Alzheimer's Disease

Circulatory dietary and gut-derived metabolites predict early cognitive decline.

INTRODUCTION: A key component of disease prevention is the identification of at-risk individuals. Microbial dysbiosis in the early stages of cognitive decline and Alzheimer's disease (AD) and can modulate the levels of microbe-derived metabolites (MDM), thought to contribute to neuroinflammation, blood‒brain barrier dysfunction, and neuronal degeneration. However, the precise role of MDM in this p...

Quantitative pathology and APOE genotype reveal dementia risk and progression in Lewy body disease.

Dementia in Lewy body diseases (LBD) is common and arises through heterogeneous and incompletely understood pathways. Evidence suggests contributions from genetic factors, including APOE ε4 genotype, co-pathology including concomitant Alzheimer's disease pathology and hypoperfusion related to orthostatic hypotension. However, the relative impact of these factors remains unclear. To address this, w...

The Deep Learning Revolution in Neuroimaging: Insights from a Bibliometric Analysis (2014-2024).

This paper presents a bibliometric analysis of the fast-growing area of deep learning in neuroimaging. Using data from the Scopus database, we analyze...

Toward ultimate NMR resolution with deep learning.

Resolution in NMR is defined as the ability to distinguish and accurately determine signal positions while mitigating overlap. In the pursuit of ultim...

Closed-loop transcranial ultrasound stimulation based on NREM and REM sleep for bidirectional modulation of sleep neural oscillation and memory.

Sleep plays an important role in memory integration. Closed-loop physical stimulation during rapid eye movement (REM) or non-rapid eye movement (NREM)...

Reappraising cardiac function with myocardial contraction fraction: normal values, disease detection, and prognostication.

AIMS: Assessing cardiac function is critical for managing cardiovascular disease, guiding treatment, monitoring progression, and risk stratification. ...

Parvalbumin Neuron-Targeted Loss of Alzheimer's Disease Risk Gene BIN1 Is Insufficient to Drive Cognitive or Network Excitability Changes.

Bridging integrator 1 (BIN1) is one of the strongest genetic risk factors for Alzheimer's disease (AD), yet its function in the brain and role in AD r...

A machine learning approach using echocardiographic and hematological parameters to classify cerebral small vessel disease burden.

BACKGROUND: Cerebral small vessel disease (CSVD) is a leading cause of stroke and dementia and is associated with cardiac and hematological biomarkers...

Screening for Alzheimer's disease in the community using an AI-driven screening platform: design of the PREDICTOM study.

BACKGROUND: Recent developments in physiological, imaging and digital biomarkers combined with the approval of new disease-modifying drugs against Alz...

Addressing disparities in transthyretin amyloid cardiomyopathy: A systematic review of artificial intelligence in the early identification to improve patient outcomes.

BACKGROUND: Transthyretin amyloid cardiomyopathy (ATTR-CM) remains substantially underdiagnosed among Black patient populations. When applied to non-i...

Corrigendum to "Enhancing dementia risk prediction with heart rate and machine learning in the Canadian Longitudinal Study on Aging".

Enriched resting-state EEG prediction of cognitive decline in prodromal Alzheimer's disease: a machine-learning approach.

OBJECTIVE: We evaluated the accuracy of standard machine learning (ML) algorithms in predicting 1-year cognitive decline in Alzheimer's disease patien...

Machine-learning approach on echocardiography to improve the detection of transthyretin amyloid cardiomyopathy: GRAAL algorithm.

AIMS: Transthyretin amyloid cardiomyopathy (ATTR-CM) is an increasingly recognized cause of heart failure, yet detection remains challenging due to it...

Ultrastructural Evidence of Altered Dendritic Morphology in the Prefrontal Cortex of Alzheimer's Model Rats.

Alzheimer's disease (AD) is a neurodegenerative disorder with synaptic pathology as a core theme in aging-related research. Conventional imaging and l...

Multimodal AI for Alzheimer Disease Diagnosis: Systematic Review of Datasets, Models, and Modalities.

BACKGROUND: Early detection of Alzheimer disease (AD) is essential for timely intervention; yet, diagnostic performance varies widely across modalitie...

Research on Alzheimer's Disease Risk Assessment Models and Biomarker Screening Based on Bioinformatics Analysis and Machine Learning Algorithms.

INTRODUCTION: Alzheimer's Disease (AD) is among the most prevalent neurodegenerative disorders globally, yet effective early diagnostic strategies rem...

Emerging Roles of Small-molecule Derivatives in Modulating Neurodegenerative Pathways: From Molecular Targets to Therapeutic Applications.

Neurodegenerative disorders such as Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and Huntington's disease involve progress...

Reimagining Brain Drug Delivery: Mechanistic and Translational Advances in Carbon Nanotube Nanomedicine.

Neurological and neurodegenerative disorders (NDDs) present ongoing therapeutic challenges attributed to the structural complexity of the central nerv...

Multimodal biomarker AI techniques for early neurocognitive disorder diagnosis: A systematic review.

BACKGROUND: Early diagnosis of Alzheimer's disease (AD) and related dementias remains challenging because no single biomarker sufficiently captures th...

Molecular mechanisms of exercise-induced improvements in Alzheimer's disease: a focus on lipid homeostasis.

Alzheimer's disease (AD) is the most prevalent type of dementia, and its pathophysiological mechanisms involve multiple factors, including genomic fac...