TY - JOUR A1 - Lehle, Karla A1 - Philipp, Alois A1 - Krenkel, Lars A1 - Gruber, Michael A1 - Hiller, Karl-Anton A1 - Müller, Thomas A1 - Lubnow, Matthias T1 - Thrombocytopenia During Venovenous Extracorporeal Membrane Oxygenation in Adult Patients With Bacterial, Viral, and COVID-19 Pneumonia JF - ASAIO Journal N2 - Contact of blood with artificial surfaces triggers platelet activation. The aim was to compare platelet kinetics after venovenous extracorporeal membrane oxygenation (V-V ECMO) start and after system exchange in different etiologies of acute lung failure. Platelet counts and coagulation parameters were analyzed from adult patients with long and exchange-free (≥8 days) ECMO runs (n = 330) caused by bacterial (n = 142), viral (n = 76), or coronavirus disease 2019 (COVID-19) (n = 112) pneumonia. A subpopulation requiring a system exchange and with long, exchange-free runs of the second oxygenator (≥7 days) (n = 110) was analyzed analogously. Patients with COVID-19 showed the highest platelet levels before ECMO implantation. Independent of the underlying disease and ECMO type, platelet counts decreased significantly within 24 hours and reached a steady state after 5 days. In the subpopulation, at the day of a system exchange, platelet counts were lower compared with ECMO start, but without differences between underlying diseases. Subsequently, platelets remained unchanged in the bacterial pneumonia group, but increased in the COVID-19 and viral pneumonia groups within 2–4 days, whereas D-dimers decreased and fibrinogen levels increased. Thus, overall platelet counts on V-V ECMO show disease-specific initial dynamics followed by an ongoing consumption by the ECMO device, which is not boosted by new artificial surfaces after a system exchange. Y1 - 2025 U6 - https://doi.org/10.1097/MAT.0000000000002383 SN - 1058-2916 SN - 1538-943X PB - Wolters Kluwer ER - TY - JOUR A1 - Pointner, Daniel A1 - Kranz, Michael A1 - Wagner, Maria Stella A1 - Haus, Moritz A1 - Lehle, Karla A1 - Krenkel, Lars T1 - Automated deep learning based detection of cellular deposits on clinically used ECMO membrane lungs JF - Frontiers in Bioinformatics N2 - Introduction: Despite the promising application of extracorporeal membrane oxygenation (ECMO) in the treatment of critically ill patients, coagulation-associated technical complications, primarily clot formation and critical bleeding, remain a major challenge during ECMO therapy. The deposition of nucleated cells on the surface has been shown, yet the role of these cells towards complication development is still matter of ongoing research. In particular, the membrane lung (MemL) is prone to clot formation. Therefore, the investigation of nuclear deposits on its hollow-fibers may provide insights for a better understanding of the cellular mechanisms involved in the development of ECMO complications. Methods: To support current research, this study aimed to develop a deep learning–based tool for the automated detection and quantitative analysis of nuclear depositions on MemL hollow-fiber mats. A customized fluorescence microscopy workflow, combined with a semi-automated iterative labeling strategy, was used to generate a high-quality dataset for model training. Results: Six configurations of instance segmentation models were evaluated, with a Mask R-CNN with ResNet 101 backbone using dilated convolution providing the most balanced performance in both nuclei count and area accuracy. Compared with U-Net–based approaches such as Cellpose or StarDist, the proposed model demonstrated superior segmentation of overlapping and low-intensity nuclei, maintaining accuracy even in densely packed cellular regions. Discussion: We present an automated image analysis tool for clinically used MemLs, which exhibit complex three-dimensional hollow-fiber architectures and irregular cellular deposits that challenge conventional tools. A dedicated graphical user interface enables streamlined detection, morphometric analysis, and spatial clustering of nuclei, establishing a reproducible workflow for high-throughput analysis of fluorescence microscopy images. This approach eliminates labor-intensive manual counting and facilitates large-scale studies on cell-fiber interactions and disease-related correlations. Y1 - 2026 U6 - https://doi.org/10.3389/fbinf.2026.1771574 N1 - Corresponding author der OTH Regensburg: Daniel Pointner, Lars Krenkel VL - 6 PB - Frontiers ER - TY - CHAP A1 - Michel, Johanna A1 - Krenkel, Lars ED - Dillmann, Andreas ED - Heller, Gerd ED - Krämer, Ewald ED - Breitsamter, Christian ED - Wagner, Claus ED - Krenkel, Lars T1 - Towards Experimental Validation of Models of Shear-Induced Aerosol Generation in the Human Respiratory System T2 - New Results in Numerical and Experimental Fluid Mechanics XV : Contributions to the 24th STAB/DGLR Symposium, Regensburg, Germany, 2024 N2 - Numerical modeling is a valuable tool to research shear-induced aerosol generation inside the human respiratory system. While the volume of fluid method and Eulerian wall film models have been used to predict the stripping of particles from the mucus film, sufficient validation data is lacking. Here, we present an experimental method to create such validation data. A film of mucus mimetic hydrogel with an initial thickness of 1 mm covering the floor of a rectangular channel (75.5 mm 25.5 mm 3 mm) was exposed to an airflow with a flow rate of 9.5 and 21.6 L/min. The number of created particles and the emergence of waves on the mucus surface were measured. Shear-induced aerosol generation was triggered successfully and caused an increase of mean particle flow. Different wave profiles were observed at varying film depths. Y1 - 2026 SN - 978-3-032-11114-2 U6 - https://doi.org/10.1007/978-3-032-11115-9_13 SP - 135 EP - 144 PB - Springer Nature CY - Cham ER -