Machine learning reduces microscope data processing time from months to just seconds

Ever since the world's first ever microscope was invented in 1590 by Hans and Zacharias Janssen--a Dutch father and son--our curiosity for what goes on at the tiniest scales has led to development of increasingly powerful devices. Fast forward to 2021, we not only have optical microscopy methods that allow us to see tiny particles in higher resolution than ever before, we also have non-optical techniques, such as scanning force microscopes, with which researchers can construct detailed maps of a range of physical and chemical properties. Institute for Bioengineering of Catalonia (IBEC)'s Nanoscale Bioelectrical Characterization group, led by UB Professor Gabriel Gomila, in collaboration with members of the IBEC's Nanoscopy for Nanomedicine group, have been analyzing cells using a special type of microscopy called Scanning Dielectric Force Volume Microscopy, an advanced technique developed in recent years with which they can create maps of an electrical physical property called the dielectric constant. Each of the biomolecules that make up cells--that is, lipids, proteins and nucleic acids--has a different dielectric constant, so a map of this property is basically a map of cell composition. The technique that they developed has an advantage over the current gold standard optical method, which involves applying a fluorescent dye that can disrupt the cell being studied.