AIMC Topic: Disease Models, Animal
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Potential diagnostic biomarkers in heart failure: Suppressed immune-associated genes identified by bioinformatic analysis and machine learning.
European journal of pharmacology
Nov 23, 2024
Heart failure (HF) threatens tens of millions of people's health worldwide, which is the terminal stage in the development of majority cardiovascular diseases. Recently, an increasing number of studies have demonstrated that bioinformatics and machin...
Magnetic soft microrobots for erectile dysfunction therapy.
Proceedings of the National Academy of Sciences of the United States of America
Nov 18, 2024
Erectile dysfunction (ED) is a major threat to male fertility and quality of life, and mesenchymal stromal cells (MSCs) are a promising therapeutic option. However, therapeutic outcomes are compromised by low MSC retention and survival rates in corpu...
Comprehensive analysis and validation of TP73 as a biomarker for calcium oxalate nephrolithiasis using machine learning and in vivo and in vitro experiments.
Urolithiasis
Nov 16, 2024
Calcium oxalate (CaOx) nephrolithiasis constitutes approximately 75% of nephrolithiasis cases, resulting from the supersaturation and deposition of CaOx crystals in renal tissues. Despite their prevalence, precise biomarkers for CaOx nephrolithiasis ...
Brain imaging and machine learning reveal uncoupled functional network for contextual threat memory in long sepsis.
Scientific reports
Nov 12, 2024
Positron emission tomography (PET) utilizes radiotracers like [F]fluorodeoxyglucose (FDG) to measure brain activity in health and disease. Performing behavioral tasks between the FDG injection and the PET scan allows the FDG signal to reflect task-re...
Interpretable machine learning uncovers epithelial transcriptional rewiring and a role for Gelsolin in COPD.
JCI insight
Nov 8, 2024
Transcriptomic analyses have advanced the understanding of complex disease pathophysiology including chronic obstructive pulmonary disease (COPD). However, identifying relevant biologic causative factors has been limited by the integration of high di...
Automated acute skin toxicity scoring in a mouse model through deep learning.
Radiation and environmental biophysics
Nov 6, 2024
This study presents a novel approach to skin toxicity assessment in preclinical radiotherapy trials through an advanced imaging setup and deep learning. Skin reactions, commonly associated with undesirable side effects in radiotherapy, were meticulou...
Machine learning accelerates the discovery of epitope-based dual-bioactive peptides against skin infections.
International journal of antimicrobial agents
Oct 31, 2024
OBJECTIVES: Skin injuries and infections are an inevitable part of daily human life, particularly with chronic wounds, becoming an increasing socioeconomic burden. In treating skin infections and promoting wound healing, bioactive peptides may hold s...
Machine learning approach to assess brain metastatic burden in preclinical models.
Methods in cell biology
Oct 29, 2024
Brain metastases (BrM) occur when malignant cells spread from a primary tumor located in other parts of the body to the brain. BrM is a deadly complication for cancer patients and severely lacks effective therapies. Due to the limited access to patie...
Characterization of Brain Abnormalities in Lactational Neurodevelopmental Poly I:C Rat Model of Schizophrenia and Depression Using Machine-Learning and Quantitative MRI.
Journal of magnetic resonance imaging : JMRI
Oct 28, 2024
BACKGROUND: A recent neurodevelopmental rat model, utilizing lactational exposure to polyriboinosinic-polyribocytidilic acid (Poly I:C) leads to mimics of behavioral phenotypes resembling schizophrenia-like symptoms in male offspring and depression-l...
Machine learning reveals prominent spontaneous behavioral changes and treatment efficacy in humanized and transgenic Alzheimer's disease models.
Cell reports
Oct 19, 2024
Computer-vision and machine-learning (ML) approaches are being developed to provide scalable, unbiased, and sensitive methods to assess mouse behavior. Here, we used the ML-based variational animal motion embedding (VAME) segmentation platform to ass...
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