Microbial transglutaminase (MTG) is an enzyme widely used in the food industry because it creates cross-links between proteins, enhancing the texture and stability of food products. Its unique properties make it a valuable tool for modifying the functional characteristics of proteins, significantly impacting the quality and innovation of food products. In this study, response surface methodology was employed to optimize the fermentation conditions for microbial transglutaminase production by the strain Streptoverticillium cinnamoneum KKP 1658. The effects of nitrogen dose, cultivation time, and initial pH on the activity of the produced transglutaminase were investigated. The significance of the examined factors was determined as follows: cultivation time > nitrogen dose > pH. The interaction between nitrogen dose and cultivation time was found to be crucial, having the second most significant impact on transglutaminase activity. Optimal conditions were identified as 48 h of cultivation with a 2% nitrogen source dose and an initial medium pH of approximately 6.0. Under these conditions, transglutaminase activity ranged from 4.5 to 5.5 U/mL. The results of this study demonstrated that response surface methodology is a promising approach for optimizing microbial transglutaminase production. Future applications of transglutaminase include the development of modern food products with improved texture and nutritional value, as well as its potential use in regenerative medicine for creating biomaterials and tissue scaffolds. This topic is particularly important and timely as it addresses the growing demand for innovative and sustainable solutions in the food and biomedical industries, contributing to an improved quality of life.

• Klíčová slova
• MTG, Response surface methodology, Streptoverticillium, Transglutaminase,
• MeSH
• dusík metabolismus   MeSH
• fermentace * MeSH
• koncentrace vodíkových iontů MeSH
• kultivační média chemie   metabolismus   MeSH
• transglutaminasy * biosyntéza   metabolismus   MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• dusík MeSH
• kultivační média MeSH
• transglutaminasy * MeSH

L-asparaginase is an essential enzyme used in cancer treatment, but its production faces challenges like low yield, high cost, and immunogenicity. Recombinant production is a promising method to overcome these limitations. In this study, response surface methodology (RSM) was used to optimize the production of L-asparaginase 1 from Saccharomyces cerevisiae in Escherichia coli K-12 BW25113. The Box-Behnken design (BBD) was utilized for the RSM modeling, and a total of 29 experiments were conducted. These experiments aimed to examine the impact of different factors, including the concentration of isopropyl-b-LD-thiogalactopyranoside (IPTG), the cell density prior to induction, the duration of induction, and the temperature, on the expression level of L-asparaginase 1. The results revealed that while the post-induction temperature, cell density at induction time, and post-induction time all had a significant influence on the response, the post-induction time exhibited the greatest effect. The optimized conditions (induction at cell density 0.8 with 0.7 mM IPTG for 4 h at 30 °C) resulted in a significant amount of L-asparaginase with a titer of 93.52 μg/mL, which was consistent with the model-based prediction. The study concluded that RSM optimization effectively increased the production of L-asparaginase 1 in E. coli, which could have the potential for large-scale fermentation. Further research can explore using other host cells, optimizing the fermentation process, and examining the effect of other variables to increase production.

• Klíčová slova
• Escherichia coli, Saccharomyces cerevisiae, Cancer treatment, L-asparaginase, Recombinant production, Response surface methodology (RSM),
• MeSH
• asparaginasa * genetika   biosyntéza   metabolismus   MeSH
• Escherichia coli K12 genetika   enzymologie   MeSH
• Escherichia coli genetika   metabolismus   MeSH
• fermentace MeSH
• isopropylthiogalaktosid farmakologie   MeSH
• rekombinantní proteiny * genetika   metabolismus   MeSH
• Saccharomyces cerevisiae * genetika   metabolismus   MeSH
• teplota MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• asparaginasa * MeSH
• isopropylthiogalaktosid MeSH
• rekombinantní proteiny * MeSH

