@article{19795,
  abstract     = {Super-resolution microscopy often entails long acquisition times of minutes to hours. Since drifts during the acquisition adversely affect data quality, active sample stabilization is commonly used for some of these techniques to reach their full potential. Although drifts in the lateral plane can often be corrected after acquisition, this is not always possible or may come with drawbacks. Therefore, it is appealing to stabilize sample position in three dimensions (3D) during acquisition. Various schemes for active sample stabilization have been demonstrated previously, with some reaching sub-nanometer stability in 3D. Here, we present a scheme for active drift correction that delivers the nanometer-scale 3D stability demanded by state-of-the-art super-resolution techniques and is straightforward to implement compared to previous schemes capable of reaching this level of stabilization precision. Using a refined algorithm that can handle various types of reference structure, without sparse signal peaks being mandatory, we stabilized sample position to ∼1 nm in 3D using objective lenses both with high and low numerical aperture. Our implementation requires only the addition of a simple widefield imaging path and we provide an open-source control software with graphical user interface to facilitate easy adoption of the module. Finally, we demonstrate how this has the potential to enhance data collection for diffraction-limited and super-resolution imaging techniques using single-molecule localization microscopy and cryo-confocal imaging as showcases.},
  author       = {Vorlaufer, Jakob and Semenov, Nikolai and Kreuzinger, Caroline and Javoor, Manjunath and Zens, Bettina and Agudelo Duenas, Nathalie and Tavakoli, Mojtaba and Suplata, Marek and Jahr, Wiebke and Lyudchik, Julia and Wartak, Andreas and Schur, Florian Km and Danzl, Johann G},
  issn         = {2667-0747},
  journal      = {Biophysical Reports},
  number       = {2},
  publisher    = {Elsevier},
  title        = {{Image-based 3D active sample stabilization on the nanometer scale for optical microscopy}},
  doi          = {10.1016/j.bpr.2025.100211},
  volume       = {5},
  year         = {2025},
}

@article{13267,
  abstract     = {Three-dimensional (3D) reconstruction of living brain tissue down to an individual synapse level would create opportunities for decoding the dynamics and structure–function relationships of the brain’s complex and dense information processing network; however, this has been hindered by insufficient 3D resolution, inadequate signal-to-noise ratio and prohibitive light burden in optical imaging, whereas electron microscopy is inherently static. Here we solved these challenges by developing an integrated optical/machine-learning technology, LIONESS (live information-optimized nanoscopy enabling saturated segmentation). This leverages optical modifications to stimulated emission depletion microscopy in comprehensively, extracellularly labeled tissue and previous information on sample structure via machine learning to simultaneously achieve isotropic super-resolution, high signal-to-noise ratio and compatibility with living tissue. This allows dense deep-learning-based instance segmentation and 3D reconstruction at a synapse level, incorporating molecular, activity and morphodynamic information. LIONESS opens up avenues for studying the dynamic functional (nano-)architecture of living brain tissue.},
  author       = {Velicky, Philipp and Miguel Villalba, Eder and Michalska, Julia M and Lyudchik, Julia and Wei, Donglai and Lin, Zudi and Watson, Jake and Troidl, Jakob and Beyer, Johanna and Ben Simon, Yoav and Sommer, Christoph M and Jahr, Wiebke and Cenameri, Alban and Broichhagen, Johannes and Grant, Seth G.N. and Jonas, Peter M and Novarino, Gaia and Pfister, Hanspeter and Bickel, Bernd and Danzl, Johann G},
  issn         = {1548-7105},
  journal      = {Nature Methods},
  pages        = {1256--1265},
  publisher    = {Springer Nature},
  title        = {{Dense 4D nanoscale reconstruction of living brain tissue}},
  doi          = {10.1038/s41592-023-01936-6},
  volume       = {20},
  year         = {2023},
}

@article{6808,
  abstract     = {Super-resolution fluorescence microscopy has become an important catalyst for discovery in the life sciences. In STimulated Emission Depletion (STED) microscopy, a pattern of light drives fluorophores from a signal-emitting on-state to a non-signalling off-state. Only emitters residing in a sub-diffraction volume around an intensity minimum are allowed to fluoresce, rendering them distinguishable from the nearby, but dark fluorophores. STED routinely achieves resolution in the few tens of nanometers range in biological samples and is suitable for live imaging. Here, we review the working principle of STED and provide general guidelines for successful STED imaging. The strive for ever higher resolution comes at the cost of increased light burden. We discuss techniques to reduce light exposure and mitigate its detrimental effects on the specimen. These include specialized illumination strategies as well as protecting fluorophores from photobleaching mediated by high-intensity STED light. This opens up the prospect of volumetric imaging in living cells and tissues with diffraction-unlimited resolution in all three spatial dimensions.},
  author       = {Jahr, Wiebke and Velicky, Philipp and Danzl, Johann G},
  issn         = {1046-2023},
  journal      = {Methods},
  number       = {3},
  pages        = {27--41},
  publisher    = {Elsevier},
  title        = {{Strategies to maximize performance in STimulated Emission Depletion (STED) nanoscopy of biological specimens}},
  doi          = {10.1016/j.ymeth.2019.07.019},
  volume       = {174},
  year         = {2020},
}