@misc{18697,
  abstract     = {The information-processing capability of the brain’s cellular network depends on the physical wiring pattern between neurons and their molecular and functional characteristics. Mapping neurons and resolving their individual synaptic connections can be achieved by volumetric imaging at nanoscale resolution with dense cellular labelling. Light microscopy is uniquely positioned to visualize specific molecules but dense, synapse-level circuit reconstruction by light microscopy has been out of reach due to limitations in resolution, contrast, and volumetric imaging capability. Here we developed light-microscopy based connectomics (LICONN). We integrated specifically engineered hydrogel embedding and expansion with comprehensive deep-learning based segmentation and analysis of connectivity, thus directly incorporating molecular information in synapse-level brain tissue reconstructions. LICONN will allow synapse-level brain tissue phenotyping in biological experiments in a readily adoptable manner.},
  author       = {Danzl, Johann G and Lyudchik, Julia and Kreuzinger, Caroline},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Light-microscopy based connectomic reconstruction of mammalian brain tissue}},
  doi          = {10.15479/AT:ISTA:18697},
  year         = {2025},
}

@misc{18837,
  abstract     = {Super-resolution methods provide far better spatial resolution than the optical diffraction limit of about half the wavelength of light (∼200-300 nm). Nevertheless, they have yet to attain widespread use in plants, largely due to plants’ challenging optical properties. Expansion microscopy improves effective resolution by isotropically increasing the physical distances between sample structures while preserving relative spatial arrangements and clearing the sample. However, its application to plants has been hindered by the rigid, mechanically cohesive structure of plant tissues. Here, we report on whole-mount expansion microscopy of thale cress (Arabidopsis thaliana) root tissues (PlantEx), achieving a four-fold resolution increase over conventional microscopy. Our results highlight the microtubule cytoskeleton organization and interaction between molecularly defined cellular constituents. Combining PlantEx with stimulated emission depletion (STED) microscopy, we increase nanoscale resolution and visualize the complex organization of subcellular organelles from intact tissues by example of the densely packed COPI-coated vesicles associated with the Golgi apparatus and put these into a cellular structural context. Our results show that expansion microscopy can be applied to increase effective imaging resolution in Arabidopsis root specimens.},
  author       = {Danzl, Johann G and Kreuzinger, Caroline},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Research Data for the publication "Super-resolution expansion microscopy in plant roots"}},
  doi          = {10.15479/AT:ISTA:18837},
  year         = {2025},
}

@article{19003,
  abstract     = {Super-resolution methods provide far better spatial resolution than the optical diffraction limit of about half the wavelength of light (∼200-300 nm). Nevertheless, they have yet to attain widespread use in plants, largely due to plants’ challenging optical properties. Expansion microscopy improves effective resolution by isotropically increasing the physical distances between sample structures while preserving relative spatial arrangements and clearing the sample. However, its application to plants has been hindered by the rigid, mechanically cohesive structure of plant tissues. Here, we report on whole-mount expansion microscopy of thale cress (Arabidopsis thaliana) root tissues (PlantEx), achieving a four-fold resolution increase over conventional microscopy. Our results highlight the microtubule cytoskeleton organization and interaction between molecularly defined cellular constituents. Combining PlantEx with stimulated emission depletion (STED) microscopy, we increase nanoscale resolution and visualize the complex organization of subcellular organelles from intact tissues by example of the densely packed COPI-coated vesicles associated with the Golgi apparatus and put these into a cellular structural context. Our results show that expansion microscopy can be applied to increase effective imaging resolution in Arabidopsis root specimens. },
  author       = {Gallei, Michelle C and Truckenbrodt, Sven M and Kreuzinger, Caroline and Inumella, Syamala and Vistunou, Vitali and Sommer, Christoph M and Tavakoli, Mojtaba and Agudelo Duenas, Nathalie and Vorlaufer, Jakob and Jahr, Wiebke and Randuch, Marek and Johnson, Alexander J and Benková, Eva and Friml, Jiří and Danzl, Johann G},
  issn         = {1532-298X},
  journal      = {The Plant Cell},
  number       = {4},
  publisher    = {Oxford University Press},
  title        = {{Super-resolution expansion microscopy in plant roots}},
  doi          = {10.1093/plcell/koaf006},
  volume       = {37},
  year         = {2025},
}

