Wheat bran as an efficient agro-process waste for enhanced yellow laccase production by Lentinus tigrinus SSB_W2 and its application in anthraquinone dye degradation

Lentinus tigrinus SSB_W2, isolated from Mahabaleshwar in the Western Ghats of Maharashtra, India, was employed to enhance laccase production in solid-state fermentation (SSF). The spectral analysis indicated that the laccase produced by L. tigrinus is a typical yellow laccase, exhibiting no absorption at 600 nm. Notably, this yellow laccase demonstrated exceptional catalytic activity, as confirmed by electrochemical analysis. Four agricultural processing wastes were evaluated as substrates for SSF, and the results showed that L. tigrinus effectively utilized wheat bran. Initial testing by one-factor-at-a-time method showed 3.79-fold increase in yellow laccase production, which subsequently increased to 6.51-fold after Plackett-Burman design. Moreover, employing response surface methodology resulted in 11.87-fold increase (108,472 IU gds-1) in laccase production. The utilization of yellow laccase for the biotransformation of various textile dyes was investigated, and it exhibited the highest degradation efficiency toward Reactive blue 4, a recalcitrant anthraquinone dye, with a rate of 18.36 mg L-1 h-1, for an initial concentration of 1000 mg L-1.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03881-9.

Triptolide nanoemulsion gel as a transdermal drug delivery system: preparation, pharmacokinetics, and rheumatoid arthritis evaluation

PURPOSE

This study aimed to develop and evaluate triptolide nanoemulsion gels (TP-NE gels) as a transdermal drug delivery system.

METHODS

TP-NE was prepared and optimized via emulsification and the central composite design response surface method. The optimized TP-NE gel was evaluated in vitro and in vivo. TP-NE gel microstructure, in vitro and in vivo pharmacokinetics, and anti-rheumatoid arthritis effects were studied to evaluate the feasibility of its percutaneous administration.

RESULTS

The Optimized TP-NE was observed using a Malvern Autosizer Nano ZS 90 inspection system and a transmission electron microscope (TEM). The nanoemulsion had an average size of 162.9 ± 0.281 nm, a polydispersity index of 0.272 ± 0.024, a zeta potential of -30.03 ± 2.01 mV, and mostly spherical and uniform morphology. In addition, the TP-NE gel pharmacokinetics, assessed via a skin-blood two-site synchronous microdialysis, revealed that TP was higher in the skin than in the blood. TP-NE gel is crucial in reducing knee edema, inhibiting inflammation, and treating rheumatoid arthritis by regulating tumor necrosis factor-alpha, interleukin-1β, and -6 levels.

CONCLUSION

The TP-NE gel is a promising local delivery method for rheumatoid arthritis (RA)-associated edema and inflammation and can serve as a prospective platform for percutaneous TP administration.

Optimization of adsorption performance of cerium-loaded intercalated bentonite by CCD-RSM and GA-BPNN and its application in simultaneous removal of phosphorus and ammonia nitrogen

Excessive phosphorus (P) and ammonia nitrogen (NH₃-N) in water bodies can lead to eutrophication of the aquatic environment. Therefore, it is important to develop a technology that can efficiently remove P and NH₃-N from water. Here, the adsorption performance of cerium-loaded intercalated bentonite (Ce-bentonite) was optimized based on single-factor experiments using central composite design-response surface methodology (CCD-RSM) and genetic algorithm-back propagation neural network (GA-BPNN) models. Based on the determination coefficient (R²), mean absolute error (MAE), mean square error (MSE), mean absolute percentage error (MAPE), and root mean square error (RMSE), the GA-BPNN model was found to be more accurate in predicting adsorption conditions than the CCD-RSM model. The validation results showed that the removal efficiency of P and NH₃-N by Ce-bentonite under optimal adsorption conditions (adsorbent dosage = 1.0 g, adsorption time = 60 min, pH = 8, initial concentration = 30 mg/L) reached 95.70% and 65.93%. Furthermore, based on the application of these optimal conditions in simultaneous removal of P and NH₃-N by Ce-bentonite, pseudo-second order and Freundlich models were able to better analyze adsorption kinetics and isotherms. It is concluded that the optimization of experimental conditions by GA-BPNN has some guidance and provides a new approach to explore adsorption performance after optimizing the conditions.