Dealing with the current defaults of environmental toxicity, heating, waste management, and economic crises, exploration of novel non-edible, toxic, and waste feedstock for renewable biodiesel synthesis is the need of the hour. The present study is concerned with Buxus papillosa with seeds oil concentration (45% w/w), a promising biodiesel feedstock encountering environmental defaults and waste management; in addition, this research performed simulation based-response surface methodology (RSM) for Buxus papillosa bio-diesel. Synthesis and application of novel Phyto-nanocatalyst bimetallic oxide with Buxus papillosa fruit capsule aqueous extract was advantageous during transesterification. Characterization of sodium/potassium oxide Phyto-nanocatalyst confirmed 23.5 nm nano-size and enhanced catalytic activity. Other characterizing tools are FTIR, DRS, XRD, Zeta potential, SEM, and EDX. Methyl ester formation was authenticated by FTIR, GC-MS, and NMR. A maximum 97% yield was obtained at optimized conditions i.e., methanol ratio to oil (8:1), catalyst amount (0.37 wt%), reaction duration (180 min), and temperature of 80 °C. The reusability of novel sodium/potassium oxide was checked for six reactions. Buxus papillosa fuel properties were within the international restrictions of fuel. The sulphur content of 0.00090% signified the environmental remedial nature of Buxus papillosa methyl esters and it is a highly recommendable species for biodiesel production at large scale due to a t huge number of seeds production and vast distribution.

• Klíčová slova
• Biodiesel, Buxus papillosa, Fuel, Hazardous waste management, Phyto-nanocatalyst, Response surface methodology,
• MeSH
• biopaliva analýza   MeSH
• Buxus * MeSH
• estery MeSH
• katalýza MeSH
• nakládání s odpady * MeSH
• nebezpečný odpad MeSH
• oleje rostlin MeSH
• sodík MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• biopaliva MeSH
• estery MeSH
• nebezpečný odpad MeSH
• oleje rostlin MeSH
• potassium oxide MeSH Prohlížeč
• sodík MeSH
• sodium oxide MeSH Prohlížeč

Rhamnolipids are extensively studied biosurfactants due to their potential in many industrial applications, eco-friendly production and properties. However, their availability for broader application is severely limited by their production costs, therefore the optimization of efficacy of their cultivation gains significance as well as the information regarding the physio-chemical properties of rhamnolipids resulting from various cultivation strategies. In this work, the bioprocess design focused on optimization of the rhamnolipid yield of Pseudomonas aeruginosa DBM 3774 utilizing the response surface methodology (RSM). Six carbon sources were investigated for their effect on the rhamnolipid production. The RSM prediction improved the total rhamnolipid yield from 2.2 to 13.5 g/L and the rhamnolipid productivity from 11.6 to 45.3 mg/L/h. A significant effect of the carbon source type, concentration and the C/N ratio on the composition of the rhamnolipid congeners has been demonstrated for cultivation of P. aeruginosa DBM 3774 in batch cultivation. Especially, changes in presence of saturated fatty acid in the rhamnolipid congeners, ranging from 18.8% of unsaturated fatty acids (carbon source glycerol; 40 g/L) to 0% (sodium citrate 20 g/L) were observed. This demonstrates possibilities of model based systems as basis in cultivation of industrially important compounds like biosurfactants rhamnolipids and the importance of detailed study of interconnection between cultivation conditions and rhamnolipid mixture composition and properties.

• Klíčová slova
• Pseudomonas aeruginosa, biosurfactants, fractional factorial design,
• Publikační typ
• časopisecké články MeSH

Co-pyrolysis of orange peel and chicken eggshell was performed for the synthesis of the composite, a co-pyrolysis technique used to promote natural fabrication and to allow the raw material elemental combination effect and the preparatory conditions such as pyrolysis temperature, residence time, and eggshell/orange peel mixing ratio, to be optimized with the response surface methodology through Box-Behnken Design(BBD). BBD involved a randomized series of 17 experimental runs, and the best optimal conditions were found with a pyrolysis temperature of 300 °C, a residence time of 1 h, and 0.5 as the mixing ratio. These conditions gave a maximum adsorption capacity of 167 mg/g for removal of the modal pollutant methylene blue. FTIR spectra of the composite showed new functional peaks of oxygenated groups, at two different bands. XRD confirmed an amorphous surface with inorganic component peaks, while SEM-EDS revealed rich defects sites along with an enhanced percentage of oxygen elements on the surface; the surface area was enhanced from 1 m2 with unmodified peel to 64 m2 with composite. The adsorption behavior of the composite was studied for dye removal and the adsorption behavior was well explained by the Langmuir isotherm model.

