AIMC Topic: Amyloid beta-Peptides

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Cerebrospinal fluid inflammatory cytokines as prognostic indicators for cognitive decline across Alzheimer's disease spectrum.

Journal of Alzheimer's disease : JAD Apr 22, 2025
BackgroundNeuroinflammation actively contributes to the pathophysiology of Alzheimer's disease (AD); however, the value of neuroinflammatory biomarkers for disease-staging or predicting disease progression remains unclear.ObjectiveTo investigate diag...
Humans Female Disease Progression Aged Cognitive Dysfunction Cytokines Amyloid beta-Peptides Aged, 80 and over Biomarkers Prognosis Male Alzheimer Disease tau Proteins
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Machine Learning Interpretation of Optical Spectroscopy Using Peak-Sensitive Logistic Regression.

ACS nano Apr 15, 2025
Optical spectroscopy, a noninvasive molecular sensing technique, offers valuable insights into material characterization, molecule identification, and biosample analysis. Despite the informativeness of high-dimensional optical spectra, their interpre...
Spectrum Analysis SARS-CoV-2 Logistic Models Support Vector Machine Principal Component Analysis Discriminant Analysis Amyloid beta-Peptides Alzheimer Disease Humans Machine Learning COVID-19 Algorithms
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Amyloid-β Deposition Prediction With Large Language Model Driven and Task-Oriented Learning of Brain Functional Networks.

IEEE transactions on medical imaging Apr 3, 2025
Amyloid- positron emission tomography can reflect the Amyloid- protein deposition in the brain and thus serves as one of the golden standards for Alzheimer's disease (AD) diagnosis. However, its practical cost and high radioactivity hinder its applic...
Female Aged Male Deep Learning Humans Brain Positron-Emission Tomography Image Interpretation, Computer-Assisted Large Language Models Magnetic Resonance Imaging Amyloid beta-Peptides Alzheimer Disease
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New approach to specific Alzheimer's disease diagnosis based on plasma biomarkers in a cognitive disorder cohort.

European journal of clinical investigation Mar 22, 2025
BACKGROUND: The validation of a combination of plasma biomarkers and demographic variables is required to establish reliable cut-offs for Alzheimer's disease diagnosis (AD).
Aged, 80 and over Sensitivity and Specificity Male Middle Aged Retrospective Studies Female Aged Alzheimer Disease Neurofilament Proteins tau Proteins Apolipoproteins E Genotype Amyloid beta-Peptides Peptide Fragments Glial Fibrillary Acidic Protein Humans Biomarkers
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Physics-informed machine learning for automatic model reduction in chemical reaction networks.

Scientific reports Mar 7, 2025
Physics-informed machine learning bridges the gap between the high fidelity of mechanistic models and the adaptive insights of artificial intelligence. In chemical reaction network modeling, this synergy proves valuable, addressing the high computati...
Amyloid beta-Peptides Kinetics Alzheimer Disease Humans Machine Learning Algorithms Computer Simulation Models, Chemical
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Sampling Conformational Ensembles of Highly Dynamic Proteins via Generative Deep Learning.

Journal of chemical information and modeling Feb 21, 2025
Proteins are inherently dynamic, and their conformational ensembles play a crucial role in biological function. Large-scale motions may govern the protein structure-function relationship, and numerous transient but stable conformations of intrinsical...
Intrinsically Disordered Proteins Protein Conformation Deep Learning Amyloid beta-Peptides Peptide Fragments Molecular Dynamics Simulation
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Predicting conversion in cognitively normal and mild cognitive impairment individuals with machine learning: Is the CSF status still relevant?

Alzheimer's & dementia : the journal of the Alzheimer's Association Jan 30, 2025
INTRODUCTION: Machine learning (ML) helps diagnose the mild cognitive impairment-Alzheimer's disease (MCI-AD) spectrum. However, ML is fed with data unavailable in standard clinical practice. Thus, we tested a novel multi-step ML approach to predict ...
Peptide Fragments Alzheimer Disease tau Proteins Neuropsychological Tests Disease Progression Cognitive Dysfunction Amyloid beta-Peptides Humans Machine Learning Female Biomarkers Aged Aged, 80 and over Male
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An unsupervised learning approach for clustering joint trajectories of Alzheimer's disease biomarkers: An application to ADNI Data.

Alzheimer's & dementia : the journal of the Alzheimer's Association Jan 27, 2025
INTRODUCTION: Current models of Alzheimer's disease (AD) progression assume a common pattern and pathology, oversimplifying the heterogeneity of clinical AD.
Alzheimer Disease Neuroimaging Cluster Analysis Unsupervised Machine Learning Amyloid beta-Peptides Female Aged Male Disease Progression Humans Biomarkers Brain
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Alzheimer's Disease: Exploring Pathophysiological Hypotheses and the Role of Machine Learning in Drug Discovery.

International journal of molecular sciences Jan 24, 2025
Alzheimer's disease (AD) is a major neurodegenerative dementia, with its complex pathophysiology challenging current treatments. Recent advancements have shifted the focus from the traditionally dominant amyloid hypothesis toward a multifactorial und...
Humans Machine Learning Animals Drug Discovery Amyloid beta-Peptides Alzheimer Disease tau Proteins
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Enhanced detection of mild cognitive impairment in Alzheimer's disease: a hybrid model integrating dual biomarkers and advanced machine learning.

BMC geriatrics Jan 23, 2025
Alzheimer's disease (AD) is a complex, progressive, and irreversible neurodegenerative disorder marked by cognitive decline and memory loss. Early diagnosis is the most effective strategy to slow the disease's progression. Mild Cognitive Impairment (...
Biomarkers Female Aged Aged, 80 and over Male Cognitive Dysfunction Magnetic Resonance Imaging Humans Machine Learning Amyloid beta-Peptides Alzheimer Disease Hippocampus
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