AIMC Topic: Mice
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Machine learning framework develops neutrophil extracellular traps model for clinical outcome and immunotherapy response in lung adenocarcinoma.
Apoptosis : an international journal on programmed cell death
Mar 22, 2024
Neutrophil extracellular traps (NETs) are novel inflammatory cell death in neutrophils. Emerging studies demonstrated NETs contributed to cancer progression and metastases in multiple ways. This study intends to provide a prognostic NETs signature an...
Robotic Actuation-Mediated Quantitative Mechanogenetics for Noninvasive and On-Demand Cancer Therapy.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Mar 21, 2024
Cell mechanotransduction signals are important targets for physical therapy. However, current physiotherapy heavily relies on ultrasound, which is generated by high-power equipment or amplified by auxiliary drugs, potentially causing undesired side e...
Utilizing machine learning to identify nifuroxazide as an inhibitor of ubiquitin-specific protease 21 in a drug repositioning strategy.
Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie
Mar 21, 2024
Ubiquitin-specific protease (USP), an enzyme catalyzing protein deubiquitination, is involved in biological processes related to metabolic disorders and cancer proliferation. We focused on constructing predictive models tailored to unveil compounds b...
Artificial intelligence-driven drug repositioning uncovers efavirenz as a modulator of α-synuclein propagation: Implications in Parkinson's disease.
Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie
Mar 20, 2024
Parkinson's disease (PD) is a complex neurodegenerative disorder with an unclear etiology. Despite significant research efforts, developing disease-modifying treatments for PD remains a major unmet medical need. Notably, drug repositioning is becomin...
In Silico Prediction of Oral Acute Rodent Toxicity Using Consensus Machine Learning.
Journal of chemical information and modeling
Mar 18, 2024
Acute oral toxicity (AOT) is required for the classification and labeling of chemicals according to the global harmonized system (GHS). Acute oral toxicity studies are optimized to minimize the use of animals. However, with the advent of the three p...
Enhancing Multi-species Liver Microsomal Stability Prediction through Artificial Intelligence.
Journal of chemical information and modeling
Mar 18, 2024
Liver microsomal stability, a crucial aspect of metabolic stability, significantly impacts practical drug discovery. However, current models for predicting liver microsomal stability are based on limited molecular information from a single species. T...
Deep Learning Powered Identification of Differentiated Early Mesoderm Cells from Pluripotent Stem Cells.
Cells
Mar 18, 2024
Pluripotent stem cells can be differentiated into all three germ-layers including ecto-, endo-, and mesoderm in vitro. However, the early identification and rapid characterization of each germ-layer in response to chemical and physical induction of d...
Deep-learning-based super-resolution for accelerating chemical exchange saturation transfer MRI.
NMR in biomedicine
Mar 15, 2024
Chemical exchange saturation transfer (CEST) MRI is a molecular imaging tool that provides physiological information about tissues, making it an invaluable tool for disease diagnosis and guided treatment. Its clinical application requires the acquisi...
In Vivo Intelligent Fluorescence Endo-Microscopy by Varifocal Meta-Device and Deep Learning.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Mar 15, 2024
Endo-microscopy is crucial for real-time 3D visualization of internal tissues and subcellular structures. Conventional methods rely on axial movement of optical components for precise focus adjustment, limiting miniaturization and complicating proced...
NuInsSeg: A fully annotated dataset for nuclei instance segmentation in H&E-stained histological images.
Scientific data
Mar 14, 2024
In computational pathology, automatic nuclei instance segmentation plays an essential role in whole slide image analysis. While many computerized approaches have been proposed for this task, supervised deep learning (DL) methods have shown superior s...
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