AIMC Topic: Mice

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Unsupervised adversarial neural network for enhancing vasculature in photoacoustic tomography images using optical coherence tomography angiography.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Aug 28, 2024
Photoacoustic tomography (PAT) is a powerful imaging modality for visualizing tissue physiology and exogenous contrast agents. However, PAT faces challenges in visualizing deep-seated vascular structures due to light scattering, absorption, and reduc...
Animals Mice Unsupervised Machine Learning Neural Networks, Computer Pregnancy Tomography, Optical Coherence Female Angiography Photoacoustic Techniques
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Constraint based Bayesian optimization of bioink precursor: a machine learning framework.

Biofabrication Aug 28, 2024
Current research practice for optimizing bioink involves exhaustive experimentation with multi-material composition for determining the printability, shape fidelity and biocompatibility. Predicting bioink properties can be beneficial to the research ...
Bayes Theorem Bioprinting Viscosity Ink Machine Learning Animals Mice
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Dynamic changes in pyroptosis following spinal cord injury and the identification of crucial molecular signatures through machine learning and single-cell sequencing.

Journal of pharmaceutical and biomedical analysis Aug 26, 2024
The pathological cascade of spinal cord injury (SCI) is highly intricate. The onset of neuroinflammation can exacerbate the extent of damage. Pyroptosis is a form of inflammation-linked programmed cell death (PCD), the inhibition of pyroptosis can pa...
Mice, Inbred C57BL Single-Cell Analysis Cell Line Mice Neuroinflammatory Diseases Disease Models, Animal Spinal Cord Machine Learning Spinal Cord Injuries Microglia Animals Pyroptosis Male
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Discovery of AMPs from random peptides via deep learning-based model and biological activity validation.

European journal of medicinal chemistry Aug 26, 2024
The ample peptide field is the best source for discovering clinically available novel antimicrobial peptides (AMPs) to address emerging drug resistance. However, discovering novel AMPs is complex and expensive, representing a major challenge. Recent ...
Structure-Activity Relationship Staphylococcal Infections Hemolysis Humans Antimicrobial Peptides Anti-Bacterial Agents Animals Mice Drug Discovery Peptides Staphylococcus aureus Deep Learning Dose-Response Relationship, Drug Microbial Sensitivity Tests
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Identification of key immune-related genes and potential therapeutic drugs in diabetic nephropathy based on machine learning algorithms.

BMC medical genomics Aug 26, 2024
BACKGROUND: Diabetic nephropathy (DN) is a major contributor to chronic kidney disease. This study aims to identify immune biomarkers and potential therapeutic drugs in DN.
Mice Diabetic Nephropathies RGS Proteins Humans Machine Learning Molecular Docking Simulation Gene Expression Profiling Algorithms Animals
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The development of machine learning approaches in two-dimensional NMR data interpretation for metabolomics applications.

Analytical biochemistry Aug 24, 2024
Metabolomics has been widely applied in human diseases and environmental science to study the systematic changes of metabolites over diverse types of stimuli. NMR-based metabolomics has been widely used, but the peak overlap problems in the one-dimen...
Feces Mice Metabolomics Magnetic Resonance Spectroscopy Least-Squares Analysis Discriminant Analysis Neural Networks, Computer Machine Learning Animals
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Machine learning approaches to detect hepatocyte chromatin alterations from iron oxide nanoparticle exposure.

Scientific reports Aug 23, 2024
This study focuses on developing machine learning models to detect subtle alterations in hepatocyte chromatin organization due to Iron (II, III) oxide nanoparticle exposure, hypothesizing that exposure will significantly alter chromatin texture. A to...
Magnetic Iron Oxide Nanoparticles Hepatocytes Ferric Compounds Chromatin Machine Learning Male Mice Animals Liver
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aiSEGcell: User-friendly deep learning-based segmentation of nuclei in transmitted light images.

PLoS computational biology Aug 23, 2024
Segmentation is required to quantify cellular structures in microscopic images. This typically requires their fluorescent labeling. Convolutional neural networks (CNNs) can detect these structures also in only transmitted light images. This eliminate...
Mice Neural Networks, Computer Computational Biology Animals Software Humans Deep Learning Cell Nucleus Image Processing, Computer-Assisted
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Using machine learning to dissect host kinases required for Leishmania internalization and development.

Molecular and biochemical parasitology Aug 22, 2024
The Leishmania life cycle alternates between promastigotes, found in the sandfly, and amastigotes, found in mammals. When an infected sandfly bites a host, promastigotes are engulfed by phagocytes (i.e., neutrophils, dendritic cells, and macrophages)...
Mice Protein-Tyrosine Kinases Phagocytosis Machine Learning Macrophages Animals Leishmania Host-Parasite Interactions Proto-Oncogene Proteins c-abl src-Family Kinases Protein Kinase Inhibitors Receptors, IgG Leishmaniasis Humans Leishmania mexicana
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MLS-Net: An Automatic Sleep Stage Classifier Utilizing Multimodal Physiological Signals in Mice.

Biosensors Aug 22, 2024
Over the past decades, feature-based statistical machine learning and deep neural networks have been extensively utilized for automatic sleep stage classification (ASSC). Feature-based approaches offer clear insights into sleep characteristics and re...
Machine Learning Algorithms Neural Networks, Computer Sleep Stages Electroencephalography Animals Signal Processing, Computer-Assisted Eye Movements Electromyography Mice
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