Computers in biology and medicine · 2018
Aspergillus fumigatus branching complexity in vitro: 2D images and dynamic modeling.
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Rajković Katarina M, Milošević Nebojša T, Otašević Suzana, Jeremić Sanja, Arsenijević Valentina Arsić
Аннотация
BACKGROUND: Aspergillus fumigatus causes serious infections in humans, and its virulence correlates with hyphal growth, branching and formation of the filamentous mycelium. The filamentous mycelium is a complex structure inconvenient for quantity analysis. In this study, we monitored the branching of A. fumigatus filamentous mycelium in vitro at different points in time in order to assess the complexity degree and develop a dynamic model for the branching complexity.
METHOD: We used fractal analysis of microscopic images (FAMI) to measure the fractal dimensions (D) of the branching complexity within 24 h of incubation.
RESULTS: By photographing the filamentous mycelium dynamically and processing the images, the D variation curve of A. fumigatus complexity degree was obtained. We acquired the D variation curve which contained initial exponential period and stationary period of A. fumigatus branching. Further, the obtained data of D was modeled via the logistic model (LM) to develop a dynamic model of A. fumigatus branching for the prediction of the specific growth rate of branching value (0.23 h-1).
CONCLUSIONS: Developed FAMI and LM models present a simple and non-destructive method of predicting the evolution of branching complexity of A. fumigatus. These models are useful as laboratory measurements for the prediction of hyphal and mycelium development, especially relevant to the pathogenesis study of aspergillosis, as well as pathogenesis of other diseases caused by moulds.
METHOD: We used fractal analysis of microscopic images (FAMI) to measure the fractal dimensions (D) of the branching complexity within 24 h of incubation.
RESULTS: By photographing the filamentous mycelium dynamically and processing the images, the D variation curve of A. fumigatus complexity degree was obtained. We acquired the D variation curve which contained initial exponential period and stationary period of A. fumigatus branching. Further, the obtained data of D was modeled via the logistic model (LM) to develop a dynamic model of A. fumigatus branching for the prediction of the specific growth rate of branching value (0.23 h-1).
CONCLUSIONS: Developed FAMI and LM models present a simple and non-destructive method of predicting the evolution of branching complexity of A. fumigatus. These models are useful as laboratory measurements for the prediction of hyphal and mycelium development, especially relevant to the pathogenesis study of aspergillosis, as well as pathogenesis of other diseases caused by moulds.