Experimental Design Optimization Research Articles

Optimization of Experimental System Design for Benchmarking of Large Angle Scattering Reaction Cross Section at 14 MeV Using Two Shadow Bars

Optimization of Experimental System Design for Benchmarking of Large Angle Scattering Reaction Cross Section at 14 MeV Using Two Shadow Bars

Ddrage: A data set generator to evaluate ddRADseq analysis software.

High-throughput sequencing makes it possible to evaluate thousands of genetic markers across genomes and populations. Reduced-representation sequencing approaches, like double-digest restriction site-associated DNA sequencing (ddRADseq), are frequently applied to screen for genetic variation. In particular in nonmodel organisms where whole-genome sequencing is not yet feasible, ddRADseq has become popular as it allows genomewide assessment of variation patterns even in the absence of other genomic resources. However, while many tools are available for the analysis of ddRADseq data, few options exist to simulate ddRADseq data in order to evaluate the accuracy of downstream tools. The available tools either focus on the optimization of ddRAD experiment design or do not provide the information necessary for a detailed evaluation of different ddRAD analysis tools. For this task, a ground truth, that is, the underlying information of all effects in the data set, is required. Therefore, we here present ddrage, the ddRAD Data Set Generator, that allows both developers and users to evaluate their ddRAD analysis software. ddrage allows the user to adjust many parameters such as coverage and rates of mutations, sequencing errors or allelic dropouts, in order to generate a realistic simulated ddRADseq data set for given experimental scenarios and organisms. The simulated reads can be easily processed with available analysis software such as stacks or pyrad and evaluated against the underlying parameters used to generate the data to gauge the impact of different parameter values used during downstream data processing.

The exposure-effect-toxicity correlation of docetaxel and magnesium isoglycyrrhizinate in non-small cell lung tumor-bearing mice

To take full advantage of combination therapy of Docetaxel (DTX) and Magnesium isoglycyrrhizinate (MGIG), the pharmacokinetic- pharmacodynamic- toxicodynamics (PK-PD-TD) interaction of DTX and MGIG in non-small cell lung tumor-bearing mice was investigated in the present study. A model, an integrated semi-mechanistic PK-PD-TD, was established for elucidating the exposure-effect-toxicity relationship between DTX and MGIG. A tumor growth and a transit compartmental system were applied to imitate the growth and death of tumor cell. An indirect model with precursor-dependence was induced to clarify the temporal relationship between liver injury and drug exposure. No PK interaction between DTX and MGIG in plasma, liver and tumor was observed. In PD and TD results, MGIG had no antitumoral activity on non-small cell lung carcinoma, while it showed a strong hepatoprotection on DTX-induced liver injury. The PK-PD parameters of anti-tumor effect were related with the tumor growth characteristics, the kinetics of the tumor death and drug potency. In the PK-TD model, it was estimated about the elevation rate of ALT after DTX challenge in hepatocytes as well as plasma. MGIG reduced the DTX-induced ALT release rate from hepatocyte efficiently. Based on parameters estimated via PK-PD-TD correlation, the model successfully predicted the tumor growth kinetics and hepatoprotection at different dose regimes. Therefore, this prospective model might provide an alternative approache to the optimization of new experiment design.

Optimization of capillary zone electrophoresis for charge heterogeneity testing of biopharmaceuticals using enhanced method development principles.

CZE is a well‐established technique for charge heterogeneity testing of biopharmaceuticals. It is based on the differences between the ratios of net charge and hydrodynamic radius. In an extensive intercompany study, it was recently shown that CZE is very robust and can be easily implemented in labs that did not perform it before. However, individual characteristics of some examined proteins resulted in suboptimal resolution. Therefore, enhanced method development principles were applied here to investigate possibilities for further method optimization. For this purpose, a high number of different method parameters was evaluated with the aim to improve CZE separation. For the relevant parameters, design of experiments (DoE) models were generated and optimized in several ways for different sets of responses like resolution, peak width and number of peaks. In spite of product specific DoE optimization it was found that the resulting combination of optimized parameters did result in significant improvement of separation for 13 out of 16 different antibodies and other molecule formats. These results clearly demonstrate generic applicability of the optimized CZE method. Adaptation to individual molecular properties may sometimes still be required in order to achieve optimal separation but the set screws discussed in this study [mainly pH, identity of the polymer additive (HPC versus HPMC) and the concentrations of additives like acetonitrile, butanolamine and TETA] are expected to significantly reduce the effort for specific optimization.

