Anti-Cancer and Anti-Oxidant Bioactive Metabolites from Aspergillus fumigatus WA7S6 Isolated from Marine Sources: In Vitro and In Silico Studies.

Cancer is a huge global disease burden. Every year, tens of millions of people worldwide are diagnosed with cancer, and more than half of them die as a result of it. The great biodiversity of the marine environment has increasingly piqued the interest of experts, especially in the field of drug discovery. The marine fungus Aspergillus fumigatus WA7S6 has been selected among a group of fungi isolated from marine sponges as it exhibits a pronounced antimicrobial activity toward a group of pathogenic microbes. The fungus has been identified genetically by amplification and analysis of its 18srRNA gene. The fungus crude extract has been obtained by cultivation of the fungus on rice media. The crude extract was tested for antibacterial activity against a variety of pathogenic microorganisms. The results demonstrated a pronounced antimicrobial action against P. aeruginosa, S. aureus, A. niger, and Candida albicans. Furthermore, we tested the antioxidant potential of the Aspergillus fumigatus WA7S6 crude extract using three different methods: ATBS, DPPH, and lipid peroxidation assays. Results showed that the crude extract WA7S6 had an IC50 value of 21.35 µg/mL. The anticancer potential of the crude extract was also evaluated against cancer cell lines such as Hela, MCF, and WI-38. The chemical profiling of the fungus extract was identified via GC-mass and in silico molecular docking of the identified compounds on heme oxygenase, as a stress protein included in cellular protection, antioxidant, and anti-inflammatory activities, suggesting that some compounds, such as 9-Tetradecynoic acid, 11-Hexadecynoic acid, methyl ester, and dehydromevalonic lactone, could be relevant for antioxidant purposes.

On the Extended Generalized Inverted Kumaraswamy Distribution.

In this work, we provide a new generated class of models, namely, the extended generalized inverted Kumaraswamy generated (EGIKw-G) family of distributions. Several structural properties (survival function (sf), hazard rate function (hrf), reverse hazard rate function (rhrf), quantile function (qf) and median, s th raw moment, generating function, mean deviation (md), etc.) are provided. The estimates for parameters of new G class are derived via maximum likelihood estimation (MLE) method. The special models of the proposed class are discussed, and particular attention is given to one special model, the extended generalized inverted Kumaraswamy Burr XII (EGIKw-Burr XII) model. Estimators are evaluated via a Monte Carlo simulation (MCS). The superiority of EGIKw-Burr XII model is proved using a lifetime data applications.