AIMC Topic: Hepatocytes

Clear Filters Showing 21 to 30 of 31 articles

Construction and characterization of recombinant adenovirus carrying a mouse TIGIT-GFP gene.

Genetics and molecular research : GMR
Recombinant adenovirus vector systems have been used extensively in protein research and gene therapy. However, the construction and characterization of recombinant adenovirus is a tedious and time-consuming process. TIGIT is a recently discovered im...

Quantifying co-cultured cell phenotypes in high-throughput using pixel-based classification.

Methods (San Diego, Calif.)
Biologists increasingly use co-culture systems in which two or more cell types are grown in cell culture together in order to better model cells' native microenvironments. Co-cultures are often required for cell survival or proliferation, or to maint...

Computational assignment of cell-cycle stage from single-cell transcriptome data.

Methods (San Diego, Calif.)
The transcriptome of single cells can reveal important information about cellular states and heterogeneity within populations of cells. Recently, single-cell RNA-sequencing has facilitated expression profiling of large numbers of single cells in para...

Predicting in vitro assays related to liver function using probabilistic machine learning.

Toxicology
While machine learning has gained traction in toxicological assessments, the limited data availability requires the quantification of uncertainty of in silico predictions for reliable decision-making. This study addresses the challenge of predicting ...

Machine Learning on Toxicogenomic Data Reveals a Strong Association Between the Induction of Drug-Metabolizing Enzymes and Centrilobular Hepatocyte Hypertrophy in Rats.

International journal of molecular sciences
Centrilobular hepatocyte hypertrophy is frequently observed in animal studies for chemical safety assessment. Although its toxicological significance and precise mechanism remain unknown, it is considered an adaptive response resulting from the induc...

A deep learning model trained on expressed transcripts across different tissue types reveals cell-type codon-optimization preferences.

Nucleic acids research
Species-specific differences in protein translation can affect the design of protein-based drugs. Consequently, efficient expression of recombinant proteins often requires codon optimization. Publicly available optimization tools do not always result...

Artificial Intelligence Supports Automated Characterization of Differentiated Human Pluripotent Stem Cells.

Stem cells (Dayton, Ohio)
Revolutionary advances in AI and deep learning in recent years have resulted in an upsurge of papers exploring applications within the biomedical field. Within stem cell research, promising results have been reported from analyses of microscopy image...

Diagnosis of focal liver lesions with deep learning-based multi-channel analysis of hepatocyte-specific contrast-enhanced magnetic resonance imaging.

World journal of gastroenterology
BACKGROUND: The nature of input data is an essential factor when training neural networks. Research concerning magnetic resonance imaging (MRI)-based diagnosis of liver tumors using deep learning has been rapidly advancing. Still, evidence to support...

[Effect of porcine small intestinal submucosa extracellular matrix in promoting vitality and functional gene expression of hepatocyte].

Zhongguo xiu fu chong jian wai ke za zhi = Zhongguo xiufu chongjian waike zazhi = Chinese journal of reparative and reconstructive surgery
OBJECTIVE: To investigate the effect of porcine small intestinal submucosa extracellular matrix (PSISM) on the vitality and gene regulation of hepatocyte so as to lay the experimental foundation for the application of PSISM in liver tissue engineerin...