DeSide: A unified deep learning approach for cellular deconvolution of tumor microenvironment.

Cellular deconvolution via bulk RNA sequencing (RNA-seq) presents a cost-effective and efficient alternative to experimental methods such as flow cytometry and single-cell RNA-seq (scRNA-seq) for analyzing the complex cellular composition of tumor microenvironments. Despite challenges due to heterogeneity within and among tumors, our innovative deep learning-based approach, DeSide, shows exceptional accuracy in estimating the proportions of 16 distinct cell types and subtypes within solid tumors. DeSide integrates biological pathways and assesses noncancerous cell types first, effectively sidestepping the issue of highly variable gene expression profiles (GEPs) associated with cancer cells.

Metabolomic response of Euglena gracilis and its bleached mutant strain to light.

Euglena, a new superfood on the market, is a nutrient-rich, green single-celled microorganism that features the characteristics of both plant and animal. When cultivated under different conditions, Euglena produces different bioactive nutrients. Interestingly, Euglena is the only known microorganism whose chloroplasts are easy to lose under stress and become permanently bleached.