Multivariate optimization of process parameters in the synthesis of calcined Ca‒Al (NO3) LDH for defluoridation using 3(3) factorial, central composite and Box-Behnken design

Development of A Nanostructured Lipid Carrier-Based Drug Delivery Strategy for Apigenin: Experimental Design Based on CCD-RSM and Evaluation against NSCLC In Vitro

Non-small-cell lung cancer (NSCLC) is the main cause of cancer-related deaths worldwide, with a low five-year survival rate, posing a serious threat to human health. In recent years, the delivery of antitumor drugs using a nanostructured lipid carrier (NLC) has become a subject of research. This study aimed to develop an apigenin (AP)-loaded nanostructured lipid carrier (AP-NLC) by melt sonication using glyceryl monostearate (GMS), glyceryl triacetate, and poloxamer 188. The optimal prescription of AP-NLC was screened by central composite design response surface methodology (CCD-RSM) based on a single-factor experiment using encapsulation efficiency (EE%) and drug loading (DL%) as response values and then evaluated for its antitumor effects on NCI-H1299 cells. A series of characterization analyses of AP-NLC prepared according to the optimal prescription were carried out using transmission electron microscopy (TEM), differential scanning calorimetry (DSC), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FT-IR). Subsequent screening of the lyophilization protectants revealed that mannitol could better maintain the lyophilization effect. The in vitro hemolysis assay of this formulation indicated that it may be safe for intravenous injection. Moreover, AP-NLC presented a greater ability to inhibit the proliferation, migration, and invasion of NCI-H1299 cells compared to AP. Our results suggest that AP-NLC is a safe and effective nano-delivery vehicle that may have beneficial potential in the treatment of NSCLC.

Optimization of the Synthesis of Fungus-Mediated Bi-Metallic Ag-Cu Nanoparticles

Bi-metallic nanoparticles (NPs) have appeared to be more efficient as antimicrobials than mono-metallic NPs. The fungus Aspergillus terreus-mediated synthesis of bi-metallic Ag-Cu NPs was optimized using response surface methodology (RSM) to reach the maximum yield of NPs. The optimal conditions were validated using ANOVA. The optimal conditions were 1.5 mM total metal (Ag + Cu) concentration, 1.25 mg fungal biomass, 350 W microwave power, and 15 min reaction time. The structure and shape of the synthesized NPs (mostly 20–30 nm) were characterized using several analytical tools. The biological activities of the synthesized NPs were assessed by studying their antioxidant, antibacterial, and cytotoxic activity in different NP concentrations. A dose-dependent response was observed in each test. Bi-metallic Ag-Cu NPs inhibited three clinically relevant human pathogens: Klebsiella pneumoniae, Enterobacter cloacae, and Pseudomonas aeruginosa. Escherichia coli, Enterococcus faecalis, and Staphylococcus aureus were inhibited less. The DPPH and hydrogen peroxide scavenging activities of the NPs were high, reaching 90% scavenging. Ag-Cu NPs could be studied as antimicrobials in different applications. The optimization procedure using statistical analyses was successful in improving the yield of nanoparticles.

A novel framework of multivariate modeling of water distribution network through 33 factorial design and artificial neural network

The water distribution network is largely affected by the change in the influencing factors, such as input pressure, demand and supply duration. The change in each parameter requires the extensive design of the network and the interactive effect of the influencing parameters are hardly explored. The main hurdles for the water providers lie in the absence of a prediction model, which can be used as a decision tool to assess the effect of the change in parameter and estimating the cost for the changed scenario. The present study developed a novel framework based on the artificial neural network for multivariate prediction modeling taking the response as the cost of the pipe network. The application of the 3³ factorial design was used for the selection of the influencing parameters and outcome was taken as the input to the neural network model. The adequacy of the model was tested through error functions and analysis of variance. The low values of the error functions (0.0004-0.228) and high F value (162,442) and R² (0.999) established the significance of the model. The model can be used for predicting the cost of the changed scenarios and assessment of the optimal solution for the system variables.