@article{19704,
  abstract     = {The information-processing capability of the brain’s cellular network depends on the physical wiring pattern between neurons and their molecular and functional characteristics. Mapping neurons and resolving their individual synaptic connections can be achieved by volumetric imaging at nanoscale resolution1,2 with dense cellular labelling. Light microscopy is uniquely positioned to visualize specific molecules, but dense, synapse-level circuit reconstruction by light microscopy has been out of reach, owing to limitations in resolution, contrast and volumetric imaging capability. Here we describe light-microscopy-based connectomics (LICONN). We integrated specifically engineered hydrogel embedding and expansion with comprehensive deep-learning-based segmentation and analysis of connectivity, thereby directly incorporating molecular information into synapse-level reconstructions of brain tissue. LICONN will allow synapse-level phenotyping of brain tissue in biological experiments in a readily adoptable manner.},
  author       = {Tavakoli, Mojtaba and Lyudchik, Julia and Januszewski, Michał and Vistunou, Vitali and Agudelo Duenas, Nathalie and Vorlaufer, Jakob and Sommer, Christoph M and Kreuzinger, Caroline and Oliveira, Bárbara and Cenameri, Alban and Novarino, Gaia and Jain, Viren and Danzl, Johann G},
  issn         = {1476-4687},
  journal      = {Nature},
  pages        = {398--410},
  publisher    = {Springer Nature},
  title        = {{Light-microscopy-based connectomic reconstruction of mammalian brain tissue}},
  doi          = {10.1038/s41586-025-08985-1},
  volume       = {642},
  year         = {2025},
}

@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},
}

@unpublished{18689,
  abstract     = {Multiplexed fluorescence microscopy imaging is widely used in biomedical applications. However, simultaneous imaging of multiple fluorophores can result in spectral leaks and overlapping, which greatly degrades image quality and subsequent analysis. Existing popular spectral unmixing methods are mainly based on computational intensive linear models and the performance is heavily dependent on the reference spectra, which may greatly preclude its further applications. In this paper, we propose a deep learning-based blindly spectral unmixing method, termed AutoUnmix, to imitate the physical spectral mixing process. A tranfer learning framework is further devised to allow our AutoUnmix adapting to a variety of imaging systems without retraining the network. Our proposed method has demonstrated real-time unmixing capabilities, surpassing existing methods by up to 100-fold in terms of unmixing speed. We further validate the reconstruction performance on both synthetic datasets and biological samples. The unmixing results of AutoUnmix achieve a highest SSIM of 0.99 in both three- and four-color imaging, with nearly up to 20% higher than other popular unmixing methods. Due to the desirable property of data independency and superior blind unmixing performance, we believe AutoUnmix is a powerful tool to study the interaction process of different organelles labeled by multiple fluorophores.},
  author       = {Gallei, Michelle C and Truckenbrodt, Sven M and Kreuzinger, Caroline and Inumella, Syamala and Vistunou, Vitali and Sommer, Christoph M and Tavakoli, Mojtaba and Agudelo Duenas, Nathalie and Vorlaufer, Jakob and Jahr, Wiebke and Randuch, Marek and Johnson, Alexander J and Benková, Eva and Friml, Jiří and Danzl, Johann G},
  booktitle    = {bioRxiv},
  title        = {{Super-resolution expansion microscopy in plant roots}},
  doi          = {10.1101/2024.02.21.581330},
  year         = {2024},
}

@unpublished{18677,
  abstract     = {The information-processing capability of the brain’s cellular network depends on the physical wiring pattern between neurons and their molecular and functional characteristics. Mapping neurons and resolving their individual synaptic connections can be achieved by volumetric imaging at nanoscale resolution with dense cellular labeling. Light microscopy is uniquely positioned to visualize specific molecules but dense, synapse-level circuit reconstruction by light microscopy has been out of reach due to limitations in resolution, contrast, and volumetric imaging capability. Here we developed light-microscopy based connectomics (LICONN). We integrated specifically engineered hydrogel embedding and expansion with comprehensive deep-learning based segmentation and analysis of connectivity, thus directly incorporating molecular information in synapse-level brain tissue reconstructions. LICONN will allow synapse-level brain tissue phenotyping in biological experiments in a readily adoptable manner.},
  author       = {Tavakoli, Mojtaba and Lyudchik, Julia and Januszewski, Michał and Vistunou, Vitali and Agudelo Duenas, Nathalie and Vorlaufer, Jakob and Sommer, Christoph M and Kreuzinger, Caroline and Oliveira, Bárbara and Cenameri, Alban and Novarino, Gaia and Jain, Viren and Danzl, Johann G},
  booktitle    = {bioRxiv},
  title        = {{Light-microscopy based dense connectomic reconstruction of mammalian brain tissue}},
  doi          = {10.1101/2024.03.01.582884},
  year         = {2024},
}