Optimization of synergistic biosorption of oxytetracycline and cadmium from binary mixtures on reed-based beads: modeling study using Brouers-Sotolongo models

The first aim of this study was to synthesize and characterize reed-based-beads (BBR), an enhanced adsorbent from Tunisian reed. The second purpose was to evaluate and optimize the BBR efficiency for the simultaneous removal of oxytetracycline (OTC) and cadmium (Cd(II)), using central composite design under response surface methodology. The third goal was to elucidate the biosorption mechanisms taking place. It was shown that under optimum conditions (4.19 g L^-1 of BBR, 165.54 μmol L^-1 of OTC, 362.16 μmol L^-1 of Cd(II), pH of 6, and 25.14-h contact time) the highest adsorption percentages (63.66% for OTC and 99.99% for Cd(II)) were obtained. It was revealed that OTC adsorption mechanism was better described by Brouers-Sotolongo fractal equation, with regression coefficient (R²) of 0.99876, and a Person's chi-square (χ²) of 0.01132. The Weibull kinetic equation better explained Cd(II) biosorption (R² = 0.99959 and χ² = 0.00194). FTIR and isotherm studies confirmed that the BBR surface was heterogeneous, and that adsorption mechanisms were better described by the Freundlich/Jovanovich equation (R² = 0.99276 and χ² = 0.04864) for OTC adsorption, and by the Brouers-Sotolongo model (R² = 0.9851 and χ² = 0.77547) for Cd(II) biosorption. Overall results indicate that, at last, the BBR lignocellulosic biocomposite beads could be considered as cost-effective and efficient adsorbent, which could be of socioeconomic and environmental relevance. Graphical abstract.

Green synthesis of bioemulsifier and exopolysaccharides by Brevibacillus borstelensis and process parameters optimization using response surface model, genetic algorithm and NSGA

Bioemulsifier and exopolysaccharides are industrially important biomolecules produced by microorganisms using green technology. They have applications in food, biomedical, pharmaceutical and cosmetic industries and hence high yield of both products becomes necessary. The current study showed that Brevibacillus borstelensis has a potential to produce bioemulsifier and exopolysaccharide simultaneously but yield of both products is limited. In this study, CCD-RSM has been used as experimental design to increase concentration of both products. Concentrations of glucose, monosodium glutamate, yeast extract and magnesium sulphate were process variables and concentrations of bioemulsifiers, exopolysaccharides and biomass were responses. 30 experimental runs were performed and the models from CCD were optimized by genetic algorithm and NSGA. The results from modelling and optimization techniques were compared along with validation of models. The predicted values from optimization techniques were better than experimental values. The study concluded that NSGA is most suitable to optimize multiple responses simultaneously when compared to RSM and genetic algorithm. The optimum conditions for production were 22 g/l glucose, 14 g/l monosodium glutamate, 6 g/l yeast extract and 0.6 g/l magnesium sulphate with maximum yield of 6.1, 17.6 and 2.8 g/l bioemulsifier, exopolysaccharide and biomass, respectively. Knowledge of optimum concentrations of carbon and nitrogen source will help to utilize industrial and agricultural wastes for production of both products. They have applications in environmental bioremediation by clearing oil spills. Bioemulsifiers also help in heavy metal removal from hazardous waste. Hence this will result in environmental bioremediation by utilization of wastes by employing products generated from wastes.

Preparation Optimization of Bovine Serum Albumin Nanoparticles and Its Application for siRNA Delivery

BACKGROUND

siRNA brings hope for cancer therapy. However, there are many obstacles for application of siRNA in clinical. Because of the excellent biocompatibility, non-toxicity and non-immunogenicity of bovine serum albumin (BSA), BSA-based nanoparticles have been widely designed as a drug carrier system.

METHODS

The optimal formula for BSA NPs preparation was investigated by central composite design response surface methodology (CCD-RSM), BSA-based survivin-siRNA delivery system (BSA NPs/siRNA) was characterized by dynamic light scattering, atomic force microscope, transmission electron microscope and Bradford method. The in vitro anti-tumor effect and mechanism of BSA NPs were investigated by confocal microscopic imaging, MTT assay, RT-qPCR and ELISA analysis. Moreover, the anti-tumor effect, distribution and biosafety of BSA NPs were studied in vivo.

