摘要

What a fantastic time to be a microscopist! A great enabling technology to help to understand how molecules regulate life or are dysregulated leading to diseases. Today focus will be on large-scale electron microscopy like nanotomy [1], as well as on analytical ‘ColorEM’ [2] and the possibility to reanalyze greyscale EM in databases using AI trained by ColorEM [3,4]. I will be happy to discuss limitations of the different techniques together, and how to overcome these by using multimodal approaches leading to a bright future of implementation of microscopy to better understand how molecules regulate life, may cause diseases or may help to prevent and cure diseases.

个人简介

Ben Giepmans is intrigued by how biomolecules act together to control cell fate in health and disease. He is a cell biologist and molecular biochemist/ microscopist. His PhD research at The Netherlands Cancer Institute (2001) and related work in The Scripps Research Institute (CA, USA) have led to a better molecular understanding of gap junctions. In his second post-doc he implemented several new advanced imaging techniques and probes to study protein dynamics in live cells and protein localization at high resolution. These studies have given unexpected new insights in Golgi apparatus reformation during mitosis (NCMIR, University of California, San Diego).

Innovative microscopy is the spearpoint of Giepmans’ research group at UMC Groningen where he also is the architect and director of the advanced microscopy & imaging center (UMIC). The team develops and/or implements new imaging techniques with and without probes for large-scale and multimodal microscopy. Particular focus is on Islets of Langerhans to help to understand trigger(s) and potential new therapies for Type 1 diabetes.

[1] Pirozzi et al. (2018) ColorEM: analytical EM for element-guided identification and imaging of the building blocks of life. Histochem Cell Biol.150:509

[2] de Boer P et al.. Large-scale EM database for human type 1 diabetes (2020). Nat ommun.11:2475

[3] Duinkerken et al. (2024) Automated analysis of ultrastructure through large-scale hyperspectral EM. npj Imaging 11;2:53

[4] Aswath A et al. (2026) ColorEM-Net: Automated segmentation of structures in large-scale EM using element-derived ground truth. In: Castrillón-Santana M et al. Computer Analysis of Images and Patterns. CAIP 2025. Lecture Notes in Computer Science, vol 15621. Springer, Cham.