BRADSHAW: a system for automated molecular design

This paper introduces BRADSHAW (Biological Response Analysis and Design System using an Heterogenous, Automated Workflow), a system for automated molecular design which integrates methods for chemical structure generation, experimental design, active learning and cheminformatics tools. The simple user interface is designed to facilitate access to large scale automated design whilst minimising software development required to introduce new algorithms, a critical requirement in what is a very fast moving field. The system embodies a philosophy of automation, best practice, experimental design and the use of both traditional cheminformatics and modern machine learning algorithms.

Truth in science: experimental design and the legacy of John D Biggers, PhD., DSc

The current article presents a brief historical perspective on Professor John D Biggers, PhD, DSc. who died on 7 April, 2018. His interests covered reproductive physiology, embryo culture, cryobiology, sperm preservation, statistics and experimental design, and the history and ethics of human reproductive biology. Emphasis is placed on John Biggers' approach to the development of media for the culture of mammalian preimplantation embryos and to correct several minor misconceptions that have arisen in recent years regarding some of his studies. Much can be learned from his detailed approach to scientific investigation and experimental design. His scientific accomplishments and seminal contributions are important, but the tapestry of his life and legacy continue to be woven through the many students, fellows, and collaborators with whom he worked with over many years. The present article builds on a previous conversation that Michael Summers and Catherine Racowsky had with John Biggers that was published in 2008 [1].

Reuse and recycle solutions in refineries by ozone-based advanced oxidation processes: A statistical approach

Fresh water sources are under pressure globally by the increasing population and consequently increasing production, which increases the water demand day by day. Thus, decreasing the industrial fresh water demand and wastewater production became crucial both for the water availability in the future and for its impact to the environment. This study examined the ozone-based treatments as the possible solution to a refinery to treat the effluent already treated by the traditional techniques to reach the final requirements for reuse and recycle purposes. The screening tests performed by fractional factorial design revealed that the significant parameters for the treatment were ozone feed ratio, H₂O₂ amount and processing time while pH was found insignificant for this case. Based on the box-Behnken response surface methodology for effluent collected after biological treatment, the significant parameters were optimized as the ozone ratio of 0.9 g/h, H₂O₂ amount of 47 mg/L and 60 min duration. However, in case of increasing the H₂O₂ amount to 80 mg/L the duration can be minimized to 37.5 min decreasing the energy and reagent consumption costs by a 37%, reaching a final total organic carbon (TOC) under 4 mg/L, that is the target for reuse possibilities.

Magnetic Cu: CuO-GO nanocomposite for efficient dispersive micro-solid phase extraction of polycyclic aromatic hydrocarbons from vegetable, fruit, and environmental water samples by liquid chromatographic determination

In this research, we presented a magnetic dispersive micro-solid phase extraction (MD-μ-SPE) method coupled with high performance liquid chromatography (HPLC) based on the use of magnetic Cu: CuO-Graphene Oxide (GO) nanocomposite (Fe₃O₄/Cu: CuO/GO-NC) for the separation and preconcentration of polycyclic aromatic hydrocarbons (PAHs), i.e. naphthalene (Nap), phenanthrene (Phe), anthracene (Ant), and pyrene (Pyr), in vegetable (onion, tomato, carrot, herb, watermelon, lettuce, eggplant, and chili pepper), fruit (apple, watermelon, and grape), wastewater, and water samples. The MD-μ-SPE of PAHs in matrix samples was carried out, and the impacts of pH, ionic strength, extraction time, temperature, eluent volume, and sorbent mass on the recovery of PAHs were investigated by using Placket-Burman design (PBD). In addition, by using the central composite design (CCD), the best combination of each important variable was measured. Sorbent mass of 14 mg, eluent volume of 200 μL, and 12 min extraction time at the central level of other factors were optimal conditions of pretreatment for the highest extraction recovery (ER%) of trace PAHs. Under the optimal conditions, the method proposed herein provided high enrichment factors ranged from 116.51 to 133.05, good linearity in the range of 10-3800 ng mL^-1 for Pyr, 3.0-3500 ng mL^-1 for Phe, 5.0-3200 ng mL^-1 for Nap, and 5.0-3000 ng mL^-1 for Ant with coefficient of determination (R²) values between 0.9889 and 0.9963, low limits of detection (LOD) and quantification (LOQ) in the range of 0.015-0.061 and 0.485-2.034 ng mL^-1, respectively, and also satisfactory spiked recoveries (between 95.1% and 106.8%) with the relative standard deviations (RSDs) values in the range of 1.73%-5.62%. The Fe₃O₄/Cu: CuO/GO-NC-based MD-μ-SPE followed by HPLC-UV corroborated promising results for the convenient and effective determination of PAHs in the samples of vegetables, fruits, and environmental water. The results of this study revealed that our developed method is easy, feasible, precise, highly effective, and convenient to operate for the trace analysis of PAHs in different real samples. The extraction recovery was about 90% of the initial recovery after the sorbent usage for three times; therefore, the Fe₃O₄/Cu: CuO/GO-NC can readily be regenerated.

