AIMC Topic: Rats, Sprague-Dawley
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Phasic dopamine release identification using convolutional neural network.
Computers in biology and medicine
Sep 25, 2019
Dopamine has a major behavioral impact related to drug dependence, learning and memory functions, as well as pathologies such as schizophrenia and Parkinson's disease. Phasic release of dopamine can be measured in vivo with fast-scan cyclic voltammet...
Characterization of Nanoscale Organization of F-Actin in Morphologically Distinct Dendritic Spines Using Supervised Learning.
eNeuro
Aug 1, 2019
The cytoarchitecture of a neuron is very important in defining morphology and ultrastructure. Although there is a wealth of information on the molecular components that make and regulate these ultrastructures, there is a dearth of understanding of ho...
Dendritic computations captured by an effective point neuron model.
Proceedings of the National Academy of Sciences of the United States of America
Jul 10, 2019
Complex dendrites in general present formidable challenges to understanding neuronal information processing. To circumvent the difficulty, a prevalent viewpoint simplifies the neuronal morphology as a point representing the soma, and the excitatory a...
Raman spectroscopic histology using machine learning for nonalcoholic fatty liver disease.
FEBS letters
Jul 8, 2019
Histopathology requires the expertise of specialists to diagnose morphological features of cells and tissues. Raman imaging can provide additional biochemical information to benefit histological disease diagnosis. Using a dietary model of nonalcoholi...
Supervised Learning and Mass Spectrometry Predicts the Fate of Nanomaterials.
ACS nano
Jul 3, 2019
The surface of nanoparticles changes immediately after intravenous injection because blood proteins adsorb on the surface. How this interface changes during circulation and its impact on nanoparticle distribution within the body is not understood. He...
A deep learning based pipeline for optical coherence tomography angiography.
Journal of biophotonics
Jul 1, 2019
Optical coherence tomography angiography (OCTA) is a relatively new imaging modality that generates microvasculature map. Meanwhile, deep learning has been recently attracting considerable attention in image-to-image translation, such as image denois...
Gene Expression Data Based Deep Learning Model for Accurate Prediction of Drug-Induced Liver Injury in Advance.
Journal of chemical information and modeling
Jun 28, 2019
Drug-induced liver injury (DILI), one of the most common adverse effects, leads to drug development failure or withdrawal from the market in most cases, showing an emerging challenge that is to accurately predict DILI in the early stage. Recently, th...
Deep learning for high-throughput quantification of oligodendrocyte ensheathment at single-cell resolution.
Communications biology
Mar 26, 2019
High-throughput quantification of oligodendrocyte myelination is a challenge that, if addressed, would facilitate the development of therapeutics to promote myelin protection and repair. Here, we established a high-throughput method to assess oligode...
The Effect of the Prethanol Extract of Trifolium pratense Leaves on Interleukin-1β-Induced Cartilage Matrix Degradation in Primary Rat Chondrocytes.
Cells, tissues, organs
Jan 31, 2019
BACKGROUND: Osteoarthritis (OA) is a degenerative joint disease, characterized by cartilage degradation and inflammation. The proinflammatory cytokine, interleukin (IL)-1β, plays a crucial role in the pathogenesis of OA by inducing the release of oth...
Quantitative ultrasound and machine learning for assessment of steatohepatitis in a rat model.
European radiology
Dec 17, 2018
OBJECTIVES: To develop a machine learning model based on quantitative ultrasound (QUS) parameters to improve classification of steatohepatitis with shear wave elastography in rats by using histopathology scoring as the reference standard.
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