Antibacterial Activity of Copper Oxide (CuO) Nanoparticles Biosynthesized by Bacillus sp. FU4: Optimization of Experiment Design

Background: There are several methods for synthesis of metallic nanoparticles (NPs) including chemical, physical and biological process. In this study, Bacillus sp. FU4 was used as biological source for biosynthesis of CuO NPs. Methods: CuO NPs have been prepared by copper sulfate (CuSO4). CuO NPs were formed after oxidation of Cu NPs. Design and analysis of Taguchi experiments (an orthogonal assay and analysis of variance (ANOVA)) carried out by the Qualitek-4 software. Average effect of CuSO4 concentration (0.1, 0.01 and 0.001 M), incubation and culturing time (48, 72, 96 hours) as three controllable factors with three levels were evaluated in CuO NPs biosynthesis. Characterization of CuO NPs was determined by UV-Vis spectroscopy, X-ray diffraction (XRD), Fourier transform infra-red (FT-IR) spectroscopy and scanning electron microscopy (SEM). Also, the antimicrobial properties of CuO NPs were investigated using Escherichia coli ATCC 25922 and Staphylococcus aureus ATCC 43300 as multidrug resistant (MDR) bacteria. Results: Results: It was evaluated that, NPs size distributions were in the range of 2-41 nm with spherical shapes. The anti-bacterial activities of CuO NPs were measured based on diameter of inhibition zone in disk diffusion tests of NPs dispersed in batch cultures. Two levels of CuSO4 concentrations (0.1 and 0.01M) had antibacterial effect on E.coli (33±0.57 and 6 ±2mm). In the case of S. aureus, there was surprisingly no sign of growth. Conclusion: CuO NPs have antibacterial activity that can be benefit in medicinal aspect for fighting against prominent pathogen bacteria such as E.coli ATCC 25922 and S.aureus ATCC 43300.

Application of novel copper organic material for facile microextraction of sodium valproate from human plasma samples: Experimental design optimization and isotherm study

Well‐designed metal organic materials (MOMs) were synthesized and applied for pre‐concentration and determination of sodium valproate (Na‐VP) from biological samples, bound to the copper complex of 1,4‐phenylenedioxydiacetic acid under mild conditions. The channels of this sorbent provide high efficiency and also selectivity. The MOMs were structurally characterized using Fourier transform infrared and energy‐dispersive X‐ray spectroscopies, scanning electron microscopy and X‐ray diffraction, and they were found to have suitable features for quantification of Na‐VP using HPLC coupled with UV detection at λ = 215 nm. Moreover, the rate of adsorption is improved by ultrasonic power and the experimental data are best fitted according to Freundlich adsorption isotherm. According to the central composite design, the best experimental conditions are 280.0 μl, 3.0 min and 17.0 mg for volume of eluent, sonication time and sorbent mass respectively. Calibration plots show linear responses towards Na‐VP concentrations (0.4–18.0 μg ml−1), satisfactory limit of detection (0.06 μg ml−1, S/N = 3) and reasonable enrichment factor (70.58). The coefficient of variation values of both inter‐ and intra‐day analyses were less than 4.0%, indicating a candidate method for the determination of Na‐VP in human plasma with reasonable recovery and efficiency.

Isotherms and kinetic study of ultrasound-assisted adsorption of malachite green and Pb2+ ions from aqueous samples by copper sulfide nanorods loaded on activated carbon: Experimental design optimization

