissues and immune-glymphatic interactions may contribute to neurodegenerative processes in Alz...

Demographic Confounding in Voice-Based Parkinson Disease Screening: Methodological Analysis of the Bridge2AI Voice Dataset.

BACKGROUND: Voice-based deep learning models for Parkinson disease (PD) and dementia screening report areas under the curve (AUCs) of 0.85-0.97, but r...

Performance of Two AI Approaches in ASReview Compared With Manual Screening for Dementia Care Literature Screening: Comparative Analysis.

BACKGROUND: Literature reviews rely on rigorous title and abstract screening by researchers, which is time-consuming. AI-assisted literature screening...

SCRIB is a Shared Transcriptomic Biomarker Candidate Linking Cardioembolic Stroke and Alzheimer's Disease.

Acute ischemic stroke is a major cause of death and disability, and post-stroke cognitive impairment remains a major clinical challenge. Cardioembolic...

Carboxyl-terminal blockade of sortilin binding enhances progranulin gene therapy in a mouse model of frontotemporal dementia.

Frontotemporal dementia is commonly caused by loss-of-function mutations in the progranulin gene. Potential therapies for this disorder have entered c...