AIMC Topic: Mice

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Identification of key diagnostic and prognostic biomarkers for aortic valve stenosis with coronary artery disease through immunological profiling integrating proteomics, single-cell sequencing, and machine learning.

Biochemical and biophysical research communications
BACKGROUND: Aortic valve stenosis with coronary artery disease (AS-CAD) represents a common yet complex cardiovascular comorbidity, characterized by multifactorial pathogenesis and a lack of specific serum biomarkers. These limitations hinder early d...

Whole-genome sequencing reveals individual and cohort level insights into chromosome 9p syndromes.

Genome medicine
BACKGROUND: Previous genomic efforts on chromosome 9p deletion and duplication syndromes have utilized low-resolution strategies (i.e., karyotypes, chromosome microarrays). These studies have provided important initial insights into these syndromes. ...

Real-time self-supervised denoising for high-speed fluorescence neural imaging.

Nature communications
Self-supervised denoising methods significantly enhance the signal-to-noise ratio in fluorescence neural imaging, yet real-time solutions remain scarce in high-speed applications. Here, we present the FrAme-multiplexed SpatioTemporal learning strateg...

Integrated experimental, computational and machine learning approaches for the development of Apremilast-Aceclofenac coamorphous systems.

International journal of pharmaceutics
Understanding the molecular mechanisms of drug coamorphization remains a key challenge in solid-state pharmaceutics. This study presents a molecular level strategy for designing drug-drug coamorphous systems (CAMs) of apremilast (APR) and aceclofenac...

A multistep platform identifies spleen-tropic lipid nanoparticles for in vivo T cell-targeted delivery of gene-editing proteins.

Science advances
Lipid nanoparticles (LNPs) are a promising nonviral delivery system for gene-editing proteins, but optimal formulations remain underexplored. Unlike messenger RNA-based approaches, ribonucleoprotein delivery enables immediate genome editing without r...

Establishment of an Infrared-Camera-Based Home-Cage Tracking System Goblotrop.

eNeuro
Studying locomotor activity in animal models is crucial for understanding physiological, behavioral, and pathological processes. This study aimed to develop an artificial intelligence-based tracking system called Goblotrop, designed to localize roden...

Machine learning and multi-omics integration reveal TRPV2 as a central regulator in bicuspid aortic valve calcification.

Biochemical and biophysical research communications
BACKGROUND: Bicuspid aortic valve (BAV), the most common congenital heart defect, is strongly predisposed to early calcification, yet the molecular drivers remain poorly defined. This study aims to identify the functional role of transient receptor p...

Descattering and image restoration with a transformer-based neural network in deep tissue imaging.

Proceedings of the National Academy of Sciences of the United States of America
Imaging biological structures deep inside tissues is crucial but challenging due to common light scattering. This study proposes a multiattention network that directly maps degraded scattering two-photon excitation fluorescence (TPEF) images to high-...

Cell Decoder: decoding cell identity with multi-scale explainable deep learning.

Genome biology
BACKGROUND: Cells are the fundamental units of life, and understanding their diversity and functionality requires detailed characterization. The rise of single-cell omics data enables this, yet current deep learning approaches lack multi-scale interp...

A machine learning framework for classifying lipids in untargeted metabolomics using mass-to-charge ratios and retention times.

Metabolomics : Official journal of the Metabolomic Society
INTRODUCTION: The identification of unknown metabolites remains a major challenge in untargeted metabolomics using liquid chromatography-mass spectrometry (LC-MS). This process typically depends on comparing mass spectral or chromatographic data to r...