Copper sulfide nanorods loaded on activated carbon (CuS-NRs-AC) was synthesized and used for simultaneous ultrasound-assisted adsorption of malachite green (MG) and Pb2+ ions from aqueous solution. Following characterization of CuS-NRs-AC were investigated by SEM, EDX, TEM and XRD, the effects of pH (2.0–10), amount of adsorbent (0.003–0.011g), MG concentration (5–25mgL−1), Pb2+ concentration (3–15mgL−1) and sonication time (1.5–7.5min) and their interactions on responses were investigated by central composite design (CCD) and response surface methodology. According to desirability function on the Design Expert optimum removal (99.4%±1.0 for MG and 68.3±1.8 for Pb2+ions) was obtained at pH 6.0, 0.009g CuS-NRs-AC, 6.0min mixing by sonication and 15 and 6mgL−1 for MG and Pb2+ ions, respectively. High determination coefficient (R2>0.995), Pred-R2-value (>0.920) and Adju-R2-value (>0.985) all are good indication of best agreement between the experimental and design modelling. The adsorption kinetics follows the pseudo-second order model and adsorption isotherm follows the Langmuir model with maximum adsorption capacity of 145.98 and 47.892mgg−1 for MG and Pb2+ ions, respectively. This adsorbent over short contact time is good choice for simultaneous removal of large content of both MG and Pb2+ ions from wastewater sample.

Investigation of Flyback Transformer Flux Leakage Reduction Ways

Results of experimental investigation and design optimization of flyback transformer are presented. Aim of the work is to investigate experimentally the impact of the flyback transformer design on the flux leakage and maximal output power. It is difficult to evaluate the effect of the leakage flux mathematically because it depends on various factors: the position of the windings relative to each other; the position of the windings in the transformer; the distance between the winding. A multi-winding flyback transformer was used for experiments. Using the results of the experiments optimal design of the investigated flyback transformer was defined.

Novel imaging techniques to study the functional organization of the human brain

Despite more than a century of investigation into the cortical organization of motor function, the existence of motor somatotopy is still debated. We review functional magnetic resonance imaging (fMRI) studies examining motor somatotopy in the cerebral cortex. In spite of a substantial overlap of representations corresponding to different body parts, especially in non-primary motor cortices, geographic approaches are capable of revealing somatotopic ordering. From the iconic homunculus in the contralateral primary cortex to the subtleties of ipsilateral somatotopy and its relations with lateralization, we outline potential reasons for the lack of segregation between motor representations. Among these are the difficulties in distinguishing activity that arises from multiple muscular effectors, the need for flexible motor control and coordination of complex movements through functional integration and artefacts in fMRI. Methodological advances with regard to the optimization of experimental design and fMRI acquisition protocols as well as improvements in spatial registration of images and indices aiming at the quantification of the degree of segregation between different functional representations are inspected. Additionally, we give some hints as to how the functional organization of motor function might be related to various anatomical landmarks in brain morphometry.

Advanced method optimization for volatile aroma profiling of beer using two-dimensional gas chromatography time-of-flight mass spectrometry

The complex mixture of volatile organic compounds (VOCs) present in the headspace of Trappist and craft beers was studied to illustrate the efficiency of thermal desorption (TD) comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC-TOFMS) for highlighting subtle differences between highly complex mixtures of VOCs. Headspace solid-phase microextraction (HS-SPME), multiple (and classical) stir bar sorptive extraction (mSBSE), static headspace (SHS), and dynamic headspace (DHS) were compared for the extraction of a set of 21 representative flavor compounds of beer aroma. A Box-Behnken surface response methodology experimental design optimization (DOE) was used for convex hull calculation (Delaunay’s triangulation algorithms) of peak dispersion in the chromatographic space. The predicted value of 0.5 for the ratio between the convex hull and the available space was 10% higher than the experimental value, demonstrating the usefulness of the approach to improve optimization of the GC×GC separation. Chemical variations amongst aligned chromatograms were studied by means of Fisher Ratio (FR) determination and F‐distribution threshold filtration at different significance levels (α=0.05 and 0.01) and based on z‐score normalized area for data reduction. Statistically significant compounds were highlighted following principal component analysis (PCA) and hierarchical cluster analysis (HCA). The dendrogram structure not only provided clear visual information about similarities between products but also permitted direct identification of the chemicals and their relative weight in clustering. The effective coupling of DHS-TD-GC×GC-TOFMS with PCA and HCA was able to highlight the differences and common typical VOC patterns among 24 samples of different Trappist and selected Canadian craft beers.

