Alzheimer's Disease

Machine learning-guided repurposing of FDA-approved quinolones as dual cholinesterase inhibitors: A multi-level docking, molecular dynamics, DFT, and SHAP-based analysis.

Alzheimer's disease (AD) involves progressive cholinergic degeneration, with acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) playing key enzymatic roles in its pathology. In this study, we computationally repurposed four FDA-approved quinolone antibiotics, Norfloxacin, Sparfloxacin, Gatifloxacin, and Nalidixic acid, as potential dual-site cholinesterase (ChE) inhibitors using a hybrid...

Neuroanatomical-based machine learning prediction of Alzheimer's Disease across sex and age.

Alzheimer's Disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline and memory loss. In 2024 it affected approximately 1 in 9 people aged 65 and older in the U.S., 6.9 million individuals. Early detection and accurate AD diagnosis are crucial for improving patient outcomes. Magnetic resonance imaging (MRI) has emerged as a valuable tool for examining brain struc...

A review of deep learning techniques in Alzheimer's disease with emphasis on data tools and transfer learning.

Alzheimer's disease (AD) is a significant neurological condition that is marked by the gradual decline of memory and cognitive function, with a higher...

Effect of a Robot Pet Companion on the Mood of Older Adults Receiving Family Caregiver Support: Pilot RCT.

BACKGROUND AND OBJECTIVES: Use of companion robot pets to reduce social isolation and loneliness in older people is well-established. Outcomes associa...

TRKM: Twin restricted kernel machines for classification and regression.

Restricted kernel machines (RKMs) have significantly advanced machine learning by integrating kernel functions with least squares support vector machi...

Transcriptomic analysis of plasma small extracellular vesicles identifies potential diagnostic biomarkers for Parkinson's disease dementia.

INTRODUCTION: Blood-based biomarkers that can aid diagnosis of Parkinson's Disease (PD) dementia (PDD), and predict PDD onset in people with PD are ur...

AlzStack: Forecasting early-onset Alzheimer's with an explainable AI system using multiple data balancing techniques.

Alzheimer's disease (AD) is a degenerative neurological disease that progresses over time, making early detection crucial for effective intervention a...

Enlarged Perivascular Spaces and Modifiable Vascular Risk Factors: Cross-Sectional and Longitudinal Analysis in the UK Biobank Cohort.

OBJECTIVE: To examine cross-sectional and longitudinal associations between vascular risk factors, APOE genotype, and perivascular spaces (PVS), with ...

Precision engineering of anti-atherosclerotic herbal nanomedicine: from machine learning-aided active components screening to optimized metal-phenolic network codelivery.

Atherosclerosis (AS), a chronic inflammatory disease linked to oxidative stress and lipid imbalance, remains a major cardiovascular threat. Traditiona...

Saccade Tasks: A Noninvasive Approach for Predicting Postoperative Delirium in Elderly Arthroplasty Patients.

BACKGROUND: Postoperative delirium (POD) is a prevalent complication in elderly surgical patients. It is associated with long-term cognitive impairmen...

Diabetes-linked metabolic dysfunction relates with distinct tau phosphorylation patterns, neuroinflammation and cognitive impairment in mouse models of Alzheimer's disease.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by amyloid-β plaques and tau neurofibrillary tangles, with tau path...

The evolving landscape of screening, management and treatment strategies of aortic stenosis in ATTR amyloidosis.

Transthyretin amyloid cardiomyopathy (ATTR-CM) and aortic stenosis (AS) frequently coexist in elderly patients, particularly men, creating a complex c...

Impact of disease-modifying therapy on [99mTc]Tc-DPD SPECT/CT markers in transthyretin cardiac amyloidosis enabled by artificial intelligence.

PURPOSE: Transthyretin cardiac amyloidosis (ATTR-CM) is a progressive, underdiagnosed disease with high morbidity and mortality. While disease-modifyi...

A Causal Validation augmented Temporal Convolutional Framework for Brain Effective Connectivity Networks Estimation.

Advancements in neuroimaging have facilitated unprecedented insights into brain connectivity, making the study of brain effective connectivity network...

QENNA: A quantum-enhanced neural network for early Alzheimer's detection using magnetic resonance imaging.

Early detection of Alzheimer's disease (AD) is essential for effective clinical intervention and disease management. However, conventional Deep Learni...

Delineating white matter phenotypes of sensori-/psychomotor functioning in large-scale cohorts of healthy individuals and patients with mental disorders across the lifespan (whiteSPAN): rationale and methods of an interdisciplinary bicentric project.

Aberrant sensori-/psychomotor functioning-including muscular hand weakness, sedentary behavior, psychomotor agitation, slowing, agitation, apathy, and...

Occupational Exposure to Welding Fumes Associated With Pulmonary Surfactant Lipid Compositional Changes, Inflammatory Activity, and Pulmonary Functioning.

OBJECTIVE: This study aimed to investigate alterations in the respiratory tract lining fluid phospholipids and their association with pulmonary functi...

Mortality prediction among older people in primary care: a comparison of predictive performance of the frailty index with regression-based and machine learning models.

INTRODUCTION: The frailty index is widely used to identify vulnerable individuals at risk of adverse outcomes like mortality. However, its predictive ...

Bridging the Hearing Divide: Policy Solutions for Aging Americans.

Hearing loss affects approximately two thirds of adults in the United States aged 70 years or older and frequently remains untreated despite its well-...

Utility of Baseline Pathological, Neuroimaging and Clinical Markers for Prognosis in Early Parkinson's Disease.

BackgroundCurrently, prognosis of Parkinson's Disease (PD) is limited. Emerging literature highlights potential of multi-modal biomarkers and neuroima...