Artificial Neural Network Prediction of Antiadhesion and Antibiofilm-Forming Effects of Antimicrobial Active Mushroom Extracts on Food-Borne Pathogens

Synergism of Computational Simulation Technique and Machine Learning Algorithm for Prediction of Anticorrosion Properties of Some Antipyrine Derivatives

This study aimed to predict the selected antipyrine compounds' inhibitory efficiencies and anticorrosion properties in a hydrochloric acid (HCl) environment. Molecular descriptors and input variables were obtained using density functional theory (DFT), and the variance inflation factor (VIF) was employed to reduce redundant variables, leading to the selection of seven quantum chemical descriptors as input variables. Using machine learning techniques such as K-nearest neighbor (KNN) and artificial neural network (ANN), a predictive model was built for 39 antipyrine compounds with known corrosion inhibition efficiencies for carbon and low alloy steel in hydrochloric acid solutions. The models' predictive capability was assessed using cross-validation, with the ANN model showing superior performance, achieving a coefficient of determination (R2) value of 0.715 compared to 0.548 for the KNN model. Performance metrics such as the mean square error (MSE), mean absolute error (MAE), and root-mean-square error (RMSE) further confirmed the superiority of the ANN model over the KNN model. The corrosion inhibition efficiencies (CIEs) of the selected antipyrine compounds ranged from 68.78 to 99.79%, with compound A1 demonstrating the highest CIE of 99.79% and compound A3 the lowest, as evaluated by the ANN model. Analysis of Fukui index parameters obtained from the Mulliken population analysis suggested that the nucleophilic and electrophilic sites play a crucial role in the interactions between the inhibitor and the metal atom through electron donor-acceptor interactions. Moreover, the energy of adsorption (Eads) in kcal·mol-1 decreased in the order of A1 (-187.8) > A2 (-132.0) > A2 (-84.4), with the high negative value of Eads indicating strong and spontaneous adsorption. Further analysis using radial distribution functions and molecular dynamics simulations revealed that inhibitor A1 exhibited predominantly chemisorption, inhibitor A2 showed a mixed type, and inhibitor A3 demonstrated predominantly physisorption, aligning well with the results of the predictive studies.

An Eco-friendly Approach to ZnO NP Synthesis Using Citrus reticulata Blanco Peel/Extract: Characterization and Antibacterial and Photocatalytic Activity

Emission of greenhouse gases and infectious diseases caused by improper agro-waste disposal has gained significant attention in recent years. To overcome these hurdles, agro-waste can be valorized into valuable bioactive compounds that act as reducing or stabilizing agents in the synthesis of nanomaterials. Herein, we report a simple circular approach using Citrus reticulata Blanco (C. reticulata) waste (peel powder/aqueous extract) as green reducing and capping/stabilizing agents and Zn nitrate/acetate precursors to synthesize ZnO nanoparticles (NPs) with efficient antimicrobial and photocatalytic activities. The obtained NPs crystallized in a hexagonal wurtzite structure and differed clearly in their morphology. UV-vis analysis of the nanoparticles showed a characteristic broad absorption band between 330 and 414 nm belonging to ZnO NPs. Fourier transform infrared (FTIR) spectroscopy of ZnO NPs exhibited a Zn-O band close to 450 cm-1. The band gap values were in the range of 2.84-3.14 eV depending on the precursor and agent used. The crystallite size obtained from size-strain plots from measured XRD patterns was between 7 and 26 nm, with strain between 16 and 4%. The highly crystalline nature of obtained ZnO NPs was confirmed by clear ring diffraction patterns and d-spacing values of the observed lattice fringes. ZnNPeelMan_400 and ZnNExtrMan showed good stability, as the zeta potential was found to be around -20 mV, and reduced particle aggregation. Photoluminescence analysis revealed different defects belonging to oxygen vacancies (VO+ and VO+2) and zinc interstitial (Zni) sites. The presence of oxygen vacancies on the surface of ZnAcExtrMan_400 and ZnAcPeelMan_400 increased antimicrobial activity, specifically against Gram-negative bacteria Escherichia coli (E. coli) and Salmonella enteritidis (S. enteritidis). ZnNExtrMan with a minimal inhibitory concentration of 0.156 mg/mL was more effective against Gram-positive bacteria Staphylococcus aureus (S. aureus), revealing a high influence of particle size and shape on antimicrobial activity. In addition, the photocatalytic activity of the ZnO NPs was examined by assessing the degradation of acid green dye in an aqueous solution under UV light irradiation. ZnAcPeelMan_400 exhibited excellent photocatalytic activity (94%) within 90 min after irradiation compared to other obtained ZnO NPs.

Bioprospecting of Selected Species of Polypore Fungi from the Western Balkans

Growing mushrooms means meeting challenges while aiming for sustainability and circularity. Wherever the producer is located, commercial strains are the same originating from several producers. Customized strains adapted to local conditions are urgently needed. Before introducing new species to the strain development pipeline, the chemical characterization and biological activity of wild ones need to be assessed. Accordingly, the mycoceutical potential of five polypore mushroom species from Serbia was evaluated including: secondary metabolite composition, oxidative damage prevention, anti-tyrosinase, and anti-angiotensin converting enzyme (ACE). The phenolic pattern was comparable in all samples, but the amounts of specific chemicals varied. Hydroxybenzoic acids were the primary components. All samples had varying quantities of ascorbic acid, carotene, and lycopene, and showed a pronounced inhibition of lipid peroxidation (LPx) and ability to scavenge HO•. Extracts were more potent tyrosinase inhibitors but unsuccessful when faced with ACE. Fomitopsis pinicola had the strongest anti-tumor efficacy while Ganoderma lucidum demonstrated strong selectivity in anti-tumor effect in comparison to normal cells. The evaluated species provided a solid foundation for commercial development while keeping local ecology in mind.