Formulation of insulin-loaded polymeric nanoparticles using response surface methodology

The objective of this work was to formulate new oral insulin-loaded nanoparticules using the response surface methodology. The insulin nanoparticles were prepared by a water-in-oil-in-water emulsification and evaporation method. The polymers used for the encapsulation were blends of biodegradable poly-epsilon-caprolactone (PCL) and of positively-charged, nonbiodegradable polymer (Eudragis RS®). A central composite design has been built to investigate the effects of three controlled variables: ratio of polymers (PCL/RS ratio), volume, and pH of the aqueous solution of polyvinyl alcohol. The nanoparticles were characterized by measuring the amount of entrapped insulin, the particle size, the polydispersity of the obtained particles, the zeta potential, and the amount of insulin released after 7 hours. A second-order model was evaluated by multiple regression and was statistically tested for each of the studied controlled variable. The obtained polynomials proved efficient to localize an optimal operating area highlighted by the use of three-dimensional response surfaces and their corresponding isoresponse curves. An interesting formulation given by the models was selected, prepared, and evaluated. The corresponding quantity of entrapped insulin was 25 IU per 100 mg of polymer, and the particle size was 350 nm with a polydispersity of 0.21. The quantity of released insulin was 4.8 IU per 100 mg of polymer after 7 hours and the zeta potential was + 44 mV. All these collected values were in perfect accordance with values estimated by the models. Finally, the results suggested that PCL/RS 50/50 nanoparticles might represent a promising formulation for oral delivery of insulin.     

Preparation and optimization of doxorubicin-loaded albumin nanoparticles using response surface methodology

Background: The objective of this work was to optimize the preparation of doxorubicin-loaded albumin nanoparticles (Dox-A-Nps) through desolvation procedures using response surface methodology (RSM). A central composite design (CCD) for four factors at five levels was used in this study.

Method: Albumin nanoparticles were prepared through a desolvation method and were optimized in the aid of CCD. Albumin concentration, amount of doxorubicin, pH values, and percentage of glutaraldehyde were selected as independent variables, particle size, zeta potential, drug loading, encapsulation efficiency, and nanoparticles yield were chosen as response variables. RSM and multiple response optimizations utilizing a quadratic polynomial equation were used to obtain an optimal formulation.

Results: The optimal formulation for Dox-A-Nps was composed of albumin concentration of 17?mg/ml, amount of doxorubicin of 2?mg/ml, pH value is 9 and percentage of glutaraldehyde of 125% of the theoretic amount, under which the optimized conditions gave rise to the actual average value of mean particle size (151?±?0.43?nm), zeta potential (?18.8?±?0.21 mV), drug loading efficiency (21.4?±?0.70%), drug entrapment efficiency (76.9?±?0.21%) and nanoparticles yield (82.0?±?0.34%). The storage stability experiments proved that Dox-A-Nps stable in 4°C over the period of 4 months. The in vitro experiments showed a burst release at the initial stage and followed by a prolonged release of Dox from albumin nanoparticles up to 60?h.

Conclusions: This study showed that the RSM-CCD method could efficiently be applied for the modeling of nanoparticles, which laid the foundation of the further research of immuno nanoparticles.     

Improved alignment of fibre-optics active devices via response surface methodology

Response surface methodology (RSM) has long been recognized as an effective approach to empirical optimization of engineering processes. This paper reports a novel application of the methodology to enhance the efficiency and reliability of an active device alignment operation that is critical to fibreoptics manufacturing. With 2² factorial designs, the RSM approach has been found capable of locating the optimum co-ordinates for maximum power coupling at speeds more than three times those of the usual search algorithms.     

响应面优化法研究蔗糖苯酚树脂胶粘剂的合成

以蔗糖代替甲醛,在碱性条件下合成了一种环保型蔗糖苯酚树脂胶粘剂.用响应面优化法对蔗糖苯酚树脂的合成条件进行了优化,以树脂黏度作为考察指标,根据中心复合的设计原理对实验进行设计并对结果进行分析.研究了温度、时间、糖酚比和催化剂用量对反应的影响,得到最佳工艺条件为:反应温度95.63℃,反应时间5.26h,糖酚比2.6,催...     