Binary vs. continuous experimental designs for the study of unconscious perceptual processing

Binary vs. continuous conceptualizations of consciousness may have an unstated influence on experimental designs in unconscious perception research. The binary approach aims to compare a conscious condition (e.g., supraliminal, no or weak stimulus masking) to an unconscious condition (e.g., subliminal, heavy stimulus masking). In contrast, continuous designs tend to vary stimulus energy along a near-threshold continuum to determine changes in perception as a function of stimulus energy (or duration). The present study compared two experimental designs, binary vs. continuous, for the influence of target-masked prime stimuli on a Stroop task. The display parameters were inspired by emotional Stroop studies reporting unconscious perception. Neither experiment produced strong evidence of unconscious perception, but the experiment with a continuous design was more informative. We thus recommend sampling a range of near-threshold display parameters to yield straight-forward, unambiguous interpretations.

On the utility of RNA sample pooling to optimize cost and statistical power in RNA sequencing experiments

Background

In gene expression studies, RNA sample pooling is sometimes considered because of budget constraints or lack of sufficient input material. Using microarray technology, RNA sample pooling strategies have been reported to optimize both the cost of data generation as well as the statistical power for differential gene expression (DGE) analysis. For RNA sequencing, with its different quantitative output in terms of counts and tunable dynamic range, the adequacy and empirical validation of RNA sample pooling strategies have not yet been evaluated. In this study, we comprehensively assessed the utility of pooling strategies in RNA-seq experiments using empirical and simulated RNA-seq datasets.

Result

The data generating model in pooled experiments is defined mathematically to evaluate the mean and variability of gene expression estimates. The model is further used to examine the trade-off between the statistical power of testing for DGE and the data generating costs. Empirical assessment of pooling strategies is done through analysis of RNA-seq datasets under various pooling and non-pooling experimental settings. Simulation study is also used to rank experimental scenarios with respect to the rate of false and true discoveries in DGE analysis. The results demonstrate that pooling strategies in RNA-seq studies can be both cost-effective and powerful when the number of pools, pool size and sequencing depth are optimally defined.

Conclusion

For high within-group gene expression variability, small RNA sample pools are effective to reduce the variability and compensate for the loss of the number of replicates. Unlike the typical cost-saving strategies, such as reducing sequencing depth or number of RNA samples (replicates), an adequate pooling strategy is effective in maintaining the power of testing DGE for genes with low to medium abundance levels, along with a substantial reduction of the total cost of the experiment. In general, pooling RNA samples or pooling RNA samples in conjunction with moderate reduction of the sequencing depth can be good options to optimize the cost and maintain the power.

Effectiveness of simulation learning program for mastering public health nursing skills to enhance strength of community: A quasi-experimental design

PURPOSE

The purpose of this study is to develop a simulation learning program for mastering public health nursing skills to enhance strength of community, and to verify its effectiveness.

METHODS

The program is one-day session to master the skills from three exercises. This study adopts a quasi-experimental design. We selected unbiased 34 participants in intervention group and 30 participants in control group, and conducted self-administered questionnaire surveys at three points in time: pre, post 1 and post 2. Three tools were used to measure the required outcome. For the outcome evaluation, we calculated the changes in the mean value of each tool between pre and post 1 and between pre and post 2, and compared them between the two groups.

RESULTS

The change of intervention group in the total score at the post 1 stage from the pre stage was significantly higher than control group regarding each of the scales (P < .05).

CONCLUSIONS

The program was found to be effective in upgrading the skills of less-experienced public health nurses to enhance strength of community.

