Machine learning helps scientists measure important inflammation process

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, PhD, 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. One type of white cell, the neutrophil, expels its DNA into the bloodstream to trap bacteria and viruses and aid in their killing to prevent infections. This neutrophil DNA has a net-like appearance and is called Neutrophil Extracellular Traps, or NETs.