In silico methods such as molecular docking and molecular dynamic (MD) simulations have significant interest due to their ability to identify the protein-ligand interactions at the atomic level. In this work, different computational methods were used to elucidate the ability of some olive oil components to act as Neisseria adhesion A Regulatory protein (NadR) inhibitors. The frontier molecular orbitals (FMOs) and the global properties such as global hardness, electronegativity, and global softness of ten olive oil components (a-Tocopherol, Erythrodiol, Hydroxytyrosol, Linoleic acid, Apigenin, Luteolin, Oleic acid, Oleocanthal, Palmitic acid, and Tyrosol) were reported using Density Functional Theory (DFT) methods. Among all investigated compounds, Erythrodiol, Apigenin, and Luteolin demonstrated the highest binding affinities (
8.72,
7.12, and
8.24 kcal/mol, respectively) against NadR, compared to
8.21 kcal/mol of the native ligand based on molecular docking calculations. ADMET properties and physicochemical features showed that Erythrodiol, Apigenin, and Luteolin have good physicochemical features and can act as drugs candidate. Molecular dynamics (MD) simulations demonstrated that Erythrodiol, Apigenin, and Luteolin show stable binding affinity and molecular interaction with NadR. Further Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) analyses using the MD trajectories also demonstrated the higher binding affinity of Erythrodiol, Apigenin and Luteolin inside NadR protein. The overall study provides a rationale to use Erythrodiol, Apigenin, and Luteolin in the drug development as anti-adhesive drugs lead. Abbreviations: DFT: Density Functional Theory; MD simulation: Molecular dynamic simulation; FMOs: The frontier molecular orbitals; ADMET: Absorption, distribution, metabolism, excretion and toxicity properties; NadR: Neisseria adhesion A Regulatory protein; 4-HPA: 4-Hydroxyphenylacetic acid; MMPBSA: Molecular Mechanics Poisson-Boltzmann Surface Area

Ternary alloys of Zn_0.78Cd_0.22S nanoparticles (NPs) are synthesized via the facile co-precipitation technique. The as-synthesized sample exhibits a zincblende-type cubic phase with an average crystalline size of 2 nm. Thermal annealing and UV irradiation are utilized as post-treatment processes for tailoring the optical properties of Zn_0.78Cd_0.22S NPs. The as-synthesized sample exhibits a stable cubic phase up to 400 °C, during which partial phase transformation to a hexagonal structure is observed at a higher temperature of 500 °C. The oxidation of Zn_0.78Cd_0.22S NPs to mixed oxide phases with the majority of ZnO begins at 600 °C which induces morphology transformation to a relatively large nano-hexagon with a single crystalline domain size. The increase of the annealing temperature is accompanied by a decrease of Zn_0.78Cd_0.22S NPs optical band gap (E_g) due to the weakness of size confinement as well as the formation of localized states below the mobility band edges. The brief UV irradiation results in the increase of E_g whereas a further increase in exposure time is accompanied by a reduction of E_g. The photoluminescence (PL) spectrum of the as-synthesized sample covers a wide spectral range from UV to visible. Thermal annealing has a slight effect on the PL emission at high excitation energy, whereas low excitation energy reveals higher sensitivity to deep-state emission. Thermal oxidation incorporates a high concentration of oxygen-related defects that induce strong enhancement in the green emission at the expense of UV emission. This indicates the thermal-induced bleaching of shal

The unique properties of aluminum (Al) and its alloys make Al one of the most versatile, economical, and widely-used materials in various industries. However, the corrosion and leaching of Al can cause significant issues for the lifetimes of mechanical structures and machine components as well as environment and health problems. In the present study, a simple, eco-friendly, and rapid fabrication of superhydrophobic Al surfaces was introduced. The superhydrophobic Al surfaces with hierarchical composite structures combining microstructures prepared by laser texturing, the new formation of pseudo-boehmite nanostructures prepared by boiling water treatment, and low surface energy prepared by silicone oil heat treatment showed excellent corrosion resistance. The mechanism for wettability change and anti-corrosion were analyzed. The influence of laser parameters and surface modification procedures on the wettability and corrosion resistance of Al surfaces was also analyzed systematically through a series of surface characterization techniques, potentiodynamic polarization tests, and electrochemical impedance spectroscopy tests. The corrosion protection efficiency of the fabricated superhydrophobic Al surface has reached up to 99.40 % as compared with an untreated flat surface. Furthermore, the fabricated superhydrophobic surfaces show good stability even after prolonged exposure to air, fresh water, seawater, and high temperature environments. The performance of the non-wetting surfaces is demonstrated through self-cleaning, water jetting, and water droplet bouncing phenomena. This research provides a novel and sustainable approach for superhydrophobic metal surfaces and improved corrosion resistance for potential practical applications.

Recently, fish parasites have been used as a biomonitoring tool to indicate the health status of ecosystems. Therefore, this research aimed to evaluate the potential capacity of Contracaecum quadripapillatum larvae as accumulation indicators for metal pollution and compare metal concentrations in host tissues of non-infected and infected fish: Lates niloticus from the Nile River. Accumulations of Cd, Cu, Fe, Mn, Ni, Pb, and Zn in larval nematodes and tissues of the liver, kidney, and muscles of both infected and non-infected fish were determined. All metal concentrations exhibit a significantly higher increase in larval nematodes than the muscles of infected fish and vice versa except Cd in the kidney. On the other hand, only Cd, Mn, Pb, and Zn concentrations were significantly higher in the parasite than in the host liver. Therefore, bioaccumulation factors were most obvious and effective in the muscles of infected 

Designing molecules for drugs has been a hot topic for many decades. However, it is hard and expensive to find a new molecule. Thus, the cost of the final drug is also increased. Machine learning can provide the fastest way to predict the biological activity of druglike molecules. In the present work, machine learning models are trained for the prediction of the biological activity of aromatase inhibitors. Data was collected from the literature. Molecular descriptors are calculated to be used as independent features for model training. The results showed that the R² values for linear regression, random forest regression, gradient boosting regression, and bagging regression are 0.58, 0.84, 0.77, and 0.80, respectively. Using these models, it is possible to predict the activity of new molecules in a short period of time and at a reasonable cost. Furthermore, Tanimoto similarity is used for similarity analysis, as well as a

Here a developed one-dimensional (1D) topological photonic crystal (PC) heterostructure for gas sensing is proposed by replacing air layers with the sensing material (gas) layers. Two promising sensing devices are proposed in the present study. In the first device, all air layers are replaced with gas layers, while only the interface layer is replaced in the second device. Accordingly, these two detection mechanisms make the proposed sensor a novel detector for low and high-refractive index gases. The proposed structure achieves numerically high values of all features sensor parameters, eg, high sensitivity of 888.285 n m/R I U and 806.658 n m/R I U of two modes, respectively, high-quality factor values reached 10 5. The figure of merit is higher than 10 5 R I U− 1 with a perfect value of detection limit around 10− 6 R I U. The proposed sensor supplies a potential platform to push the current technology's ability to …