Guidelines for the experimental design of pharmacokinetic studies with nanomaterials in preclinical animal models

A shared feature in the value proposition of every nanomaterial-based drug delivery systems is the desirable improvement in the disposition (or ADME) and pharmacokinetic profiles of the encapsulated drug being delivered. Remarkable progress has been made towards understanding the complex and multifactorial relationships between pharmacokinetic profiles and nanomaterial physicochemical properties, biological interactions, species physiology, etc. These advances have fuelled the rational design of numerous nanomaterials with long-circulation times and improved tissue accumulation (e.g., in tumours). Unfortunately, a central weakness in many of these research efforts has been the inconsistent and insufficient characterisation of the pharmacokinetic profiles of nanomaterials in scientific reporting-a problem affecting the majoirty of of contemporary nanomaterials literature and innovative nanomaterials in early stages of preclinical development especially. Given the significant role of pharmacokinetic assessments to serve as guideposts for deciding whether to continue with the preclinical development and clinical translation of drug delivery systems, the prevalence of poor pharmacokinetic characterisations in nanomaterials research is particularly alarming. A conspicuous problem in many reports is the inappropriate selection of experimental designs and methodologies for studying nanomaterial pharmacokinetics, the consequences of which are increased uncertainty over the accurate interpretation of reported pharmacokinetic data and diminished experimental reproducibility throughout the field. Thus, there is renewed interest in the establishment of consistent and comprehensive strategies for designing preclinical experiments to assess the pharmacokinetics of nanomaterials with diverse physicochemical properties. Towards this end, herein are proposed simple guidelines for the experimental design of pharmacokinetic studies with nanomaterials drawn from the best research practices, principle strategies, and important considerations used in industry for collecting pharmacokinetic data in preclinical animal models. Specifically, key experimental design factors in these studies are identified and examined in the context of nanomaterials for optimality, including blood sampling strategy and technique, sample allocation and sampling time window, test species selection, experimental sources of pharmacokinetic variability, etc. Methods for noninvasive imaging-derived pharmacokinetic assessments of theranostic nanomaterials are also explored with particular focus on emission tomography imaging modalities. Taken together, this review will provide nanomaterial researchers with practical knowledge and pragmatic recommendations for selecting the best designs and methodologies for assessing the pharmacokinetic profiles of their nanomaterials, and hopefully maximise the chances of translational success of these innovative products into humans.

gscreend: modelling asymmetric count ratios in CRISPR screens to decrease experiment size and improve phenotype detection

Pooled CRISPR screens are a powerful tool to probe genotype-phenotype relationships at genome-wide scale. However, criteria for optimal design are missing, and it remains unclear how experimental parameters affect results. Here, we report that random decreases in gRNA abundance are more likely than increases due to bottle-neck effects during the cell proliferation phase. Failure to consider this asymmetry leads to loss of detection power. We provide a new statistical test that addresses this problem and improves hit detection at reduced experiment size. The method is implemented in the R package gscreend, which is available at http://bioconductor.org/packages/gscreend.

Ultrasonic-assisted micro solid phase extraction of arsenic on a new ion-imprinted polymer synthesized from chitosan-stabilized pickering emulsion in water, rice and vegetable samples

Pickering emulsion polymerization has been employed for the Ultrasonic assisted-micro solid phase extraction (UA-µSPE) of ultra trace arsenic species by a new magnetic ion imprinted polymer (MIIP) prior to hydride generation atomic absorption spectrometry. 2-acetyl benzofuran thiosemicarbazone (2-ABT) as a new chelating agent and core- shell hydrophobic magnetic nanoparticles was synthesized and the polymerization was carried out at the presence of arsenic - ligand complex, crosslinker, monomer, initiator, stabilizing agent and water-oil emulsion magnetic carrier. In second step, the nanoparticles and polymers were characterized. The analytical parameters such as pH, amount of polymer and ultrasonic time were selected and optimozed by Plackett-Burman and Box-Behnken designs respectively. Linear dynamic range, detection limit and relative standard deviation were 0.01-85.000 µg·L^-l, 0.003 µg·L^-l, and 3.21%, respectively. The proposed preconcentration procedure was successfully applied to the determination of arsenic ion in a wide range of food samples with different and complex matrixes.