@article{12115,
  author       = {Glajzer, Jacek and Castillo-Tong, Dan Cacsire and Richter, Rolf and Vergote, Ignace and Kulbe, Hagen and Vanderstichele, Adriaan and Ruscito, Ilary and Trillsch, Fabian and Mustea, Alexander and Kreuzinger, Caroline and Gourley, Charlie and Gabra, Hani and Taube, Eliane T. and Dorigo, Oliver and Horst, David and Keunecke, Carlotta and Baum, Joanna and Angelotti, Timothy and Sehouli, Jalid and Braicu, Elena Ioana},
  issn         = {1534-4681},
  journal      = {Annals of Surgical Oncology},
  keywords     = {Oncology, Surgery},
  pages        = {46--47},
  publisher    = {Springer Nature},
  title        = {{ASO Visual Abstract: Impact of BRCA mutation status on tumor dissemination pattern, surgical outcome, and patient survival in primary and recurrent high-grade serous ovarian cancer (HGSOC). A multicenter, retrospective study of the ovarian cancer therapy—innovative models prolong survival (OCTIPS) consortium}},
  doi          = {10.1245/s10434-022-12681-z},
  volume       = {30},
  year         = {2023},
}

@article{12205,
  abstract     = {Background: This study seeks to evaluate the impact of breast cancer (BRCA) gene status on tumor dissemination pattern, surgical outcome and survival in a multicenter cohort of paired primary ovarian cancer (pOC) and recurrent ovarian cancer (rOC).

Patients and Methods: Medical records and follow-up data from 190 patients were gathered retrospectively. All patients had surgery at pOC and at least one further rOC surgery at four European high-volume centers. Patients were divided into one cohort with confirmed mutation for BRCA1 and/or BRCA2 (BRCAmut) and a second cohort with BRCA wild type or unknown (BRCAwt). Patterns of tumor presentation, surgical outcome and survival data were analyzed between the two groups.

Results: Patients with BRCAmut disease were on average 4 years younger and had significantly more tumor involvement upon diagnosis. Patients with BRCAmut disease showed higher debulking rates at all stages. Multivariate analysis showed that only patient age had significant predictive value for complete tumor resection in pOC. At rOC, however, only BRCAmut status significantly correlated with optimal debulking. Patients with BRCAmut disease showed significantly prolonged overall survival (OS) by 24.3 months. Progression-free survival (PFS) was prolonged in the BRCAmut group at all stages as well, reaching statistical significance during recurrence.

Conclusions: Patients with BRCAmut disease showed a more aggressive course of disease with earlier onset and more extensive tumor dissemination at pOC. However, surgical outcome and OS were significantly better in patients with BRCAmut disease compared with patients with BRCAwt disease. We therefore propose to consider BRCAmut status in regard to patient selection for cytoreductive surgery, especially in rOC.},
  author       = {Glajzer, Jacek and Castillo-Tong, Dan Cacsire and Richter, Rolf and Vergote, Ignace and Kulbe, Hagen and Vanderstichele, Adriaan and Ruscito, Ilary and Trillsch, Fabian and Mustea, Alexander and Kreuzinger, Caroline and Gourley, Charlie and Gabra, Hani and Taube, Eliane T. and Dorigo, Oliver and Horst, David and Keunecke, Carlotta and Baum, Joanna and Angelotti, Timothy and Sehouli, Jalid and Braicu, Elena Ioana},
  issn         = {1534-4681},
  journal      = {Annals of Surgical Oncology},
  keywords     = {Oncology, Surgery},
  pages        = {35--45},
  publisher    = {Springer Nature},
  title        = {{Impact of BRCA mutation status on tumor dissemination pattern, surgical outcome and patient survival in primary and recurrent high-grade serous ovarian cancer: A multicenter retrospective study by the Ovarian Cancer Therapy-Innovative Models Prolong Survival (OCTIPS) consortium}},
  doi          = {10.1245/s10434-022-12459-3},
  volume       = {30},
  year         = {2023},
}

