AIMC Topic: Alzheimer Disease

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Detection of brain network abnormalities by graph invariants in Alzheimer's disease using MRI images.

Scientific reports
Alzheimer's disease is a major cause of dementia in older adults. It involves gradual changes in brain function that result in cognitive decline, affecting memory, reasoning, and executive skills. The accurate detection of structural abnormalities in...

Identification and validation of PANoptosis-related biomarkers in Alzheimer's disease via single-cell RNA sequencing and machine learning.

European journal of medical research
BACKGROUND: Alzheimer's disease (AD) is a progressive neurodegenerative disorder with complex underlying mechanisms. PANoptosis, a newly defined form of programmed cell death that integrates pyroptosis, apoptosis, and necroptosis, may play a crucial ...

Association of blood-based DNA methylation of lncRNAs with Alzheimer's disease diagnosis.

Clinical epigenetics
BACKGROUND: DNA methylation has shown great potential in Alzheimer's disease (AD) blood diagnosis. However, the ability of long non-coding RNAs (lncRNAs), which can be modified by DNA methylation, to serve as noninvasive biomarkers for AD diagnosis r...

Association Between Choroid Plexus Morphological Alterations, Alzheimer Pathologies, and Cognitive Impairment: A Longitudinal Study.

Neurology
BACKGROUND AND OBJECTIVES: The choroid plexus (ChP) plays a crucial role in maintaining brain health. Alzheimer disease (AD) pathologies may damage the ChP and accelerate neurodegeneration. Previous imaging studies have found overall increased ChP vo...

AI-driven discovery of dual antiaging and anti-AD therapeutics via PROTAC target deconvolution of a super-enhancer-regulated axis.

Science advances
The lack of safe, durable therapeutics that act against both biological aging and Alzheimer's disease is an unmet clinical need. To bridge this gap, we devised an artificial intelligence (AI)-enabled approach that pairs rapid compound triage with mec...

Universal black-box attacks against a third-party Alzheimer's diagnostic system.

Biomedical physics & engineering express
Artificial intelligence (AI) systems are increasingly used in medical imaging for disease diagnosis, yet their vulnerability to adversarial attacks poses significant risks for clinical deployment. In this work, we systematically evaluate the suscepti...

A novel approach integrating topological deep learning from EEG Data in Alzheimer's disease.

Scientific reports
High-throughput analysis of EEG data has significantly contributed to understanding neural dynamics in Alzheimer's disease diagnosis. However, the complexity and high dimensionality of EEG signals pose challenges for traditional classification method...

Ultrasensitive SERS-LFA for the detection of neurofilament light chain and machine learning-assisted Alzheimer's disease classification.

Nanoscale
Neurofilament light chain (NfL), a cytoskeletal protein released during neuronal injury, is a promising biomarker, with elevated levels consistently associated with disease severity and progression in multiple neurological conditions, including Alzhe...

Dual-Channel Multiscale Graph Transformer with Adversarial Contrastive Learning and Low-Rank Disentangled Stratified Negative Sampling for Drug Repositioning.

Journal of chemical information and modeling
Drug repositioning accelerates therapeutic discovery, but existing computational methods are hampered by representation collapse, noisy supervision, and suboptimal negative sampling. To address these limitations, we introduce MGTAL-DR, a novel graph ...

Machine Learning-Based Bioactivity Prediction and Descriptor-Guided Rational Design of Amyloid-β Aggregation Inhibitors.

ACS chemical neuroscience
Alzheimer's disease (AD) is a progressive neurodegenerative disorder in which amyloid-β (Aβ) aggregation plays a pivotal role in its onset and progression. Inhibiting Aβ aggregation is a promising therapeutic strategy; however, its intrinsically diso...