A simple magnetic solid-phase extraction method based on magnetite/graphene oxide nanocomposite for pre-concentration and determination of melamine by high-performance liquid chromatography

In this study, a clean and simple magnetic solid-phase extraction (MSPE) procedure using magnetite/graphene oxide nanocomposite as an adsorbent was developed for melamine separation and preconcentration from water and dairy products. After synthesis and characterization of the adsorbent, adsorption isotherms and kinetic studies of the adsorption were carried out. The analyte quantification was performed by reversed phase high-performance liquid chromatography after elution of the preconcentrated analytes from the adsorbent surface. Several factors affecting the extraction/preconcentration procedure such as pH, adsorbent amount, extraction time, sample volume, type, and volume of eluent were investigated. The optimizing of some important parameters was assessed by employing a response surface method. The constructed calibration curve in the optimized conditions is linear in the working range of 0.10-100 μg L^-1 with a correlation coefficient of 0.9999. The detection limit, limit of quantification, and enrichment factor are 0.03 μg L^-1, 0.10 μg L^-1, and 500, respectively. The melamine relative recoveries from different real samples are between 97.20 and 103.10% with relative standard deviations of 1.07-4.98%.

How Politico-Economic Systems Shape Individuals' Value of Elderly Care: Evidence From the German Reunification

BACKGROUND AND OBJECTIVES

Perceptions of how societies should care for the elderly people can differ among countries. This study examines to what extent individuals' value of informal care is shaped by the politico-economic system in which they grew up and if this value adjusts once an individual lives in a different politico-economic system.

RESEARCH DESIGN AND METHODS

We use data from the German Family Panel and take advantage of the unique setting of the German separation and reunification. Probit models are used to examine the effect of being born in East Germany on individuals' value of informal care relative to employment at different birth cohorts and survey waves (N = 14,093). Average marginal effects are calculated.

RESULTS

Twenty years after reunification, East Germans who spent their adolescence under communism exhibit a higher value of informal care relative to employment than West Germans who grew up in a western social market economy. Differences in values between East and West Germans do not significantly converge over time.

DISCUSSION AND IMPLICATIONS

Individuals' value of informal care is deeply shaped by the politico-economic system in which they grew up. If immigration policies are introduced to increase the care for elderly people, differences in individuals' cultural perceptions of elderly care should be considered as these will not suddenly adjust.

Pharmacokinetic incompatibility of the Huanglian-Gancao herb pair

Background

Pharmacokinetic interaction is one of the most important indices for the evaluation of the compatibility of herbal medicines. Both Gancao (Glycyrrhizae Radix et Rhizoma) and Huanglian (Coptidis Rhizoma) are commonly used traditional Chinese medicines (TCMs). In this study, the influence of Gancao on the pharmacokinetics of Huanglian was systematically studied by using berberine as a pharmacokinetic marker.

Methods

Extracts of the herbal pieces of Huanglian and the herb pair (Huanglian plus Gancao) were prepared with boiling water. The concentration of berberine in the samples was analyzed using liquid chromatography-mass spectrometry. The total amounts of berberine in all extract samples were compared. Comparative pharmacokinetic studies of Huanglian and the herb pair were conducted in ICR mice. In vitro berberine absorption and efflux were studied using mice gut sacs. The equilibrium solubility of berberine in the extracts was determined. The in vitro dissolution of berberine was comparatively studied using a rotating basket method.

Results

Gancao significantly reduced berberine exposure in the portal circulation (425.8 ng·h/mL vs. 270.4 ng·h/mL) and the liver (29,500.8 ng·h/mL vs. 15,422.4 ng·h/mL) of the mice. In addition, Gancao decreased the peak concentration (C_max) of berberine in the portal circulation (104.3 ng·h/mL vs. 76.5 ng·h/mL) and liver (4926.1 ng·h/mL vs. 2642.8 ng·h/mL) of mice. Significant influences of Gancao on the amount of berberine extracted (32% reduction), the solubility of berberine (34.7% compared with the control group), and dissolution (88.7% vs. 66.1% at 15 min in acid buffer and 68% vs. 51.8% at 15 min in phosphate buffer) were also revealed. Comparative pharmacokinetic studies in ICR mice indicated that the formation of sediment was unfavorable in terms of berberine absorption (345.3 ng·h/mL vs. 119.8 ng·h/mL).