Sorptive equilibrium profile of fluoride onto aluminum olivine [(FexMg1-x)2SiO4] composite (AOC): Physicochemical insights and isotherm modeling by non-linear least squares regression and a novel neural-network-based method

A novel aluminum/olivine composite (AOC) was prepared by wet impregnation followed by calcination and was introduced as an efficient adsorbent for defluoridation. The adsorption of fluoride was modeled with one-, two- and three-parameter isotherm equations by non-linear regression to demonstrate the adsorption equilibrium. The FI was the best-fitted model among the two-parameter isotherms with a R² value of 0.995. The three-parameter models were found to have better performance with low values of the error functions and high F values. The neural-network-based model was applied for the first time in the isotherm study. The optimized model was framed with eight neurons in hidden layer with a mean square of error of 0.0481 and correlation coefficient greater than 0.999. The neural-based model has the better predictability with a higher F value of 9484 and R² value of 0.998 compared to regression models, exhibiting the F value and the R² in the range of 86-3572 and 0.835-0.995, respectively. The material characterization established the formation of the aluminum oxide, silicate, etc. onto the olivine which is conducive of the removal of fluoride by the formation of aluminum fluoride compounds, such as AlF₃ in the spent material after defluoridation.

Adsorptive removal of arsenic by novel iron/olivine composite: Insights into preparation and adsorption process by response surface methodology and artificial neural network

Olivine, a low-cost natural material, impregnated with iron is introduced in the adsorptive removal of arsenic. A wet impregnation method and subsequent calcination were employed for the preparation of iron/olivine composite. The major preparation process parameter, viz., iron loading and calcination temperature were optimized through the response surface methodology coupled with a factorial design. A significant variation of adsorption capacity of arsenic (measured as total arsenic), i.e., 63.15 to 310.85 mg/kg for arsenite [As(III)^T] and 76.46 to 329.72 mg/kg for arsenate [As(V)^T] was observed, which exhibited the significant effect of the preparation process parameters on the adsorption potential. The iron loading delineated the optima at central points, whereas a monotonous decreasing trend of adsorption capacity for both the As(III)^T and As(V)^T was observed with the increasing calcination temperature. The variation of adsorption capacity with the increased iron loading is more at lower calcination temperature showing the interactive effect between the factors. The adsorbent prepared at the optimized condition of iron loading and calcination temperature, i.e., 10% and 200 °C, effectively removed the As(III)^T and As(V)^T by more than 96 and 99%, respectively. The material characterization of the adsorbent showed the formation of the iron compound in the olivine and increase in specific surface area to the tune of 10 multifold compared to the base material, which is conducive to the enhancement of the adsorption capacity. An artificial neural network was applied for the multivariate optimization of the adsorption process from the experimental data of the univariate optimization study and the optimized model showed low values of error functions and high R² values of more than 0.99 for As(III)^T and As(V)^T. The adsorption isotherm and kinetics followed Langmuir model and pseudo second order model, respectively demonstrating the chemisorption in this study.

Magnetic Solid-phase Extraction with Fe₃O₄/Molecularly Imprinted Polymers Modified by Deep Eutectic Solvents and Ionic Liquids for the Rapid Purification of Alkaloid Isomers (Theobromine and Theophylline) from Green Tea

Different kinds of deep eutectic solvents (DES) based on choline chloride (ChCl) and ionic liquids (ILs) based on 1-methylimidazole were used to modify Fe3O4/molecularly imprinted polymers (Fe3O4/MIPs), and the resulting materials were applied for the rapid purification of alkaloid isomers (theobromine and theophylline) from green tea with magnetic solid-phase extraction (M-SPE). The M-SPE procedure was optimized using the response surface methodology (RSM) to analyze the maximum conditions. The materials were characterized by Fourier transform infrared spectroscopy (FI-IR) and field emission scanning electron microscopy (FE-SEM). Compared to the ILs-Fe3O4/MIPs, the DESs-Fe3O4/MIPs were developed for the stronger recognition and higher recoveries of the isomers (theophylline and theobromine) from green tea, particularly DES-7-Fe3O4/MIPs. With RSM, the optimal recovery condition for theobromine and theophylline in the M-SPE were observed with ratio of methanol (80%) as the washing solution, methanol/acetic acid (HAc) (8:2) as the eluent at pH 3, and an eluent volume of 4 mL. The practical recoveries of theobromine and theophylline in green tea were 92.27% and 87.51%, respectively, with a corresponding actual extraction amount of 4.87 mg•g-1 and 5.07 mg•g-1. Overall, the proposed approach with the high affinity of Fe3O4/MIPs might offer a novel method for the purification of complex isomer samples.

An insight into thermodynamics of adsorptive removal of fluoride by calcined Ca–Al–(NO3) layered double hydroxide

A framework for determination of thermodynamic equilibrium constant and Gibbs free surface energy change was presented. The interactive effect of temperature on adsorption process was addressed by RSM. Endothermic, spontaneous reaction was observed.