Optimization of enzymatic hydrolysis of wool fibers for nanoparticles production using response surface methodology

Optimization of enzymatic hydrolysis of wool fiber was carried out using a Central Composite Design (CCD) in order to produce wool nanoparticles. The effects of three important determinants, i.e. enzyme loading, substrate concentration and hydrolysis time on enzymatic efficiency were investigated. Polynomial regression model was fitted to the experimental data to generate predicted response such as particle size. The results were subjected to analysis of variance (ANOVA) to determine significant parameters used for optimization. Wool nanoparticles was produced under the attained optimal condition (enzyme loading: 3.3%, substrate concentration: 5 g/l and hydrolysis time: 214 h), followed by ultrasonic treatment. SEM micrographs indicated wool fiber degradation in which the outer cuticle layer was removed and the inner cortical cells were isolated. The results of particle size analysis indicated the positive effect of sonication on reducing particles size further. FTIR spectra denoted no evident changes in the composition of the chemical groups in the macromolecular structure of wool fiber. Besides, the enzymatic hydrolysis and ultrasonic treatment led to an increase in crystallinity, solubility in caustic solution and thermal stability of wool nanoparticles, but caused a decrease in moisture regain comparing to the raw wool fiber.     

Prediction of nanofiber diameter and optimization of electrospinning process via response surface methodology

Response surface methodology (RSM) was used to obtain a more systematic understanding of the electrospinning conditions of polyamide 6 solutions. This method was used to establish a quantitative basis for the relationships between the electrospinning parameters such as applied electric field, the polymer concentrations, the rate of injection and nozzle-collector distance with the diameter of the produced nanofibers, and to predict the optimum conditions for electrospinning to produce nanofibers with controlled size. A response function was empirically determined by central composite design (CCD) using fiber diameter as an observed response and the electrospinning parameters as variables. The relationship between the response and the variables is visualized by a response surface or contour plots. The study of the graphical representations of contour plots, prediction formulas and prediction profiler can predict the operating conditions necessary to generate nanofibers with the desired diameters.     

Tailor-made nanoparticles via gas-phase synthesis

Gas-phase synthesis is a well-known chemical manufacturing technique for an extensive variety of nanoscale particles. Since the potential of ultrafine and, in particular, nanoscale particles in high-performance applications has been identified, scientific and commercial interest has increased immensely, thus identifying this field as a most important technology of the future. However, nanomaterials can perform their multifunctional tasks only if they are customized in terms of chemical composition, size, and morphology to suit the application at hand. Profound knowledge of the synthesis and precise process control is crucial in meeting the stringent specifications. Although the gas-phase synthesis of ultrafine materials has been known and commercially exploited for decades, existing knowledge is based almost exclusively on empirical know-how. Process simulation is a very suitable tool for expanding the understanding of the synthesis-relevant processes, particle formation mechanisms, and operating parameters. Based on the resulting expertise some special nanoscale gas-phase products of high innovative potential have been developed.     

Optimisation of food grade mixed surfactant‐based l‐ascorbic acid nanoemulsions using response surface methodology

Co‐surfactant free l‐ascorbic acid (LAA) nanoemulsions were prepared using mixed surfactants (Soya lecithin and Tween 80). Response surface methodology (RSM) was used to optimise the emulsifying conditions for LAA nanoemulsions. The effects of water proportion (6%–14% w/w), homogenisation pressure (80–160 MPa), surfactant concentrations (4%–12% w/w) and laa concentration (0.5–1.3 w/w) on responses (size of droplets and nanoemulsion stability) were investigated. RSM results showed that the values of responses can be successfully predicted through second‐order polynomial model. The coefficients of determinations for droplet size and nanoemulsion stability were 0.9375 and 0.9027, respectively. The optimum preparation conditions for l‐LAA nanoemulsion were 9.04% water proportion, 114.48 MPa homogenisation pressure, 7.36% surfactant concentration and 1.09% LAA concentration. At the end of one month storage study, the retention of LAA in optimised nanoemulsions stored at 4°C and 25°C were 74.4% and 66.7%, respectively. These results may provide valuable contributions for food and pharmaceutical industry to develop delivery system for food additives and nutraceutical components.     

