AIMC Topic: Amyloid beta-Peptides
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Interpretable deep learning of myelin histopathology in age-related cognitive impairment.
Acta neuropathologica communications
Sep 21, 2022
Age-related cognitive impairment is multifactorial, with numerous underlying and frequently co-morbid pathological correlates. Amyloid beta (Aβ) plays a major role in Alzheimer's type age-related cognitive impairment, in addition to other etiopatholo...
Mapping the association between tau-PET and Aβ-amyloid-PET using deep learning.
Scientific reports
Aug 30, 2022
In Alzheimer's disease, the molecular pathogenesis of the extracellular Aβ-amyloid (Aβ) instigation of intracellular tau accumulation is poorly understood. We employed a high-resolution PET scanner, with low detection thresholds, to examine the Aβ-ta...
A combination model of AD biomarkers revealed by machine learning precisely predicts Alzheimer's dementia: China Aging and Neurodegenerative Initiative (CANDI) study.
Alzheimer's & dementia : the journal of the Alzheimer's Association
Jun 6, 2022
INTRODUCTION: To test the utility of the "A/T/N" system in the Chinese population, we study core Alzheimer's disease (AD) biomarkers in a newly established Chinese cohort.
Validation of deep learning-based nonspecific estimates for amyloid burden quantification with longitudinal data.
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Jun 2, 2022
PURPOSE: To validate our previously proposed method of quantifying amyloid-beta (Aβ) load using nonspecific (NS) estimates generated with convolutional neural networks (CNNs) using [F]Florbetapir scans from longitudinal and multicenter ADNI data.
Deep-Learning-Assisted Stratification of Amyloid Beta Mutants Using Drying Droplet Patterns.
Advanced materials (Deerfield Beach, Fla.)
May 4, 2022
The development of simple and accurate methods to predict mutations in proteins remains an unsolved challenge in modern biochemistry. It is discovered that critical information about primary and secondary peptide structures can be inferred from the s...
Deep learning from multiple experts improves identification of amyloid neuropathologies.
Acta neuropathologica communications
Apr 28, 2022
Pathologists can label pathologies differently, making it challenging to yield consistent assessments in the absence of one ground truth. To address this problem, we present a deep learning (DL) approach that draws on a cohort of experts, weighs each...
Single-molecule fluorescence imaging and deep learning reveal highly heterogeneous aggregation of amyloid-β 42.
Proceedings of the National Academy of Sciences of the United States of America
Mar 15, 2022
Polymorphism in the structure of amyloid fibrils suggests the existence of many different assembly pathways. Characterization of this heterogeneity is the key to understanding the aggregation mechanism and toxicity, but in practice it is extremely di...
Machine Learning-Assisted Pattern Recognition of Amyloid Beta Aggregates with Fluorescent Conjugated Polymers and Graphite Oxide Electrostatic Complexes.
Analytical chemistry
Jan 27, 2022
Five fluorescent positively charged poly(-aryleneethynylene) (-) were designed to construct electrostatic complexes - with negatively charged graphene oxide (). The fluorescence of conjugated polymers was quenched by the quencher . Three electrostati...
Predictive value of ATN biomarker profiles in estimating disease progression in Alzheimer's disease dementia.
Alzheimer's & dementia : the journal of the Alzheimer's Association
Nov 10, 2021
We aimed to evaluate the value of ATN biomarker classification system (amyloid beta [A], pathologic tau [T], and neurodegeneration [N]) for predicting conversion from mild cognitive impairment (MCI) to dementia. In a sample of people with MCI (n = 41...
Increasing the confidence of F-Florbetaben PET interpretations: Machine learning quantitative approximation.
Revista espanola de medicina nuclear e imagen molecular
Apr 21, 2021
AIM: To assess the added value of semiquantitative parameters on the visual assessment and to study the patterns of F-Florbetaben brain deposition.
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