AIMC Topic: Mice
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CPHNet: a novel pipeline for anti-HAPE drug screening via deep learning-based Cell Painting scoring.
Respiratory research
Mar 8, 2025
BACKGROUND: High altitude pulmonary edema (HAPE) poses a significant medical challenge to individuals ascending rapidly to high altitudes. Hypoxia-induced cellular morphological changes in the alveolar-capillary barrier such as mitochondrial structur...
Yi-qi-yang-yin decoction ameliorates diabetic retinopathy: New and comprehensive evidence from network pharmacology, machine learning, molecular docking and molecular biology experiment.
Journal of pharmaceutical and biomedical analysis
Mar 6, 2025
Yi-Qi-Yang-Yin Decoction (YQYY), a traditional Chinese medicine (TCM) formula, has been used to treat diabetic retinopathy (DR), yet its precise mechanisms of action remain poorly understood. In this study, two distinct diabetic models, namely sponta...
Diabetic Retinopathy
Machine Learning
Diabetes Mellitus, Type 2
Mice
Drugs, Chinese Herbal
Rats
Diabetes Mellitus, Experimental
Signal Transduction
Chromatography, High Pressure Liquid
Animals
Medicine, Chinese Traditional
Network Pharmacology
Rats, Sprague-Dawley
Male
Mice, Inbred C57BL
Molecular Docking Simulation
EVlncRNA-net: A dual-channel deep learning approach for accurate prediction of experimentally validated lncRNAs.
International journal of biological macromolecules
Mar 6, 2025
Long non-coding RNAs (lncRNAs) play key roles in numerous biological processes and are associated with various human diseases. High-throughput RNA sequencing (HTlncRNAs) has identified tens of thousands of lncRNAs across species, but only a small fra...
Involvement of disulfidptosis in the pathophysiology of autism spectrum disorder.
Life sciences
Mar 5, 2025
Autism Spectrum Disorder (ASD) is a complex neurodevelopmental disorder, with oxidative stress recognized as a key pathogenic mechanisms. Oxidative stress disrupts intracellular dynamic- thiol/disulfide homeostasis (DTDH), potentially leading to disu...
Deep Learning Enhanced Near Infrared-II Imaging and Image-Guided Small Interfering Ribonucleic Acid Therapy of Ischemic Stroke.
ACS nano
Mar 5, 2025
Small interfering RNA (siRNA) targeting the NOD-like receptor family pyrin domain-containing 3 (NLRP3) inflammasome has emerged as a promising therapeutic strategy to mitigate infarct volume and brain injury following ischemic stroke. However, the cl...
Predicting inflammatory response of biomimetic nanofibre scaffolds for tissue regeneration using machine learning and graph theory.
Journal of materials chemistry. B
Mar 5, 2025
Tissue regeneration after a wound occurs through three main overlapping and interrelated stages namely inflammatory, proliferative, and remodelling phases, respectively. The inflammatory phase is key for successful tissue reconstruction and triggers ...
An antibody developability triaging pipeline exploiting protein language models.
mAbs
Mar 4, 2025
Therapeutic monoclonal antibodies (mAbs) are a successful class of biologic drugs that are frequently selected from phage display libraries and transgenic mice that produce fully human antibodies. However, binding affinity to the correct epitope is n...
Logic-based machine learning predicts how escitalopram attenuates cardiomyocyte hypertrophy.
Proceedings of the National Academy of Sciences of the United States of America
Mar 4, 2025
Cardiomyocyte hypertrophy is a key clinical predictor of heart failure. High-throughput and AI-driven screens have the potential to identify drugs and downstream pathways that modulate cardiomyocyte hypertrophy. Here, we developed LogiRx, a logic-bas...
Machine learning-assisted design of immunomodulatory lipid nanoparticles for delivery of mRNA to repolarize hyperactivated microglia.
Drug delivery
Mar 3, 2025
Regulating inflammatory microglia presents a promising strategy for treating neurodegenerative and autoimmune disorders, yet effective therapeutic agents delivery to these cells remains a challenge. This study investigates modified lipid nanoparticle...
SeizyML: An Application for Semi-Automated Seizure Detection Using Interpretable Machine Learning Models.
Neuroinformatics
Mar 3, 2025
Despite the vast number of publications reporting seizures and the reliance of the field on accurate seizure detection, there is a lack of open-source software tools in the scientific community for automating seizure detection based on electrographic...
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