Bioremediation of a soil contaminated by lindane utilizing the fungus Ganoderma australe via response surface methodology

Mixtures of a sandy soil and wheat straw were doped with the organochlorine insecticide lindane in glass tubes and were inoculated with the polypore fungus, Ganoderma australe. An evaluation of bioremediation process effectiveness was searched and five parameters identified for the solid-state system. Fungi growth is a function of temperature and requires moisture for a proper colonization. These microorganisms need inorganic nutrients such nitrogen and phosphorus to support cell growth and it is also appropriate to know the range of concentration and toxicity of the used insecticide. Thus, an orthogonal central composite design (CCD) of experiments was used to construct second order response surfaces. Five design factors, namely temperature, moisture, straw, lindane content and nitrogen content and seven optimization parameters (responses), namely lag time, propagation velocity, biomass growth rate, biodegradation rate, biodegradation/biomass, biomass/propagation and biomass content were analyzed. The optima of the responses of the adequate models were found to be the following: propagation velocity 4.25mm/day, biomass growth rate 408mg/day, biodegradation/biomass 56.9microg/g, biomass/propagation 250mg/mm and fungal biomass content in solid mixture 260mg/cm(3). The most important response for bioremediation purposes is biodegradation/biomass which is maximized at the factors levels: temperature 17.3 degrees C, moisture 58%, straw content 45%, lindane content 13ppm and nitrogen content 8.2ppm.     

Role of pH in the green synthesis of silver nanoparticles

The role of pH in the green synthesis of silver nanoparticles (AgNPs) is investigated. For the reduction synthesis of AgNPs we use silver nitrate, glucose, sodium hydroxide and starch respectively to serve as precursor, reducing agent, accelerator and stabilizer. The effect of NaOH addition on the nature of AgNPs is systematically studied. Two reaction pathways are proposed to explain the formation of AgNPs, keeping in view the pH changes that occur on addition of different amounts of NaOH. The aqueous sol of AgNPs prepared at different pH values display different surface plasmon resonance (SPR) behavior. This is explained in terms of size and size distribution of AgNPs.     

Optimizing energy harvesting parameters using response surface methodology

Energy harvesting is a process in which energy that would otherwise be wasted is stored and then used to power a system. Due to their unique properties piezoelectric materials are ideal for energy harvesting applications. In this study a pre-stressed piezoelectric composite was pressure loaded dynamically to harvest energy. The objective of this study was to optimize, using piezoelectric diaphragms, relevant parameters that have an effect on the energy harvesting process. Parameters considered were temperature, pressure, resistance and frequency. Response surface methodology was used to develop models to identify optimal parameter ranges and also to predict power conversion capabilities for specific parameter levels. Power densities of approximately 24.27 muW/mm³ were measured at optimal conditions. The model identified an optimal temperature of 12degC and a pressure of 240 kPa, which are in agreement with experimental results.     

Application of fractional factorial design for green synthesis of cyano-modified silica nanoparticles: Chemometrics and multifarious response optimization

Cyano-functionalized spherical silica nanoparticles (SNPs) were synthesized via Stöber method. A 2?^k-p_IV–fractional factorial design (2^k-p_IV–FFD) was used to smartly prepare monodispersed evenly distributed SNPs. Six factors were considered; concentrations of tetraethylorthosilicate (TEOS), 3-Cyanopropyltriethoxysilane (CPTS), water, and ammonia, reaction time (RT) and stirring time (ST). Two responses; particle size (PS, measured by SEM) and particle-size distribution (PSD, calculated as standard deviation, ±SD) were measured. Control charts were used to decide on impacts of linear and two-way interactions on both responses. Derringer’s function was used to consolidate these multifarious responses into a uniform execution characteristic. Both screening and optimization were always accompanied by ANOVA testing at a 95.0% confidence interval (CI). The ideal synthetic conditions were obtained from the composite desirability plots. Cyano-functionalized SNPs with an average PS of 474.04?±?86.71?nm were produced. Raman spectroscopy and FTIR were used to confirm the functionalization process. Thermogravimetric analysis (TGA) was used to evaluate the thermal behavior of synthesized particles.     

响应面法优化保水缓释肥料的合成工艺及其性能研究

以丙烯酸为聚合包裹材料,高比例添加膨润土无机添加剂,利用响应面法进行实验设计,获得氮(N)含量与各个单因素的函数关系,并建立以含氮量为响应值的保水缓释肥料合成工艺模型.通过回归方程和响应曲面分析,获得保水缓释肥料最佳合成工艺为丙烯酸中和度为59％,尿素量为37.26％,膨润土量为20％,反应时间4h.验证结果显示,在此条件下含氮量为20.56％.N素缓释行为研究表明,在蒸馏水中N的缓释机制为Fick扩散机制,且具有较好的缓释性能.盆栽试验表明,在干旱条件下,保水缓释肥料的使用在很大程度上提高了棉花的发芽率、成苗率及生物量的积累.     

