AIMC Topic: Amyloid beta-Peptides

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Inferring Parameters of Pyramidal Neuron Excitability in Mouse Models of Alzheimer's Disease Using Biophysical Modeling and Deep Learning.

Bulletin of mathematical biology
Alzheimer's disease (AD) is believed to occur when abnormal amounts of the proteins amyloid beta and tau aggregate in the brain, resulting in a progressive loss of neuronal function. Hippocampal neurons in transgenic mice with amyloidopathy or tauopa...

Surface-functionalized SERS platform for deep learning-assisted diagnosis of Alzheimer's disease.

Biosensors & bioelectronics
Early diagnosis of Alzheimer's disease is crucial to stall the deterioration of brain function, but conventional diagnostic methods require complicated analytical procedures or inflict acute pain on the patient. Then, label-free Surface-enhanced Rama...

Artificial Intelligence Assistive Software Tool for Automated Detection and Quantification of Amyloid-Related Imaging Abnormalities.

JAMA network open
IMPORTANCE: Amyloid-related imaging abnormalities (ARIA) are brain magnetic resonance imaging (MRI) findings associated with the use of amyloid-β-directed monoclonal antibody therapies in Alzheimer disease (AD). ARIA monitoring is important to inform...

Aggregation-induced electrochemiluminescence enhancement of Ag-MOG for amyloid β 42 sensing.

Analytica chimica acta
This study aimed to introduce an immunosensor for measuring amyloid β 42 (Aβ) levels by aggregation-induced enhanced electrochemiluminescence (ECL). Metal-organic gels (MOGs) are novel soft materials with advantages such as high gel stability, good l...

Metastable alpha-rich and beta-rich conformations of small Aβ42 peptide oligomers.

Proteins
Probing the structures of amyloid-β (Aβ) peptides in the early steps of aggregation is extremely difficult experimentally and computationally. Yet, this knowledge is extremely important as small oligomers are the most toxic species. Experiments and s...

A unique color-coded visualization system with multimodal information fusion and deep learning in a longitudinal study of Alzheimer's disease.

Artificial intelligence in medicine
PURPOSE: Automated diagnosis and prognosis of Alzheimer's Disease remain a challenging problem that machine learning (ML) techniques have attempted to resolve in the last decade. This study introduces a first-of-its-kind color-coded visualization mec...

A deep learning model for detection of Alzheimer's disease based on retinal photographs: a retrospective, multicentre case-control study.

The Lancet. Digital health
BACKGROUND: There is no simple model to screen for Alzheimer's disease, partly because the diagnosis of Alzheimer's disease itself is complex-typically involving expensive and sometimes invasive tests not commonly available outside highly specialised...

Interpretable deep learning of myelin histopathology in age-related cognitive impairment.

Acta neuropathologica communications
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
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...