Comparison between dispersive solid-phase and dispersive liquid–liquid microextraction combined with spectrophotometric determination of malachite green in water samples based on ultrasound-assisted and preconcentration under multi-variable experimental design optimization

The ultrasound-assisted dispersive solid-phase microextraction (USA-DSPME) and the ultrasound-assisted dispersive liquid–liquid microextraction (USA-DLLME) developed for as an ultra preconcentration and/or technique for the determination of malachite green (MG) in water samples. Central composite design based on analysis of variance and desirability function guide finding best operational conditions and represent dependency of response to variables viz. volume of extraction, eluent and disperser solvent, pH, adsorbent mass and ultrasonication time has significant influence on methods efficiency. Optimum conditions was set for USA-DSPME as: 1mg CNTs/Zn:ZnO@Ni2P-NCs; 4min sonication time and 130μL eluent at pH 6.0. Meanwhile optimum point for USA-DLLME conditions were fixed at pH 6.0; 4min sonication time and 130, 650μL and 10mL of extraction solvent (CHCl3), disperser solvent (ethanol) and sample volume, respectively. Under the above specified best operational conditions, the enrichment factors for the USA-DSPME and USA-DLLME were 88.89 and 147.30, respectively. The methods has linear response in the range of 20.0 to 4000.0ngmL−1 with the correlation coefficients (r) between 0.9980 to 0.9995, while its reasonable detection limits viz. 1.386 to 2.348ngmL−1 and good relative standard deviations varied from 1.1% to 2.8% (n=10) candidate this method for successful monitoring of analyte from various media. The relative recoveries of the MG dye from water samples at spiking level of 500ngmL−1 were in the range between 94.50% and 98.86%. The proposed methods has been successfully applied to the analysis of the MG dye in water samples, and a satisfactory result was obtained.

Trial timing and pattern-information analyses of fMRI data

Pattern-information approaches to fMRI data analysis are becoming increasingly popular but few studies to date have investigated experimental design optimization for these analyses. Here, we tested several designs that varied in the number of trials and trial timing within fixed duration scans while participants encoded images of animals and tools. Trial timing conditions with fixed onset-to-onset timing ranged from slow 12-s trials with two repetitions of each item to quick 6-s trials with four repetitions per item. We also tested a jittered version of the quick design with 4–8s trials. We assessed the effect of trial timing on three dependent measures: category-level (animals vs. tools) decoding accuracy using a multivoxel pattern analysis, item-level (e.g., cat vs. dog vs. lion) information estimates using pattern similarity analysis, and memory effects comparing pattern similarity scores across repetitions of individual items subsequently remembered vs. forgotten. For single trial estimates, category decoding was equal across all trial timing conditions while item-level information and memory effects were better detected using slow trial timing. When modeling events on an item-by-item basis across all repetitions of a given item, a larger number of quick, regularly spaced trials provided an advantage over fewer slow trials for category decoding while item-level information was comparable across conditions. Jittered and non-jittered versions of the quick trial timing did not differ significantly in any analysis. These results will help inform experimental design choices in future studies planning to employ pattern-information analyses and demonstrate that design optimization guidelines developed for univariate analyses of a few conditions are not necessarily optimal for pattern-information analyses and condition-rich designs.

An Integrated Approach of System Dynamics, Orthogonal Experimental Design and Inexact Optimization for Supporting Water Resources Management under Uncertainty

An integrated approach of system dynamics (SD), orthogonal experimental design (OED) and inexact optimization modeling was proposed for water resources management under uncertainty. The developed method adopted a combination of SD and OED to identify key scenarios within multiple factors, through which interval solutions for water demands could be obtained as input data for consequential optimization modeling. Also, optimal schemes could be obtained in the combination of inexact two-stage stochastic programming and credibility constrained programming. The developed method was applied to a real-world case study for supporting allocation of multiple-source water resources to multiple users in Dalian city within a multi-year context. The results indicated that a lower credibility-satisfaction level would generate higher allocation efficiency, a higher system benefit and a lower system violation risk. The developed model could successfully reflect and address the variety of uncertainties through provision of credibility levels, which corresponds to the decision makers’ preference regarding the tradeoffs between system benefits and violation risks.