Conclusions

Gancao was able to reduce intestinal absorption and in vivo exposure of berberine in Huanglian via the formation of sediment, which caused reductions in the extracted amount, solubility, and dissolution of berberine.

Metallic copper removal optimization from real wastewater using pulsed electrodeposition

The recovery of metals from wastewater is a recurrent problem due to numerous productive activities that produce wastewaters rich in toxic metals. Within this context, this research presents the study and optimization of copper recovery of real wastewater using pulsed electrodeposition. The studied parameters - method, current, temperature, and rotation- influence both the removal of Cu and the composition of the formed deposit, noting that the variation of these parameters enables the removal of copper with formation from crystalline oxides to crystalline copper in its metallic form. The process was optimized, and a 33.59% copper removal from a real wastewater with a deposition efficiency of 84.36% in 30 min was deemed optimal, using fast galvanic pulse, t_on = 1 ms, 190 mA, 70 rpm, and 37 °C. For coating in the optimum point, a metallic and crystalline copper with 100% purity was obtained.

Optimization of the collagen extraction from Nile tilapia skin (Oreochromis niloticus) and its hydrogel with hyaluronic acid

Nile tilapia skin, an abundant waste from fish processing, can be used for collagen extraction, which has a high aggregated value for biomedical applications. Collagen extraction was conducted under different reaction conditions (time, temperature, and concentration of acetic acid) in order to optimize the yield without compromising the integrity of the collagen. Temperature and time were responsible for increased yield. The extraction at 4 and 20 °C produced the acid-solubilized collagen (ASC) with the intact triple helix and was analysed by Fourier-transform infrared spectroscopy (FT-IR) and circular dichroism (CD). The optimized ASC (which used 0.35 mol/L of acetic acid at 20 °C) was consumed to obtain for the first-time fish-based hydrogels with hyaluronic acid (HA) crosslinked with 1-ethyl-3-(3-dimethylaminopropryl carbodiimide (EDC) and N-hydroxysuccinimide (NHS). The hydrogel was characterized by FT-IR, rheology, swelling, and scanning electron microscopy (SEM), confirming that cross-linking was accomplished. It possesses a robust organized network, swells 255 % in PBS and bears interconnected pores with a diameter in the range of 10-100 μm. Until now, col-HA hydrogels crosslinked with EDC/NHS have not been reported in literature with collagen from Nile Tilapia skin. Fish collagen can be a better option than those from land-based animals (cow and pig).

Optimization of uranium soil decontamination in alkaline washing using mechanical stirring and ultrasound field

The ex situ decontamination of uranium polluted soils was performed by alkaline washing using mechanical agitation and ultrasound field. Two types of polluted soils were considered in terms of texture and organic content. The tests were performed using experimental design: a 2³ factorial plan for mechanical washing and Taguchi L₁₈ orthogonal matrix for ultrasound (US)-assisted decontamination. The factors considered in mechanical washing were temperature, duration, and pH. For ultrasound decontamination, the US frequency was added. The optimum was estimated based on statistical analysis and validated by confirmation experiments. The study revealed that in ultrasound field, the decontamination degree is increased with over 25% compared with mechanical stirring, while the duration of the process is drastically reduced (from 120 to 25 min). The most important factor leading to the increase of decontamination is the ultrasound frequency. To refine the result, artificial neural network modeling and subsequent optimization by genetic algorithms were also carried out for the decontamination in ultrasound field, and new optimum operating conditions were identified and validated. The best operating conditions identified were temperature around 50 °C, pH = 8, and ultrasound frequency of 24 kHz. In these conditions, the decontamination degree reached 85% for Soil 1 (characterized by low clay and organic content) and 69% for Soil 2 (with high clay and organic content).

Reducing Ageism: Education About Aging and Extended Contact With Older Adults

BACKGROUND AND OBJECTIVES

Ageism is of increasing concern due to the growing older population worldwide and youth-centered focus of many societies.

RESEARCH DESIGN AND METHODS

The current investigation tested the PEACE (Positive Education about Aging and Contact Experiences) model for the first time. Two online experimental studies examined 2 key factors for reducing ageism: education about aging (providing accurate information about aging) and extended contact (knowledge of positive intergenerational contact) as well as their potential combined effect (education plus extended contact).