RESULTS

The optimal formula for BSA NPs was settled to be 20 mg/mL for BSA concentration, 9 for pH value, 136% for crosslinking degree and 1.6 mL/min for speed of ethanol addition. BSA NPs/siRNA could remain stable at 4°C for 4 weeks and protect siRNA from degradation by RNase A. Besides, BSA NPs/siRNA could maintain a sustained release of siRNA and promote the uptake of siRNA significantly. The survivin-mRNA level and the survivin-protein level were decreased by 55% ± 1.6% and 54% ± 1.6% separately. The in vivo tumor inhibition results suggested that the tumor inhibition rate of BSA NPs/siRNA-treated group was 54% ± 12% and was similar with that of DOX-treated group (57% ± 9.2%, P > 0.05). The biosafety results confirmed that BSA NPs/siRNA could not induce significant damages to the main organs and blood in vivo.

CONCLUSION

These results demonstrated that CCD-RSM was an effective tool for preparation analysis, and the BSA NPs/siRNA was a promising system for siRNA-based gene therapy.

Encapsulation of β-Glucosidase within PVA Fibers by CCD-RSM-Guided Coelectrospinning: A Novel Approach for Specific Mogroside Sweetener Production

Siamenoside I is a rare mogroside in Siraitia grosvenorii Swingle and has become one of the target ingredients in natural sweetener production. However, the complex structure of siamenoside I has hindered its production in various ways. Here, a yeast cell that produces a specific β-glucosidase for siamenoside I conversion from mogroside V was constructed, and the enzymes were coelectrospun with poly(vinyl alcohol) followed by phenylboronic acid cross-linking to provide potential usage in the batch production process of Siamenoside I. A central composite design (CCD)-response surface methodology (RSM) was used to find the optimum coelectrospinning parameters. The pH stability and sodium dodecyl sulfate tolerance increased for the entrapped enzymes, and positive correlations between the fiber diameter and enzymatic activity were confirmed. The batch process showed an average siamenoside I production rate of 118 ± 0.08 mg L^-1 h^-1 per gram of fiber. This is the first research article showing specific siamenoside I production on enzyme-loaded electrospun fibers.

Rapid determination and optimisation of berberine from Himalayan Berberis lycium by soxhlet apparatus using CCD-RSM and its quality control as a potential candidate for COVID-19

SARS-CoV-2 (or COVID-19) has become a global risk and scientists are attempting to investigate antiviral vaccine. Berberis are important plants due to the presence of bioactive phytochemicals, especially berberine from the protoberberine group of benzylisoquinoline and recent studies have shown its potential in treating COVID-19. B. lycium Royle growing in subtropical regions of Asia had wide applications in Indian system of medicine. Rapid determination and novel optimisation method for berberine extraction has been developed by Soxhlet extraction utilising central composite design-response surface methodology (CCD-RSM). Berberine was detected by high-performance liquid chromatography (HPLC), and the highest yield (13.39%) was obtained by maintaining optimal extraction conditions i.e., extraction time (7.28 hrs), ethyl alcohol (52.21%) and solvent to sample ratio (21.78 v/w). Investigation of two geographic regions (Ramnagar and Srinagar) showed high berberine content in lower altitude. This novel optimisation technique has placed berberine as a potential candidate for developing pharmaceutical products for human health care.

Optimization of process parameters for improved chitinase activity from Thermomyces sp. by using artificial neural network and genetic algorithm

Chitinase is responsible for the breaking down of chitin to N-acetyl-glucosamine units linked through (1-4)-glycosidic bond. The chitinases find several applications in waste management and pest control. The high yield with characteristics thermal stability of chitinase is the key to their industrial application. Therefore, the present work focuses on parameter optimization for chitinase production using fungus Thermomyces lanuginosus MTCC 9331. Three different optimization approaches, namely, response surface methodology (RSM), artificial neural network (ANN) and genetic algorithm (GA) were used. The parameters under study were incubation time, pH and inoculum size. The central composite design with RSM was used for the optimization of the process parameters. Further, results were validated with GA and ANN. A multilayer feed-forward algorithm was performed for ANN, i.e., Levenberg-Marquardt, Bayesian Regularization, and Scaled Conjugate Gradient. The ANN predicted values gave higher chitinase activity, i.e., 102.24 U/L as compared to RSM-predicted values, i.e., 88.38 U/L. The predicted chitinase activity was also closer to the observed data at these levels. The validation study suggested that the highest activity of chitinase as predicted by ANN is in line with experimental analysis. The comparison of three different statistical approaches suggested that ANN gives better optimization results compared to the GA and RSM study.