Application of cyclodextrins in antibody microparticles: potentials for antibody protection in spray drying

Objectives: Dry powder formulations are extensively used to improve the stability of antibodies. Spray drying is one of important methods for protein drying. This study investigated the effects of trehalose, hydroxypropyl beta cyclodextrin (HPBCD) and beta cyclodextrin (BCD) on the stability and particle properties of spray-dried IgG.Methods: D-optimal design was employed for both experimental design and analysis and optimization of the variables. The size and aerodynamic behavior of particles were determined using laser light scattering and glass twin impinger, respectively. In addition, stability, ratio of beta sheets and morphology of antibody were analyzed using size exclusion chromatography, IR spectroscopy and electron microscopy, respectively.Results: Particle properties and antibody stability were significantly improved in the presence of HPBCD. In addition, particle aerodynamic behavior, in terms of fine-particle fraction (FPF), enhanced up to 52.23%. Furthermore, antibody was better preserved not only during spray drying, but also during long-term storage. In contrast, application of BCD resulted in the formation of larger particles. Although trehalose caused inappropriate aerodynamic property, it efficiently decreased antibody aggregation.Conclusion: HPBCD is an efficient excipient for the development of inhalable protein formulations. In this regard, optimal particle property and antibody stability was obtained with proper combination of cyclodextrins and simple sugars, such as trehalose.

Experimental design optimization of reverse osmosis purification of pretreatedolive mill wastewater

The management of the effluents generated by olive oil industries, commonly known as olive mills, represents an ever increasing problem still unresolved. The core of the present work was the modelling and optimization of a reverse osmosis (RO) membrane operation for the purification of a tertiary-treated olive mill wastewater stream (OMW2TT). Statistical multifactorial analysis showed all the studied variables including the operating pressure (PTM), crossflow velocity (vt) and operating temperature (T) remarkably influence the permeate flux yielded by the selected membrane (p-value practically equal to zero), confirming a statistically significant relationship among the variables considered at 95% confidence level. However, PTM and T exhibit a deeper influence than vt, according to the p-values withdrawn from the analysis, being the squared effects significant too, but more in case of the former ones. The obtained contour plots and response surface support the former results. In particular, the optimized parameters were ambient temperature range (24–29.6°C), moderate operating pressure (31.5–35bar) and turbulent crossflow (4.1–5.1ms−1). In the end, the quality standards to reuse the purified effluent for irrigation purposes and discharge to sewers were stably ensured.

DOE Optimization of Nano-based Carrier of Pregabalin as Hydrogel: New Therapeutic & Chemometric Approaches for Controlled Drug Delivery Systems

Niosomes entrapping pregabalin (PG) were prepared using span 60 and cholesterol in different molar ratios by hydration method, the remaining PG from the hydrating solution was separated from vesicles by freeze centrifugation. Optimization of nano-based carrier of pregabalin (PG) was achieved. Quality by Design strategy was successfully employed to obtain PG-loaded niosomes with the desired properties. The optimal particle size, drug release and entrapment efficiency were attained by Minitab® program using design of experiment (DOE) that predicted the best parameters by investigating the combined effect of different factors simultaneously. Pareto chart was used in the screening step to exclude the insignificant variables while response surface methodology (RSM) was used in the optimization step to study the significant factors. Best formula was selected to prepare topical hydrogels loaded with niosomal PG using HPMC and Carbopol 934. It was verified, by means of mechanical and rheological tests, that addition of the vesicles to the gel matrix affected significantly gel network. In vitro release and ex vivo permeation experiments were carried out. Delivery of PG molecules followed a Higuchi, non Fickian diffusion. The present work will be of interest for pharmaceutical industry as a controlled transdermal alternative to the conventional oral route.

