| Issue Date | Title | Involved Person(s) |
| 2021 | Keeping SARS-CoV-2 out : vaccines, filters, and self-disinfecting textiles | Eibl, Dieter; Sievers, Martin; Eibl, Regine; Bachmann, Martin; Walton, Senta, et al |
| 2021 | Effects of low and high aneurysmal wall shear stress on endothelial cell behavior : differences and similarities | Morel, Sandrine; Schilling, Sabine; Diagbouga, Mannekomba R.; Delucchi, Matteo; Bochaton-Piallat, Marie-Luce, et al |
| 16-Nov-2020 | Genome-wide association study of intracranial aneurysms identifies 17 risk loci and genetic overlap with clinical risk factors | Bakker, Mark K.; van der Spek, Rick A. A.; van Rheenen, Wouter; Morel, Sandrine; Bourcier, Romain, et al |
| 4-Jun-2020 | Shape irregularity of the intracranial aneurysm lumen exhibits diagnostic value | Juchler, Norman; Schilling, Sabine; Bijlenga, Philippe; Morel, Sandrine; Rüfenacht, Daniel, et al |
| 17-Mar-2020 | Radiomics approach to quantify shape irregularity from crowd-based qualitative assessment of intracranial aneurysms | Juchler, Norman; Schilling, Sabine; Glüge, Stefan; Bijlenga, Philippe; Rüfenacht, Daniel, et al |
| 1-Feb-2020 | Incorporating variability of patient inflow conditions into statistical models for aneurysm rupture assessment | Detmer, Felicitas J.; Mut, Fernando; Slawski, Martin; Hirsch, Sven; Bijlenga, Philippe, et al |
| 21-Jan-2020 | Influence of input image configurations on output of a convolutional neural network to detect cerebral aneurysms | Watanabe, Kazuhiro; Anzai, Hitomi; Juchler, Norman; Hirsch, Sven; Ohta, Makoto |
| Jan-2020 | Comparison of statistical learning approaches for cerebral aneurysm rupture assessment | Detmer, Felicitas J.; Lückehe, Daniel; Mut, Fernando; Slawski, Martin; Hirsch, Sven, et al |
| 2020 | Production and secretion dynamics of prokaryotic Penicillin G acylase in Pichia pastoris | Borčinová, Martina; Raschmanová, Hana; Zamora, Iwo; Looser, Verena; Marešová, Helena, et al |