• Klíčová slova
• Adsorption, Co-pyrolysis, Methylene blue, Optimization, Orange peel & eggshell composite,
• MeSH
• adsorpce MeSH
• chemické látky znečišťující vodu * MeSH
• kinetika MeSH
• methylenová modř MeSH
• pomerančovník čínský * MeSH
• pyrolýza MeSH
• teplota MeSH
• vaječná skořápka MeSH
• zvířata MeSH
• Check Tag
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• chemické látky znečišťující vodu * MeSH
• methylenová modř MeSH

Lipases are industrially important enzymes having vast applications in various fields. Cloning and expression of lipase enzyme-encoding genes in suitable host lead to their widespread use in different fields. The present study represents the first attempt towards the expression of the synthetic lipase gene in Pseudomonas aeruginosa. An alkalophilic lipase gene (GenBank accession number: NP_388152) from Bacillus subtilis was synthetically designed and introduced in the pJN105 vector and subsequently cloned in Pseudomonas aeruginosa SDK-6. Agarose gel electrophoresis confirmed the transformation of SDK-6, exhibiting a band difference of ~ 700 bp between native and recombinant pJN105. Further amplification of cloned lipase gene was confirmed using PCR amplification with Lip 1 and Lip 2 primers respectively, followed by restriction analysis. Approximately 15-fold increase in lipase production was observed in recombinant Pseudomonas as compared to the native strain. One factor at a time (OFAT) analysis revealed L-arabinose, inoculum size (0.5%; v/v), and agitation (120 rpm) as significant factors affecting the over-expression of lipase enzyme. Optimization of enzyme induction conditions by central composite design (CCD) led to 1.60-fold increase in the production of lipase at 0.65% (w/v) inducer concentration, OD600-1.075 before induction and 35 °C post induction temperature with overall lipase production of 50.50 IU/mL. Statistical validation of observed value via ANOVA showed an F-value of 138.70 at p < 0.01 with R2 of 0.9921.

• Klíčová slova
• Bacillus subtilis, Pseudomonas aeruginosa, Optimization, Recombinant lipase, Response surface methodology, pJN105,
• MeSH
• arabinosa metabolismus   MeSH
• Bacillus subtilis * genetika   enzymologie   MeSH
• bakteriální proteiny genetika   metabolismus   MeSH
• exprese genu MeSH
• genetické vektory genetika   MeSH
• klonování DNA MeSH
• lipasa * genetika   metabolismus   MeSH
• Pseudomonas aeruginosa * genetika   enzymologie   MeSH
• rekombinantní proteiny * genetika   metabolismus   MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• arabinosa MeSH
• bakteriální proteiny MeSH
• lipasa * MeSH
• rekombinantní proteiny * MeSH

Droplet coalescence in microchannels is a complex phenomenon influenced by various parameters such as droplet size, velocity, liquid surface tension, and droplet-droplet spacing. In this study, we thoroughly investigate the impact of these control parameters on droplet coalescence dynamics within a sudden expansion microchannel using two distinct numerical methods. Initially, we employ the boundary element method to solve the Brinkman integral equation, providing detailed insights into the underlying physics of droplet coalescence. Furthermore, we integrate Response Surface Methodology (RSM) to effectively optimize droplet coalescence dynamics, harnessing the power of machine learning algorithms. Our results showcase the efficacy of these computational techniques in enhancing experimental efficiency. Through rigorous evaluation utilizing Regression Coefficient and Mean Absolute Error metrics, we ascertain the accuracy of our estimations. Our findings highlight the significant influence of key parameters, specifically the non-dimensional initial distance of the droplets (D), viscosity ratio ( μ ), Capillary number (Ca), and width (w), as identified by the non-dimensional final droplet-droplet spacing (DD), velocity of the first droplet (VFD), and velocity of the second droplet (VBD), respectively. This comprehensive approach provides valuable insights into droplet coalescence phenomena and offers a robust framework for optimizing microfluidic systems. The most influential parameters on DD are the values of Ad and D, while viscosity has the lowest influence on DD. The most influential parameters on droplet velocity are viscosity and channel width, whereas the initial distance and Ca have the least influence on droplet velocity. The comparison of different machine learning algorithms indicates that the best ones for predicting DD, VFD, and VBD are function, SMOreg, Lazy-IBK, and Meta-Bagging, respectively.

