Characterization of Aspergillus fumigatus secretome during sublethal infection of Galleria mellonella larvae.

Introduction. The fungal pathogen Aspergillus fumigatus can induce prolonged colonization of the lungs of susceptible patients, resulting in conditions such as allergic bronchopulmonary aspergillosis and chronic pulmonary aspergillosis.Hypothesis. Analysis of the A. fumigatus secretome released during sub-lethal infection of G. mellonella larvae may give an insight into products released during prolonged human colonisation.Methodology. Galleria mellonella larvae were infected with A. fumigatus, and the metabolism of host carbohydrate and proteins and production of fungal virulence factors were analysed. Label-free qualitative proteomic analysis was performed to identify fungal proteins in larvae at 96 hours post-infection and also to identify changes in the Galleria proteome as a result of infection.Results. Infected larvae demonstrated increasing concentrations of gliotoxin and siderophore and displayed reduced amounts of haemolymph carbohydrate and protein. Fungal proteins (399) were detected by qualitative proteomic analysis in cell-free haemolymph at 96 hours and could be categorized into seven groups, including virulence (n = 25), stress response (n = 34), DNA repair and replication (n = 39), translation (n = 22), metabolism (n = 42), released intracellular (n = 28) and cellular development and cell cycle (n = 53). Analysis of the Gallerial proteome at 96 hours post-infection revealed changes in the abundance of proteins associated with immune function, metabolism, cellular structure, insect development, transcription/translation and detoxification.Conclusion. Characterizing the impact of the fungal secretome on the host may provide an insight into how A. fumigatus damages tissue and suppresses the immune response during long-term pulmonary colonization.

"Individualized learning in a course with a tight schedule".

The article presents a solution supporting individualised learning in courses with a tight schedule. Such courses pose additional organisational challenges and require appropriate tools. The presented solution is based on an Intelligent Tutoring System immersed in repository of e-learning content, which enables selection of content immediately before its provision to the student instead of at the beginning of a course. Thanks to this, the system, having identified the student's needs, is able to make available the most suitable repository content at a given stage of education. The flexibility of the system is guaranteed by modularisation of content and its logical division using the UCTS taxonomy. The content has been described by means of concepts arranged according to the specificity of the domain to which the resources belong in order to ensure that the ITS is able to select relevant content. The proposed solution was used to set up an Applications of Fuzzy Logic course, which was part of an Artificial Intelligence class. The course was conducted within a very limited time frame resulting from the COVID-19 epidemic.