New research from the University of Chicago shows that a deceptively simple mathematical model can describe how the soil responds to environmental change. Using just two variables, the model shows that changes in pH levels consistently result in three distinct metabolic states of the community.

Cells and tissues surrounding a breast cancer tumor may hold critical information about how patients will respond to treatment. After looking for patterns in images of tissue and biopsy samples, a newly developed AI tool sorted breast cancer patients patients into seven groups. Some of the groups had better survival outcomes than others, suggesting there may be information in the microenvironments that oncologists could use for prognoses. 

Developed by researchers at Oregon Health & Science University’s Knight Cancer Institute, the tool, dubbed OmicsTweezer, uses advanced machine learning techniques to analyze biological data at a scale large enough to estimate the composition of cell types in a sample of tissue that may be taken from a biopsy. This process allows scientists to map the cellular makeup of tumors and surrounding tissues — an area known as the tumor microenvironment.