RESULTS AND DISCUSSION

In Study 1, 354 undergraduates in all 3 experimental conditions (vs. control participants) reported less negative attitudes toward older adults (delayed post-test) and greater aging knowledge (immediate and delayed post-tests), when controlling for pre-study attitudes. In Study 2, 505 national community participants (ages 18-59) in all experimental conditions (vs. control participants) reported less negative attitudes toward older adults (immediate post-test) and greater aging knowledge (immediate and delayed post-tests). In summary, across 2 online studies, education about aging and knowledge of intergenerational extended contact improved attitudes toward older adults and aging knowledge.

IMPLICATIONS

Thus, brief, online ageism-reduction strategies can be an effective way to combat ageism. These strategies hold promise to be tested in other settings, with other samples, and to be elaborated into more in-depth interventions that aim to reduce ageism in everyday culture.

Oriented Immobilization on Gold Nanoparticles of a Recombinant Therapeutic Zymogen

Direct immobilization of functional proteins on gold nanoparticles (AuNPs) affects their structure and function. Changes may vary widely and range from strong inhibition to the enhancement of protein function. More often though the outcome of direct protein immobilization results in protein misfolding and the loss of protein activity. Additional complications arise when the protein being immobilized is a zymogen which requires and relies on additional protein-protein interactions to exert its function. Here we describe molecular design of a glutathione-S-transferase-Staphylokinase fusion protein (GST-SAK) and its conjugation to AuNPs. The multivalent AuNP-(GST-SAK)n complexes generated show plasminogen activation activity in vitro. The methods described are transferable and could be adapted for conjugation and functional analysis of other plasminogen activators, thrombolytic preparations or other functional enzymes.

Digital Twins and Their Role in Model-Assisted Design of Experiments

Rising demands for biopharmaceuticals and the need to reduce manufacturing costs increase the pressure to develop productive and efficient bioprocesses. Among others, a major hurdle during process development and optimization studies is the huge experimental effort in conventional design of experiments (DoE) methods. As being an explorative approach, DoE requires extensive expert knowledge about the investigated factors and their boundary values and often leads to multiple rounds of time-consuming and costly experiments. The combination of DoE with a virtual representation of the bioprocess, called digital twin, in model-assisted DoE (mDoE) can be used as an alternative to decrease the number of experiments significantly. mDoE enables a knowledge-driven bioprocess development including the definition of a mathematical process model in the early development stages. In this chapter, digital twins and their role in mDoE are discussed. First, statistical DoE methods are introduced as the basis of mDoE. Second, the combination of a mathematical process model and DoE into mDoE is examined. This includes mathematical model structures and a selection scheme for the choice of DoE designs. Finally, the application of mDoE is discussed in a case study for the medium optimization in an antibody-producing Chinese hamster ovary cell culture process.

Review of Batch Effects Prevention, Diagnostics, and Correction Approaches

Systematic technical variation in high-throughput studies consisting of the serial measurement of large sample cohorts is known as batch effects. Batch effects reduce the sensitivity of biological signal extraction and can cause significant artifacts. The systematic bias in the data caused by batch effects is more common in studies in which logistical considerations restrict the number of samples that can be prepared or profiled in a single experiment, thus necessitating the arrangement of subsets of study samples in batches. To mitigate the negative impact of batch effects, statistical approaches for batch correction are used at the stage of experimental design and data processing. Whereas in genomics batch effects and possible remedies have been extensively discussed, they are a relatively new challenge in proteomics because methods with sufficient throughput to systematically measure through large sample cohorts have only recently become available. Here we provide general recommendations to mitigate batch effects: we discuss the design of large-scale proteomic studies, review the most commonly used tools for batch effect correction and overview their application in proteomics.

Harmonizing analytical chemistry and clinical epidemiology for human biomonitoring studies. A case-study of plastic product chemicals in urine

There is an interdisciplinary interface between analytical chemistry and epidemiology studies with respect to the design, execution, and analysis of environmental epidemiology cohorts and studies. Extracting meaningful results linking chemical exposure to human health outcomes begins at study design and spans the entire workflow. Here we discuss analytical experimental design from an exposure science perspective, and propose a reporting checklist for the design of human biomonitoring studies. We explain key analytical chemistry concepts of blanks and limits of reporting and present a case series of plastic product chemical exposure in prenatal urine specimens from the Barwon Infant Study.