Optimization and Evaluation of the Thermosensitive In Situ and Adhesive Gel for Rectal Delivery of Budesonide

Budesonide is a glucocorticoid for the treatment of ulcerative colitis (UC). The current study aims to develop a thermosensitive in situ and adhesive gel for rectal delivery of budesonide. HPMC K4M was selected as the adhesive agent based on the adhesive force and the effect on gel performance. The formulation of gel was optimized by using the central composite design-response surface methodology (CCD-RSM); a mathematical model was successfully developed to predict desired formulations as well as to analyze relationships between the amount of Pluronic F-127, Pluronic F-68, and HPMC K4M and the performances of gel. Based on CCD-RSM, a thermosensitive in situ and adhesive gel consisting of 0.002% budesonide, 0.74% HPMC, 4.87% F-68, and 19.0% F-127 was developed. Furthermore, the in vivo behavior of gel was evaluated in Sprague-Dawley rats. In comparison with budesonide solution, rectal administration of budesonide gel at 0.1 mg/kg in rats showed relative bioavailability of 230% with significant increase in rectum uptake.

Isolation and identification of Pseudomonas from wastewater, its immobilization in cellulose biopolymer and performance in degrading Triclosan

Triclosan (TCS) is a well-known emerging contaminant got wide use in daily use products of domestic purpose, which provides the way to enter the ecological cycle, and is preferably detected in sewage treatment plants. In this study, TCS degrading bacteria (TDB) was isolated and identified from a wastewater treatment plant at the National Institute of Technology-Karnataka, Surathkal (NITK), India. The isolate was reported as Pseudomonas strain by performing 16S RNA Sequencing using BLAST analysis. Bacterial growth depends upon several environmental factors. Hence its growth optimization was carried out by response surface method (RSM) based central composite design (CCD) and validated by the artificial neural network (ANN). The Parameters or inputs used for optimization are pH, time (days), agitation (rpm) and sorbent dosage (μg/L). Experiments were conducted in batch mode to achieve optimum growth of bacteria based on RSM trial runs. The RSM model predictions were in better agreement with the experimental results and it was confirmed by ANN. The deviation lies within ±10% with experimental results compared to ANN for maximum trials. Hence optimized parameters were established and arrived at pH - 7, time - 13 days, agitation - 150 rpm, dosage - 1.5 μg/L presented 69% removal of TCS. Minimum inhibitory assay of isolated strain was conducted to identify the degradation capacity of TCS and it was found out to be lesser than 0.025 mg of TCS. Later the strain was immobilized in two different matrices. One is biopolymer extracted from cellulose (Water Hyacinth) along with sodium alginate and second is free bacteria with sodium alginate and was made in the form of beads. The removal of TCS by TDB-cellulose-alginate (BCA) and TDB-Alginate (BA) beads were 58% and 30% respectively. Hence it was concluded that BCA beads showed effective removal compared to BA beads. Therefore, isolate can degrade TCS when the concentration ranges from 0.025 mg/L to 5.5 ng/L.

Enhancement of gold and silver recovery from discarded computer printed circuit boards by Pseudomonas balearica SAE1 using response surface methodology (RSM)

Two-step bioleaching was applied using a cyanogenic bacterium Pseudomonas balearica SAE1 to recover gold (Au) and silver (Ag) from the computer printed circuit boards (CPCBs) via central composite design of a response surface methodology (CCD-RSM). To enhance Au and Ag recovery, factors like pH level, pulp density, temperature and glycine concentration were optimized and their interactions were studied. CCD-RSM optimization resulted in 73.9 and 41.6% dissolution of Au and Ag, respectively, at initial pH 8.6, pulp density 5 g/L, temperature 31.2 °C, and glycine concentration 6.8 g/L, respectively. Two quadratic models were proposed by RSM which can be utilized as an efficient tool to predict Au and Ag recovery through bioleaching. The experimental results are in line with the predicted results, indicating reliability of RSM model in enhancing the Au and Ag recovery from CPCBs. The increased bioleaching yield of Au and Ag from discarded CPCBs has its importance in industrial e-waste recycling and safe disposal.