@article{9429,
  abstract     = {De novo loss of function mutations in the ubiquitin ligase-encoding gene Cullin3 lead to autism spectrum disorder (ASD). In mouse, constitutive haploinsufficiency leads to motor coordination deficits as well as ASD-relevant social and cognitive impairments. However, induction of Cul3 haploinsufficiency later in life does not lead to ASD-relevant behaviors, pointing to an important role of Cul3 during a critical developmental window. Here we show that Cul3 is essential to regulate neuronal migration and, therefore, constitutive Cul3 heterozygous mutant mice display cortical lamination abnormalities. At the molecular level, we found that Cul3 controls neuronal migration by tightly regulating the amount of Plastin3 (Pls3), a previously unrecognized player of neural migration. Furthermore, we found that Pls3 cell-autonomously regulates cell migration by regulating actin cytoskeleton organization, and its levels are inversely proportional to neural migration speed. Finally, we provide evidence that cellular phenotypes associated with autism-linked gene haploinsufficiency can be rescued by transcriptional activation of the intact allele in vitro, offering a proof of concept for a potential therapeutic approach for ASDs.},
  author       = {Morandell, Jasmin and Schwarz, Lena A and Basilico, Bernadette and Tasciyan, Saren and Dimchev, Georgi A and Nicolas, Armel and Sommer, Christoph M and Kreuzinger, Caroline and Dotter, Christoph and Knaus, Lisa and Dobler, Zoe and Cacci, Emanuele and Schur, Florian KM and Danzl, Johann G and Novarino, Gaia},
  issn         = {2041-1723},
  journal      = {Nature Communications},
  keywords     = {General Biochemistry, Genetics and Molecular Biology},
  number       = {1},
  publisher    = {Springer Nature},
  title        = {{Cul3 regulates cytoskeleton protein homeostasis and cell migration during a critical window of brain development}},
  doi          = {10.1038/s41467-021-23123-x},
  volume       = {12},
  year         = {2021},
}

@unpublished{7800,
  abstract     = {De novo loss of function mutations in the ubiquitin ligase-encoding gene Cullin3 (CUL3) lead to autism spectrum disorder (ASD). Here, we used Cul3 mouse models to evaluate the consequences of Cul3 mutations in vivo. Our results show that Cul3 haploinsufficient mice exhibit deficits in motor coordination as well as ASD-relevant social and cognitive impairments. Cul3 mutant brain displays cortical lamination abnormalities due to defective neuronal migration and reduced numbers of excitatory and inhibitory neurons. In line with the observed abnormal columnar organization, Cul3 haploinsufficiency is associated with decreased spontaneous excitatory and inhibitory activity in the cortex. At the molecular level, employing a quantitative proteomic approach, we show that Cul3 regulates cytoskeletal and adhesion protein abundance in mouse embryos. Abnormal regulation of cytoskeletal proteins in Cul3 mutant neuronal cells results in atypical organization of the actin mesh at the cell leading edge, likely causing the observed migration deficits. In contrast to these important functions early in development, Cul3 deficiency appears less relevant at adult stages. In fact, induction of Cul3 haploinsufficiency in adult mice does not result in the behavioral defects observed in constitutive Cul3 haploinsufficient animals. Taken together, our data indicate that Cul3 has a critical role in the regulation of cytoskeletal proteins and neuronal migration and that ASD-associated defects and behavioral abnormalities are primarily due to Cul3 functions at early developmental stages.},
  author       = {Morandell, Jasmin and Schwarz, Lena A and Basilico, Bernadette and Tasciyan, Saren and Nicolas, Armel and Sommer, Christoph M and Kreuzinger, Caroline and Knaus, Lisa and Dobler, Zoe and Cacci, Emanuele and Danzl, Johann G and Novarino, Gaia},
  booktitle    = {bioRxiv},
  title        = {{Cul3 regulates cytoskeleton protein homeostasis and cell migration during a critical window of brain development}},
  doi          = {10.1101/2020.01.10.902064 },
  year         = {2020},
}