Optical nanoscopy challenges in the metaverse era. The case of multimodal imaging of chromatin in the nucleus

Optical Nanoscopy deals with designing and developing optical microscopes able to produce images that are rich sources of quantitative information at the nanoscale. This fact offers an unprecedented insight into the molecular mechanisms that govern and determine the fate of living cells, coupled with a large amount of data to be structured. In this scenario, multimodal optical microscopy is a growing attitude boosted by artificial intelligence. Metaverse environments offer potential advantages in analysing data in terms of interactivity in a kind of “infinite” space to visualise multimodal data. In the era of super-resolved fluorescence microscopy, the photochemical parameters, from brightness to lifetime, can be merged with the ones coming from label-free approaches like Mueller matrix microscopy. Here, we report on the potential of convolutional neural networks (CNN) and independent component analysis (ICA) algorithms in the domain of machine learning and deep learning with the ambitious target to create a robust virtual environment “to see” what we could not perceive before. Is the metaverse an helpful approach to elucidating the still open universal question in biology about how chromatin organisation in the nucleus rules the compaction and function of the human genome in the interphase of cells and mitotic chromosomes? We start with the development of a multimodal optical microscope reinforced by the artificial intelligence component.