Optimization of A-TIG process parameters using response surface methodology

In the present work, the influence of process parameters such as welding current (I), welding speed (S), and flux coating density (F) on different aspects of weld bead geometry for example depth of penetration (DOP), bead width (BW), depth to width ratio (D/W), and weld fusion zone area (WA) were investigated by using the central composite design (CCD). 9–12% Cr ferritic stainless steel (FSS) plates were welded using A-TIG welding. It was observed that all input variables have a direct influence on the DOP, BW, and D/W. However, flux coating density has no significant effect on WA. Mathematical models were generated from the obtained responses to predict the weld bead geometry. An optimized DOP, BW, D/W, and WA of 6.95?mm, 8.76?mm, 0.80, and 41.99?mm², respectively, were predicted at the welding current of 213.78 A, the welding speed of 96.22?mm/min, and the flux coating density of 1.99?mg/cm². Conformity test was done to check the practicability of the developed models. The conformity test results were in good agreement with the predicted values. Arc constriction and reversal in Marangoni convection were considered as major mechanisms for the deep and narrow weld bead during A-TIG welding.     

Surfactant-assisted synthesis of Sn nanoparticles via solution plasma technique

We have adopted a solution plasma synthesis for preparing Sn nanoparticles (Sn-NPs) directly from metallic Sn electrode. The Sn-NPs were synthesized in the presence of the surfactant, cetyltrimethylammonium bromide (CTAB), and the effect of the concentration of CTAB on the Sn-NPs was investigated. Without CTAB addition, SnO plates were precipitated. Sn-NPs with less than 200 nm were synthesized at a high concentration of 200 × 10⁻⁶ g ml⁻¹ of CTAB. Electrochemical properties of SnO plates and Sn-NPs were analyzed for use as an anode material in Li-ion batteries. A composite of Sn-NPs and graphite enhanced the cyclic stability owing to the buffer space provided by the graphite for volume expansion. In the case of the 30 wt% loaded Sn-NPs, the capacity was measured to be 414 mA h g⁻¹ after 20 cycles.     

Solvothermal synthesis of ceria nanoparticles with large surface areas

Ceria nanoparticles were obtained by the calcination of precursors synthesised via the solvothermal reaction of cerium acetate. The CeO₂ samples obtained by the thermal decomposition of Ce(C₇H₁₅COO)₃·xH₂O synthesised by solvothermal reaction in 1,4-butanediol in the presence of octanoic acid had an extremely large surface area of 180 m²/g. The Ru catalyst supported on this CeO₂ sample showed a high catalytic activity for benzyl alcohol oxidation.     

Optimising photoelectrocatalytic oxidation of fulvic acid using response surface methodology

In this paper, statistics-based experimental design with response surface methodology (RSM) was employed to investigate the effect of operation conditions on photoelectrocatalytic oxidation of fulvic acid (FA) using a Ti/TiO(2) electrode in a photoreactor. Initially, the Box-Behnken design was employed including the three key variables (initial pH, potassium peroxodisulphate (K(2)S(2)O(8)) and bias potential). Thereafter, the mutual interaction and effects between these parameters and optimum conditions were obtained in greater detail by means of SAS and Matlab software. The results of this investigation reveal that: (1) the regression analysis with R(2) value of 0.9754 shows a close fit between the experimental results and the model predictions; (2) three-dimension response surface plot can provide a good manner for visualizing the parameter interactions; (3) the optimum pH, K(2)S(2)O(8) and bias potential is found to be 3.8, 88.40 mg/L, 0.88 V, respectively, and the highest FA removal efficiency of 57.06% can be achieved.     

基于响应面法的结构动力学模型修正

为了获得精确的结构动力学模型,提出了响应面和优化相结合的方法。利用参数化模型和优化拉丁方试验设计获取样本点构造多项式响应面模型,最小二乘法确定多项式系数并检验响应面的拟合精度。用响应面计算结果与实验结果的误差构造目标函数,自适应模拟退火算法来优化修正响应面参数,将修正后的参数值带入有限元模型得到修正模型。以欧洲航空科技组织的基准模型GARTEUR飞机模型为算例,对比修正前后模态频率,结果表明修正后的模型在测试频段和预测频段具有良好的复现和预测能力,进而验证了基于响应面法与优化方法相结合的结构动力学有限元模型修正的有效性。