AIMC Topic: Mice

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Application of a metabolic network-based graph neural network for the identification of toxicant-induced perturbations.

Toxicological sciences : an official journal of the Society of Toxicology
Transcriptomic analyses have been an effective approach to investigate the biological responses and metabolic perturbations by environmental contaminants in rodent models. However, it is well recognized that metabolic networks are highly connected an...

Identification and designing an analgesic opioid cyclic peptide from Defensin 4 of Mesobuthus martensii Karsch scorpion venom with more effectiveness than morphine.

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie
Considering the limitations of use and side effects of existing analgesics, the discovery of new analgesics is necessary. Venoms of organisms are an important source of analgesic peptides. In this study, using computational biology methods such as mo...

MACHINE LEARNING AND BIOINFORMATICS TO IDENTIFY COAGULATION BIOMARKERS IN SEPSIS-RELATED KIDNEY INJURY.

Shock (Augusta, Ga.)
Background: Sepsis-associated acute kidney injury (SA-AKI) is a life-threatening complication with mortality rates exceeding 50%, yet its molecular drivers remain poorly defined. Dysregulated coagulation is increasingly implicated in SA-AKI pathogene...

Accelerated EPR imaging using deep learning denoising.

Magnetic resonance in medicine
PURPOSE: Trityl OXO71-based pulse electron paramagnetic resonance imaging (EPRI) is an excellent technique to obtain partial pressure of oxygen (pO) maps in tissues. In this study, we used deep learning techniques to denoise 3D EPR amplitude and pO m...

Identification of potential biomarkers in cardiovascular calcification based on bioinformatics combined with single-cell RNA-seq and multiple machine learning analysis.

Cellular signalling
BACKGROUND: The molecular and genetic mechanisms underlying vascular calcification remain unclear. This study aimed to determine the differences in calcification marker-related gene expression in macrophages.

Hugan Tiaoshen Formula Improves the Comorbid Mechanism of Schizophrenia and Sleep Disorder via Multitarget Interaction Network.

FASEB journal : official publication of the Federation of American Societies for Experimental Biology
This study aims to integrate cross-disease omics data and perform multidimensional analysis to uncover the molecular basis of schizophrenia (SCZ) and sleep disorder (SD) comorbidity and to systematically analyze the potential mechanism of the Hugan T...

Antimicrobial peptide developed with machine learning sequence optimization targets drug resistant Staphylococcus aureus in mice.

The Journal of clinical investigation
As antimicrobial resistance rises, new antibacterial candidates are urgently needed. Using sequence space information from over 14,743 functional antimicrobial peptides (AMPs), we improved the antimicrobial properties of citropin 1.1, an AMP with wea...

Unveiling the systemic impact of airborne microplastics: Integrating breathomics and machine learning with dual-tissue transcriptomics.

Journal of hazardous materials
Airborne microplastics (MPs) pose significant respiratory and systemic health risks upon inhalation; however, current assessment methods remain inadequate. This study integrates breathomics and transcriptomics to establish a non-invasive approach for...

Multiplexing and Sensing with Fluorescence Lifetime Imaging Microscopy Empowered by Phasor U-Net.

Analytical chemistry
Fluorescence lifetime imaging microscopy (FLIM) has been widely used as an essential multiplexing and sensing tool in frontier fields such as materials science and life sciences. However, the accuracy of lifetime estimation is compromised by limited ...

AI Quantification of Vascular Lesions in Mouse Fundus Fluorescein Angiography.

Translational vision science & technology
PURPOSE: Quantifying vascular leakage in fundus fluorescein angiography (FFA) is a critical endpoint in preclinical models of diseases such as neovascular age-related macular degeneration, retinopathy of prematurity, and diabetic retinopathy. Traditi...