• Klíčová slova
• Coalescence, Droplet, Machine learning, Microchannel, Optimization,
• Publikační typ
• časopisecké články MeSH

Response surface methodology (RSM) and artificial neural network-real encoded genetic algorithm (ANN-REGA) were employed to develop a process for fermentative swainsonine production from Metarhizium anisopliae (ARSEF 1724). The effect of finally screened process variables viz. inoculum size, oatmeal extract, glucose, and CaCl2 were investigated through central composite design and were further utilized for training sets in ANN with training and test R values of 0.99 and 0.94, respectively. ANN-REGA was finally employed to simulate the predictive swainsonine production with best evolved media composition. ANN-REGA predicted a more precise fermentation model with 103 % (shake flask) increase in alkaloid production compared to 75.62 % (shake flask) obtained with RSM model upon validation.

• MeSH
• alkaloidy izolace a purifikace   metabolismus   MeSH
• biotechnologie metody   MeSH
• fermentace MeSH
• kultivační média chemie   MeSH
• Metarhizium genetika   metabolismus   MeSH
• neuronové sítě MeSH
• počet mikrobiálních kolonií MeSH
• swainsonin izolace a purifikace   metabolismus   MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• alkaloidy MeSH
• kultivační média MeSH
• swainsonin MeSH

The primary objective of this study is to investigate the microstructural, mechanical, and wear behaviour of AZ31/TiC surface composites fabricated through friction stir processing (FSP). TiC particles are reinforced onto the surface of AZ31 magnesium alloy to enhance its mechanical properties for demanding industrial applications. The FSP technique is employed to achieve a uniform dispersion of TiC particles and grain refinement in the surface composite. Microstructural characterization, mechanical testing (hardness and tensile strength), and wear behaviour evaluation under different operating conditions are performed. Response surface methodology (RSM) is utilized to optimize the wear rate by considering the effects of process parameters. The results reveal a significant improvement in hardness (41.3%) and tensile strength (39.1%) of the FSP-TiC composite compared to the base alloy, attributed to the refined grain structure (6-10 μm) and uniform distribution of TiC particles. The proposed regression model accurately predicts the wear rate, with a confirmation test validating an error percentage within ± 4%. Worn surface analysis elucidates the wear mechanisms, such as shallow grooves, delamination, and oxide layer formation, influenced by the applied load, sliding distance, and sliding velocity. The enhanced mechanical properties and wear resistance are attributed to the synergistic effects of grain refinement, particle-accelerated nucleation, the barrier effect of TiC particles, and improved interfacial bonding achieved through FSP. The optimized FSP-TiC composites exhibit potential for applications in industries demanding high strength, hardness, and wear resistance.

• Klíčová slova
• AZ31 alloy, Friction stir processing, Hardness, Microstructure, Tensile properties, TiC particles, Wear optimization,
• Publikační typ
• časopisecké články MeSH

Monel K-500 is a high-performance superalloy composed of nickel and copper, renowned for its exceptional strength, hardness, and resistance to corrosion. To machine this material more precisely and accurately, Electrical Discharge Machining (EDM) is one of the best choices. In EDM, material removal rate (MRR) and electrode wear rate (EWR) are crucial performance parameters that are often conflicting in nature. These parameters depend on several input variables, including peak current (Ip), pulse on time (Ton), duty cycle (Tau), and servo voltage (SV). Optimizing the EDM process is essential for enhancing performance. In this research, a set of experiments were conducted using EDM on Monel K500 alloy to determine the optimal process parameters. The Box-Behnken design was used to prepare the experimental design matrix. Utilizing the experimental data, a second-order mathematical model was developed using Response Surface Methodology (RSM). R2 value is found to be 99.40% and 96.60% for MRR and EWR RSM-based prediction model, respectively. High value of R2 is indicated is indicated good adequacy for prediction. The mathematical model further used in multi-objective dragonfly algorithm (MODA): a new meta-heuristic optimization technique to solve multi-objective optimization problem of EDM. The MODA is a very useful technique to achieve optimal solutions from the multi decision criteria. Utilizing this technique, a set of non-dominated solutions was obtained. Further, the TOPSIS method was used to determine the most desirable optimal solution, which was found to be 0.0135 mm3/min for EWR and 6.968 mm3/min for MRR. These results were obtained when the optimal process parameters were selected as Ip = 6 A, Ton = 200 µs, Tau = 12, and SV = 41.6 V. Operators can machine Monel K500 by selecting the above-mentioned optimal parameters to achieve the best performance.

• Klíčová slova
• EDM, MODA, Monel K-500, RSM,
• Publikační typ
• časopisecké články MeSH