Optimization of operational parameters in moving bed biofilm reactor with low cost polystyrene biocarrier by the response surface method

The combined effects of three independent variables (carrier filling ratio, aeration rate and reactor run time (RRT)) were evaluated in a continuous moving bed biofilm reactor (MBBR) through central composite design (CCD) of the response surface methodology (RSM) for experimental design, analysis and process optimization for municipal wastewater treatment processes. A low-cost polystyrene biocarrier was designed and its efficiency in terms of organic and nutrient removal was evaluated in an MBBR. A mathematical–statistical tool represented by CCD was employed to assess the interactive effects of the three key independent operational parameters, inclusive of biocarrier filling ratio (0–70%), aeration rate (0.21–0.63 m3 h–1) and RRT (1–15 days), on the removal efficiency of chemical oxygen demand (COD), biochemical oxygen demand (BOD), total Kjeldahl nitrogen (TKN), total phosphorus (TP) and turbidity. The maximum efficiency obtained was at carrier filling rate 50%, aeration rate 0.42 m3 h–1 and RRT of 9 days, respectively. The results obtained for COD, BOD, TKN, TP and turbidity were 91.6, 92.9, 72.0, 55.0 and 46.0%, respectively. This study provides valuable information about interrelations of process parameters at different values of the operating variables. The results illustrate that this statistical tool could be effectively utilized for effluent organic load, nutrient and turbidity removal.

Implementation of an untargeted liquid chromatography ion mobility-mass spectrometry-based metabolomics method for inherited metabolic diseases investigation

High-resolution mass spectrometry coupled with pattern recognition techniques is an established tool to perform comprehensive metabolite profiling of biological datasets. Interpreting untargeted metabolomic data requires robust, reproducible and reliable analytical methods to translate results into biologically relevant and actionable knowledge. The analyses of biological samples were developed based on ultra-high performance liquid chromatography (UHPLC) coupled to ion mobility - mass spectrometry (IM-MS). An innovative strategy for optimizing simultaneously the analytical conditions for untargeted UHPLC-IM-MS methods is proposed using an experimental design approach. Optimization experiments were conducted through a screening process designed to identify the influential factors that have significant effects on the selected responses (total number of peaks and number of reliable peaks). For this purpose, full and fractional factorial designs were used while partial least squares regression was used for experimental design modeling and optimization of parameter values. The total number of peaks yielded the best predictive model and is used for the optimization of parameters settings. Fifty-five urine samples have been used to assess the developed method. Twenty-two controles and 33 diseases allocated to five different groups: propionic aciduria, cystinuria, tyrosiniemia, mucopolysaccharidoses (I, IV and VI) and creatine metabolism defect have been metabolically profiled. Multivariate modeling has been performed on the data. This pilot study yielded predictive models that allowed clear classification of the different diseases. These promising results highlight the potential of this new approach in the screening of IEMs and in patient stratification. An assay on a larger cohort is needed to assess the clinical validity of the method. (This work is co-supported by European Union, Region Normandie, Inserm, CNRS, Normandy University and IRIB. Europe gets involved in Normandie with European Regional Development Fund (ERDF).)

Experimental Investigation and Design Optimization of Face Milling Parameters on Monel K-500 by Doe Concept

Experimental Investigation and Design Optimization of Face Milling Parameters on Monel K-500 by Doe Concept

The investigation of expanded polystyrene creep behaviour

The results obtained in long-term testing under constant compressive stress of the cut from the Slabs EPS 50/100 and EPS 150 with the density ranging from 15 to 24 kg/m 3 , which were manufactured by the same manufacturer by foaming EPS solid granules (beads) in closed volume. The creep strain of the above described specimens was used as a criterion for estimating the deformability of the EPS slabs under long-term compressive stress. It was measured using special stands EN 1606, maintaining constant stress during the fixed time interval t n =122 days. Creep strains were determined by the methods described in EN 1606 for constant stress σ c =0.35σ 10% (compressive stress σ 10% was determined in accordance with EN 826:2013. The long-term compressive stress measurement error did not exceed 1 %, while the creep strain measurement error was not larger than 0,005 mm. The tests were conducted at the ambient temperature of (23±2)°С and relative humidity of (50±5) %.The long-term constant compressive load σ c =0.35σ 10% . The method of mathematical and statistical experimental design optimization models taking into account the thickness of specimens is proposed to determine the creep compliance I c ( t n ) the creep strain e c ( t n ) and predictive point estimate of creep strain e c ( T ). Graphical interpretation of the abstained models is also presented. It should be noted that the abstained equations may be used in practice for estimating the creep strains at time t n =122 days and predictive estimates of e c ( T ) for the load time of 10 years.