AIMC Topic: Mice

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iDIA-QC: AI-empowered data-independent acquisition mass spectrometry-based quality control.

Nature communications Jan 21, 2025
Quality control (QC) in mass spectrometry (MS)-based proteomics is mainly based on data-dependent acquisition (DDA) analysis of standard samples. Here, we collect 2754 files acquired by data independent acquisition (DIA) and paired 2638 DDA files fro...
Artificial Intelligence Tandem Mass Spectrometry Mice Software Quality Control Proteomics Animals Mass Spectrometry Liver Chromatography, Liquid
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Genomic and algorithm-based predictive risk assessment models for benzene exposure.

Frontiers in public health Jan 21, 2025
AIM: In this research, we leveraged bioinformatics and machine learning to pinpoint key risk genes associated with occupational benzene exposure and to construct genomic and algorithm-based predictive risk assessment models.
Benzene Occupational Exposure Animals Genomics Risk Assessment Humans Mice Machine Learning Algorithms
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Efficient recognition of Parkinson's disease mice on stepping characters with CNN.

Scientific reports Jan 20, 2025
Parkinson's disease (PD), as the second most prevalent neurodegenerative disorder worldwide, impacts the quality of life for over 12 million patients. This study aims to enhance the accuracy of early diagnosis of PD through non-invasive methods, with...
Animals Image Processing, Computer-Assisted Mice Parkinson Disease Early Diagnosis Disease Models, Animal Mice, Inbred C57BL Neural Networks, Computer Algorithms
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Analyzing the relationship between gene expression and phenotype in space-flown mice using a causal inference machine learning ensemble.

Scientific reports Jan 18, 2025
Spaceflight has several detrimental effects on human and rodent health. For example, liver dysfunction is a common phenotype observed in space-flown rodents, and this dysfunction is partially reflected in transcriptomic changes. Studies linking trans...
Gene Expression Profiling Transcriptome Mice Machine Learning Phenotype Animals Liver Space Flight
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Explainable deep learning and virtual evolution identifies antimicrobial peptides with activity against multidrug-resistant human pathogens.

Nature microbiology Jan 17, 2025
Artificial intelligence (AI) is a promising approach to identify new antimicrobial compounds in diverse microbial species. Here we developed an AI-based, explainable deep learning model, EvoGradient, that predicts the potency of antimicrobial peptide...
Mice Klebsiella pneumoniae Bacteria Enterococcus faecium Antimicrobial Peptides Escherichia coli Acinetobacter baumannii Deep Learning Microbial Sensitivity Tests Humans Drug Resistance, Multiple, Bacterial Anti-Bacterial Agents Animals
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Biologically relevant integration of transcriptomics profiles from cancer cell lines, patient-derived xenografts, and clinical tumors using deep learning.

Science advances Jan 17, 2025
Cell lines and patient-derived xenografts are essential to cancer research; however, the results derived from such models often lack clinical translatability, as they do not fully recapitulate the complex cancer biology. Identifying preclinical model...
Animals Neoplasms Gene Expression Profiling Transcriptome Humans Gene Expression Regulation, Neoplastic Xenograft Model Antitumor Assays Heterografts Deep Learning Cell Line, Tumor Mice
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Opioid growth factor receptor overexpression exerts anti-hepatocellular carcinoma effects by activating P16 and P21 to inhibit proliferation and migration of HepG2 cells.

Folia histochemica et cytobiologica Jan 13, 2025
INTRODUCTION: Hepatocellular carcinoma (HCC) is the sixth most common type of cancer and the second leading cause of cancer death worldwide [19]. Opioid growth factor (OGF) has been shown to exhibit antitumour potential, binding to OGF receptor (OGFr...
Hep G2 Cells Cell Movement Mice, Nude Male Cyclin-Dependent Kinase Inhibitor p16 Carcinoma, Hepatocellular Liver Neoplasms Apoptosis Humans Mice Mice, Inbred BALB C Animals Cell Proliferation Cyclin-Dependent Kinase Inhibitor p21 Receptors, Opioid
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Machine Learning-Assisted High-Throughput Screening of Nanozymes for Ulcerative Colitis.

Advanced materials (Deerfield Beach, Fla.) Jan 12, 2025
Ulcerative colitis (UC) is a chronic gastrointestinal inflammatory disorder with rising prevalence. Due to the recurrent and difficult-to-treat nature of UC symptoms, current pharmacological treatments fail to meet patients' expectations. This study ...
Reactive Oxygen Species Colitis, Ulcerative High-Throughput Screening Assays Humans Gastrointestinal Microbiome Mice Machine Learning Apoptosis Antioxidants Animals
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Diagnostic Accuracy of Ambient Mass Spectrometry with Blood Plasma in a Murine Glioma Model Using Machine Learning.

World neurosurgery Jan 9, 2025
OBJECTIVE: Malignant glioma progresses rapidly and shows poor prognosis, but clinically applicable blood plasma-based biochemical tumor markers remain lacking. This study aimed to develop a diagnostic system using probe electrospray ionization mass s...
Machine Learning Biomarkers, Tumor Brain Neoplasms Glioma Mice, Inbred C57BL Animals Male Disease Models, Animal Spectrometry, Mass, Electrospray Ionization Cell Line, Tumor Mice
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ULM-MbCNRT: In Vivo Ultrafast Ultrasound Localization Microscopy by Combining Multibranch CNN and Recursive Transformer.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control Jan 8, 2025
Ultrasound localization microscopy (ULM) overcomes the acoustic diffraction limit by localizing tiny microbubbles (MBs), thus enabling the microvascular to be rendered at subwavelength resolution. Nevertheless, to obtain such superior spatial resolut...
Phantoms, Imaging Microscopy, Acoustic Neural Networks, Computer Algorithms Image Processing, Computer-Assisted Animals Mice Deep Learning Microbubbles Ultrasonography
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