{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T15:01:51Z","timestamp":1791385311458,"version":"4.3.3"},"reference-count":80,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2026,8,31]],"date-time":"2026-08-31T00:00:00Z","timestamp":1788134400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,8,31]],"date-time":"2026-08-31T00:00:00Z","timestamp":1788134400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Journal of Microscopy"],"published-print":{"date-parts":[[2026,10]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Multimodal optical microscopy has recently converged with artificial intelligence (AI) to enable in silico labelling\u2014the computational prediction of fluorescence\u2010like molecular contrast from label\u2010free measurements. Fluorescence plays a crucial role in linking microscopy and spectroscopy at molecular level, enabling image formation by means of linear and non\u2010linear investigation modalities. Over the past two decades, fluorescence optical microscopy has progressed into optical nanoscopy and single molecule localisation methods that operate at the nano\u2010 and even \u00c5ngstrom level under ambient conditions. Methods such as Stimulated Emission Depletion (STED), Photo\u2010Activated Localisation (PALM), Stochastic Optical Reconstruction (STORM), super\u2010resolution fluorescence lifetime imaging microscopy (FLIM) and image scanning microscopy (ISM), Minimal Fluorescence photon Flux (MINFLUX) microscopy allows us to investigate living cells at the molecular level. A significant and challenging development in this field is the coupling of fluorescence with label\u2010free polarisation and phase optical methods\u2014for example, Mueller\u2010matrix (MM) microscopy\u2014with the aim of extracting specific molecular information from label\u2010free datasets. In this review, we discuss how this convergence, together with modern generative modelling for in silico labelling, is turning the optical microscope into an intelligent instrument.<\/jats:p>","DOI":"10.1111\/jmi.70163","type":"journal-article","created":{"date-parts":[[2026,8,31]],"date-time":"2026-08-31T15:11:36Z","timestamp":1788189096000},"page":"41-50","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["\u2018In silico labelling\u2019: Exploring the biological landscape at the nanoscale using intelligent multimodal optical microscopy"],"prefix":"10.1111","volume":"304","author":[{"given":"A.","family":"Diaspro","sequence":"first","affiliation":[{"name":"Department of Nanoscopy, Italian Institute of Technology, CHT Erzelli  Genoa Italy"},{"name":"SEELIFE, Department of Physics University of Genoa  Genoa Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"P.","family":"Bianchini","sequence":"additional","affiliation":[{"name":"Department of Nanoscopy, Italian Institute of Technology, CHT Erzelli  Genoa Italy"},{"name":"SEELIFE, Department of Physics University of Genoa  Genoa Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"R.","family":"Bizzarri","sequence":"additional","affiliation":[{"name":"Department of Nanoscopy, Italian Institute of Technology, CHT Erzelli  Genoa Italy"},{"name":"Department of Surgical Medical and Molecular Pathology, and Critical Care Medicine, University of Pisa  Pisa Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"F. 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