Intelligent-activated carbon prepared from pistachio shells precursor for effective adsorption of heavy metals from industrial waste of copper mine

A novel and efficient bio-adsorbent based on magnetic activated carbon nanocomposites (MAC NCs)-modified by sulfamic acid (H₃NSO₃) has been developed from pistachio shell precursor as agricultural by-products and then was applied for heavy metal removal. Design an experimental model (Central Composite Design (CCD)) for adopting surface response could efficiently be used for adsorption process, and it is an economical way of obtaining the optimal adsorption conditions based on the limited number of experiments. The variants of adsorbent dosage, metal ion concentration, and contact time were optimized for Cu(II) metal by CCD. In addition, adsorption capacity and isoelectric point (pHzpc) of adsorbent were studied at different pH values. Kinetic and isotherm of adsorption were investigated via the Langmuir and the pseudo-second-order model. The maximum adsorption capacity using the Langmuir model was 277.77 mg g^-1 for Cu(II) ions on H₂NSO₃-MAC NCs. Then adsorption process was investigated for ions of Fe(II), Zn(II), and Ni(II) under optimized condition. Also, the competitive adsorption of Fe(II), Zn(II), and Ni(II) ions mixed solution onto H₂NSO₃-MAC NCs was conducted. Adsorption-desorption results exhibited that the H₂NSO₃-MAC NCs can be used up to seven cycles while they have excellent performance. Finally, to evaluate the efficiency of this bio-adsorbent, the removal of heavy metals from wastewater of the Sarcheshmeh copper mine as a real sample was studied. Graphical abstract.

Multivariate Optimization: A Powerful Tool for the Systematic Control of Quantum Dots Properties

In this chapter, we present some chemometric tools used in the area of experimental design and multivariate optimization. To make the subject more understandable, a didactic example employing colloidal aqueous synthesis of quantum dots is employed. We start with the factorial design that is very useful in screening which factors are important to the response of interest. All statistical calculations and interpretations of individual and interaction effects are detailed. Then, we describe how to build and evaluate empirical models by analysis of variance (ANOVA) to explain the behavior of the data set. Finally, the response surface methodology (RSM) is described. We expect this chapter to be useful as a guide for those who seek to solve synthetic problems in a quicker and more objective way, providing particularly a wider perception of the experimental factors that dominate the responses of interest of a system under study.

Statistical optimization and characterization of a biocellulose produced by local Egyptian isolate Komagataeibacter hansenii AS.5

Optimization of the culture parameters used for biocellulose (BC) production by a previously isolated bacterial strain (Komagataeibacter hansenii AS.5) was carried out. The effect of nine culture parameters on BC production was evaluated by implementing the Plackett-Burman design, and the results revealed that, the most significant variables affecting BC production were MgSO₄, ethanol, pH and yeast extract. A three-level and four-factor Box-Behnken design was applied to determine the optimum level of each significant variable. According to the results of the Plackett-Burman (PBD) and Box-Behnken designs (BBD), the following medium composition and parameters were calculated to be optimum (g/l): glucose 25, yeast extract 13, MgSO₄ 0.15, KH₂PO₄ 2, ethanol 7.18 ml/l, pH 5.5, inoclume size 7%, cultivation temperature 20 °C and incubation time 9 days. Characterization of purified BC was performed to determine the network morphology by scanning electron microscopy, crystallinity by X-ray diffraction, chemical structure and functional groups by Fourier-transform infrared spectroscopy, thermal stability by thermogravimetric analysis and mechanical properties such as Young's modulus, tensile strength and elongation at beak % of BC.

Experimental design for parameter estimation in steady-state linear models of metabolic networks

Metabolic networks are typically large, containing many metabolites and reactions. Dynamical models that aim to simulate such networks will consist of a large number of ordinary differential equations, with many kinetic parameters that must be estimated from experimental data. We assume these data to be metabolomics measurements made under steady-state conditions for different input fluxes. Assuming linear kinetics, analytical criteria for parameter identifiability are provided. For normally distributed error terms, we also calculate the Fisher information matrix analytically to be used in the D-optimality criterion. A test network illustrates the developed tool chain for finding an optimal experimental design. The first stage is to verify global or pointwise parameter identifiability, the second stage to find optimal input fluxes, and finally remove redundant measurements.