AIMC Topic: Mice

Clear Filters Showing 421 to 430 of 1771 articles

Unsupervised Domain Adaptation for EM Image Denoising With Invertible Networks.

IEEE transactions on medical imaging
Electron microscopy (EM) image denoising is critical for visualization and subsequent analysis. Despite the remarkable achievements of deep learning-based non-blind denoising methods, their performance drops significantly when domain shifts exist bet...

Microbial perspective of multidisciplinary collaborative weight management approach: may serve as a key target for weight loss.

Gut microbes
Changes in the gut microbiota are associated with obesity and may influence weight loss. We are currently implementing a sustained multidisciplinary collaborative weight management (MCWM) approach to weight loss. We report significant improvements in...

A data-driven approach to establishing cell motility patterns as predictors of macrophage subtypes and their relation to cell morphology.

PloS one
The motility of macrophages in response to microenvironment stimuli is a hallmark of innate immunity, where macrophages play pro-inflammatory or pro-reparatory roles depending on their activation status during wound healing. Cell size and shape have ...

Machine learning and confirmatory factor analysis show that buprenorphine alters motor and anxiety-like behaviors in male, female, and obese C57BL/6J mice.

Journal of neurophysiology
Buprenorphine is an opioid approved for medication-assisted treatment of opioid use disorder. Used off-label, buprenorphine has been reported to contribute to the clinical management of anxiety. Although human anxiety is a highly prevalent disorder, ...

Trans-m5C: A transformer-based model for predicting 5-methylcytosine (m5C) sites.

Methods (San Diego, Calif.)
5-Methylcytosine (m5C) plays a pivotal role in various RNA metabolic processes, including RNA localization, stability, and translation. Current high-throughput sequencing technologies for m5C site identification are resource-intensive in terms of cos...

Artificial intelligence-driven rational design of ionizable lipids for mRNA delivery.

Nature communications
Lipid nanoparticles (LNPs) have proven effective in mRNA delivery, as evidenced by COVID-19 vaccines. Its key ingredient, ionizable lipids, is traditionally optimized by inefficient and costly experimental screening. This study leverages artificial i...

Application of deep learning models on single-cell RNA sequencing analysis uncovers novel markers of double negative T cells.

Scientific reports
Double negative T (DNT) cells are a unique subset of CD3 + TCRαβ + T lymphocytes that lack CD4, CD8, or NK1.1 expression and constitute 3-5% of the total T cell population in C57BL/6 mice. They have increasingly gained recognition for their novel rol...

Unraveling Microplastic Effects on Gut Microbiota across Various Animals Using Machine Learning.

ACS nano
Microplastics, rapidly expanding and durable pollutant, have been shown to significantly impact gut microbiota across a spectrum of animal species. However, comprehensive analyses comparing microplastic effects on gut microbiota among these species a...

HDAC3_VS_assistant: cheminformatics-driven discovery of histone deacetylase 3 inhibitors.

Molecular diversity
Histone deacetylase 3 (HDAC3) inhibitors keep significant therapeutic promise for treating oncological, neurodegenerative, and inflammatory diseases. In this work, we developed robust QSAR regression models for HDAC3 inhibitory activity and acute tox...

Artificial intelligence-enabled discovery of a RIPK3 inhibitor with neuroprotective effects in an acute glaucoma mouse model.

Chinese medical journal
BACKGROUND: Retinal ganglion cell (RGC) death caused by acute ocular hypertension is an important characteristic of acute glaucoma. Receptor-interacting protein kinase 3 (RIPK3) that mediates necroptosis is a potential therapeutic target for RGC deat...