In this project, the growth of fungal hyphae is modeled. As a parameterized approach, different hyphal structures can be learned, simulated and reproduced for further analysis or applications. The algorithm is implemented as a recursive approach, which allows to potentially grow a new hyphal branch at each depth level. The angle of curvature, frequency of new branching, and piercing (in the alveolus) is also parameterized, making it highly adaptable for different scenarios. Interactions with immune cells (alveolar macrophages) is realized according to the set of rules within the agent-based modeling.
Hyphal growth simulation
Publications
Organ-on-chip models for infectious disease research.
Alonso-Roman R, Mosig AS, Figge MT, Papenfort K, Eggeling C, Schacher FH, Hube B, Gresnigt MS
Research on microbial pathogens has traditionally relied on animal and cell culture models to mimic infection processes in the host. Over recent years, developments in microfluidics and bioengineering have led to organ-on-chip (OoC) technologies. These microfluidic systems create conditions that are more physiologically relevant and can be considered humanized in vitro models. Here we review […]
Deep learning-based characterization of neutrophil activation phenotypes in ex vivo human Candida blood infections.
Sarkar A, Praetorius JP, Figge MT#
Early identification of human pathogens is crucial for the effective treatment of bloodstream infections to prevent sepsis. Since pathogens that are present in small numbers are usually difficult to detect directly, we hypothesize that the behavior of the immune cells that are present in large numbers may provide indirect evidence about the causative pathogen of […]
Modeling of intravenous caspofungin administration using an intestine-on-chip reveals altered Candida albicans microcolonies and pathogenicity.
Kaden T*, Alonso-Roman R*, Akbarimoghaddam P*, Mosig AS, Graf K, Raasch M, Hoffmann B, Figge MT#, Hube B#, Gresnigt MS#
Candida albicans is a commensal yeast of the human intestinal microbiota that, under predisposing conditions, can become pathogenic and cause life-threatening systemic infections (candidiasis). Fungal-host interactions during candidiasis are commonly studied using conventional 2D in vitro models, which have provided critical insights into the pathogenicity. However, microphysiological models with a higher biological complexity may be […]