Machine learning helps scientists measure important inflammation process

Inflammation is a hallmark of many health conditions, but quantifying how the underlying biology of inflammation contributes to specific diseases has been difficult. For the first time, UNC School of Medicine researchers and colleagues now report the development of a new technology to identify white blood cells called neutrophils that are primed to eject inflammatory DNA into the circulation via a process called NETosis. The findings, published in Scientific Reports, mark the first time scientists have used machine learning tools for rapid quantitative and qualitative cell analysis in basic science. "This new test will allow investigators to measure NETosis in different diseases and to test drugs that may inhibit or promote the process," said senior author Leslie Parise, Ph.D., professor and chair of the UNC Department of Biochemistry and Biophysics. When foreign invaders such as viruses or bacteria enter our bodies, white blood cells rush in to fight the invaders in various ways.