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Abstract Background Trace elements play a crucial role in fish nutrition, with zinc (Zn) being one of the most important elements. BIO-sourced zinc nanoparticles were synthesized using the green microalga Pediastrum boryanum (BIO-ZnNPs, 29.35 nm). 30 or 60 mg/ kg dry feed of the BIO-ZnNPs (BIO-ZnNPs30 and BIO-ZnNPs60) were mixed with the Nile tilapia (Oreochromis niloticus) basal diet and fed to the fish for 8 weeks to evaluate their impact on fish growth, digestion, intestinal integrity, antioxidative status, and immunity. Results A significant enhancement was observed in all investigated parameters, except for the serum protein profile. BIO-ZnNPs at 60 mg/kg feed elevated the activities of reduced glutathione (GSH) and catalase (CAT), enzymatic antioxidants, but did not induce oxidative stress as reflected by no change in MDA level. Fish intestinal immunity was improved in a dose-dependent manner, in terms of improved morphometry and a higher count of acid mucin-producing goblet cells. Interleukin-8 (IL-8) was upregulated in BIO-ZnNPs30 compared to BIO-ZnNPs60 and control fish groups, while no significant expressions were noted in tumor necrosis factor-alpha (TNFα), nuclear factor kappa B (NF k B), and Caspase3 genes. Conclusion Overall, BIO-ZnNPs inclusion at 60 mg/kg feed showed the most advantage in different scenarios, compared to BIO-ZnNPs at 30 mg/kg feed. The positive effects on growth and intestinal health suggest that BIO-ZnNPs supplementation of aquafeeds has many benefits for farmed fish.

We proposed a new computational methodology for computational modeling of mass transfer in membranes with application for molecular separation. The computational method centered on hybrid computational fluid dynamics (CFD) and machine learning (ML) in which the data of CFD are used for training machine learning model. The case study is a polymeric membrane for removing a solute from a solution, and the mass transfer equations are solved using CFD. Therefore, the data set has two inputs: r and z which are the coordinates. Also, the single output is C which indicates the solute concentration, and the quantity of data points is more than 8,000. The data analysis and modeling in this study were carried out utilizing the Adaboost (Adaptive Boosting) model. Essentially, this model requires a base model to be built, and in this case, we have chosen three models to build this model, namely Decision Trees (DT), Theil-Sen Regressions (TS), and Support Vector Regressions (SVR), and compared their results. The coefficient of determination (R2) of boosted DT, TS, and SVR are 0.9978, 0.9171, and 0.9908 respectively. Also, in terms of RMSE their error values were 3.96E + 01, 3.03E + 02, and 7.99E + 01. Finally, Boosted Decision Tree model is selected as the most accurate technique for the membrane simulation. The MAE metric for this model is 1.01E + 01 and its MAPE error rate is 9.07E-03.

Bacterial infections are a global issue, causing sickness and death, mainly in developing nations. Resistance to current medicines is a significant issue in healthcare. Overcoming the resistance problem will necessitate the development of molecules with novel modes of action that do not cross-react with existing medicines. Synthesis of new bis-heterocycles linked to the piperazine core and vanillin unit is disclosed in this regard. The target compounds were produced via the reaction of 4,4′-((piperazine-1,4-diylbis(2-oxoethane-2,1-diyl))bis(oxy))bis(3-methoxybenzaldehyde) with various reagents using the Hantzsch, Biginelli, and Michael’s reactions. All the generated compounds were tested for their antibacterial activity against a variety of bacterial strains. The antibacterial activity evaluations revealed that compound 32 has the most promising activity against Pseudomonas aeruginosa (19.5 ± 0.7 mm) compared to Ofloxacin (17 mm) with minimum inhibitory concentration (MIC) equaled to 625 µg/mL. A molecular docking investigation revealed that compound 32 had the greatest binding affinity for bacterial enoyl reductase (−36.13 ± 0.2 Kcal/mole) when compared to the co-crystallized ligand (−16.8 ± 0 Kcal/mole).

Abstract Background Feed supplements, including essential trace elements are believed to play an important role in augmenting fish immune response. In this context, selenium nanoparticles (SeNPs) in fish diets via a green biosynthesis strategy have attracted considerable interest. In this investigation, selenium nanoparticles (SeNPs, 79.26 nm) synthesized from the green microalga Pediastrum boryanum were incorporated into Nile tilapia diets to explore its beneficial effects on the immune defense and intestinal integrity, in comparison with control basal diets containing inorganic Se source. Nile tilapia (No. 180, 54–57 g) were fed on three formulated diets at concentrations of 0, 0.75, and 1.5 mg/kg of SeNPs for 8 weeks. After the trial completion, tissue bioaccumulation, biochemical indices, antioxidant and pro-inflammatory cytokine-related genes, and intestinal histological examination were analyzed. Results Our finding revealed that dietary SeNPs significantly decreased (P

The reaction of sulfamethoxazolehydrazonoyl chloride with thiosemicarbazones, bis-thiosemicarbazones, or 4-amino-3-mercapto-1,2,4-triazole in dioxane in the presence of triethylamine as a basic catalyst at reflux resulted in the regioselective synthesis of thiazoles and bis-thiazoles linked to azo-sulfamethoxazole as novel hybrid molecules. The structures of the new compounds were confirmed using a range of spectra. Each compound's antibacterial properties were evaluated using the agar well-diffusion technique, and most of them demonstrated significant potency. In silico investigations revealed that the described compounds had strong interactions with the binding sites of MurE ligase, tyrosyl-tRNA synthetase, and dihydropteroate synthase, demonstrating inhibitory activity.

The present study was designed to improve the aqueous solubility and dissolution rate of citreorosein, a poorly water soluble drug, by producing its nanoparticles (NPs) using an “antisolvent precipitation with a syringe pump” (APSP) method. Various process parameters including flow rate, stirring speed, temperature, drug concentration and solvent-antisolvent ratio were investigated and optimized to obtain the smallest particle size of citreorosein. The prepared NPs were subjected to different analytical techniques such as SEM, FTIR, XRD and DLS. The NPs were tested for different dissolution parameters including difference (f1) and similarity factors (f2), dissolution efficiency (DE) and mean dissolution time (MDT). The antioxidant potential of citreorosein and its NPs were evaluated using DPPH, ABTS, and FRAP models, while their cytotoxicity was tested on various cancer cell lines such as breast (MDA-MB-231), lung (A549) and liver (HepG2), using the MTT assay. The specificity of the test compound was investigated against two normal human primary epithelial cells including renal (HRPTEpiC) and alveolar (HPAEpiC) cells. DLS analysis revealed that the prepared NPs were less than 200 nm in size while SEM and XRD confirmed their rod shape and amorphous nature, respectively. Citreorosein-NPs exhibited enhanced solubility and dissolution rate in all medias as compared to pure citreorosein. The NPs displayed significant antioxidant effects against ABTS, DPPH and FRAP models, with IC50 values of22.6, 21.45 and 27.30 µg/ml, respectively. Moreover, it showed significant cytotoxic activity against MDA-MB-231, A549 and HepG2 cells, with IC50 values of 3.45, 4.5 and 6.23 µg/ml, respectively. Furthermore, the NPs demonstrated high selectivity index values for the aforementioned cell lines as compared to reference drugs. This study demonstrated that APSP method successfully produced citreorosein-NPs and hence, showed better aqueous solubility, dissolution rate, antioxidant and cytotoxic activities than the pure compound.