Unraveling the interplay of common groundwater ions in arsenic removal by sulfide-modified nanoscale zerovalent iron.

Sulphidation of nZVI (S-nZVI) has shown to significantly improve the arsenic removal capacity of nZVI, concurrently modifying the sequestration mechanism. However, to better apply S-nZVI for groundwater arsenic remediation, the impact of groundwater coexisting ions on the efficacy of arsenic uptake by S-nZVI needs to be investigated. This present study evaluates the potential of S-nZVI to remove arsenic in the presence of typical groundwater coexisting ions such as Cl-, HA, HCO3-, PO43- and SO42- through batch adsorption experiments. Individually, PO43- and HA had a dominant inhibition effect, while SO42- promoted As(III) removal by S-nZVI. Conversely, for As(V) removal, HCO3- and SO42- impeded the removal process. X-ray spectroscopic investigation suggests that the coexisting ions can either compete with arsenic for the adsorption sites, influence the S-nZVI corrosion rates and/or generate distinct corrosion products, thereby interfering with arsenic removal by S-nZVI. To investigate the cumulative effects of these ions, a 25-1 Fractional Factorial Design of experiments was employed, wherein the concentration of all the ions were varied simultaneously in an optimized manner, and their impact on arsenic removal by S-nZVI was observed. Our results shows that when these ions are present concurrently, PO43-, SO42- and HA still exerted a dominant influence on As(III) removal, whereas HCO3- was the main ions affecting As(V) removal, although the combined influence of the ions was not merely a summation of their individual effects. Overall, the finding of our study might provide valuable insight for predicting the actual performance of S-nZVI in field-scale applications for the remediation of arsenic-contaminated groundwater.

Three steps toward dose optimization for oncology dose finding.

Background: Traditional dose selection for oncology registration trials typically employs a one- or two-step single maximum tolerated dose (MTD) approach. However, this approach may not be appropriate for molecularly targeted therapy, which tends to have toxicity profiles that are markedly different than cytotoxic agents. The US Food and Drug Administration launched Project Optimus to reform dose optimization in oncology drug development and has recently released a related guidance for industry. Methods: We propose a "three steps toward dose optimization" procedure, in response to these initiatives, and discuss the details in dose-optimization designs and analyses. The first step is dose escalation to identify the MTD or maximum administered dose with an efficient hybrid design, which can offer good overdose control and increases the likelihood of the recommended MTD being close to the true MTD. The second step is the selection of appropriate recommended doses for expansion (RDEs), based on all available data, including emerging safety, pharmacokinetics, pharmacodynamics, and other biomarker information. The third step is dose optimization, which uses data from a randomized fractional factorial design with multiple RDEs explored in multiple tumor cohorts during the expansion phase to ensure a feasible dose is selected for registration trials, and that the tumor type most sensitive to the investigative treatment is identified. Conclusion: We believe using this three-step approach can increase the likelihood of selecting an optimal dose for a registration trial that demonstrates a balanced safety profile while retaining much of the efficacy observed at the MTD.

Fabrication and Optimization of Electrospun Shellac Fibers Loaded with Senna alata Leaf Extract.

Single-fluid electrospinning creates nanofibers from molten polymer solutions with active ingredients. This study utilized a combination of a fractional factorial design and a Box-Behnken design to examine crucial factors among a multitude of parameters and to optimize the electrospinning conditions that impact fiber mats' morphology and the entrapment efficiency of Senna alata leaf extract. The findings indicated that the shellac content had the greatest impact on both fiber diameter and bead formation. The optimum electrospinning conditions were identified as a voltage of 24 kV, a solution feed rate of 0.8 mL/h, and a shellac-extract ratio of 38.5:3.8. These conditions produced nanosized fibers with a diameter of 306 nm, a low bead-to-fiber ratio of 0.29, and an extract entrapment efficiency of 96% within the fibers. The biphasic profile of the optimized nanofibers was confirmed with an in vitro release study. This profile consisted of an initial burst release of 88% within the first hour, which was succeeded by a sustained release pattern surpassing 90% for the next 12 h, as predicted with zero-order release kinetics. The optimized nanofibers demonstrated antimicrobial efficacy against diverse pathogens, suggesting promising applications in wound dressings and protective textiles.

Improvement of Targeted Fungi Secondary Metabolite Production Using a Systematic Experimental Design and Chemometrics Analysis.

Fungi are well-known producers of chemically diverse and biologically active secondary metabolites. However, their production yields through fermentation may hamper structural analysis and biological activity downstream investigations. Herein, a systematic experimental design that varies multiple cultivation parameters, followed by chemometrics analysis on HPLC-UV-MS or UHPLC-HRMS/MS data, is presented to enhance the production yield of fungal natural products. The overall procedure typically requires 3-4 months of work when first developed, and up to 3 months as a routine procedure.

A sensitive UPLC-MS/MS method for the simultaneous assay and trace level genotoxic impurities quantification of SARS-CoV-2 inhibitor-Molnupiravir in its pure and formulation dosage forms using fractional factorial design.

Two potential genotoxic impurities were identified (PGTIs)-viz. 4-amino-1-((2R,3R,4S,5R)-3,4-dihydroxy-5-(hydroxymethyl)tetrahydrofuran-2-yl)pyrimidin-2(1H)-one (PGTI-1), and 1-(2R,3R,4S,5R)-3,4-dihydroxy-5-(hydroxymethyl)tetrahydrofuran-2-yl)pyrimidin-2,4(1H,3H)-one (PGTI-II) in the Molnupiravir (MOPR) synthetic routes. COVID-19 disease was treated with MOPR when mild to moderate symptoms occurred. Two (Q)-SAR methods were used to assess the genotoxicity, and projected results were positive and categorized into Class-3 for both PGTIs. A simple, accurate and highly sensitive ultra-performance liquid chromatography-mass spectrometry (UPLC-MS/MS) method was optimized for the simultaneous quantification of the assay, and these impurities in MOPR drug substance and formulation dosage form. The multiple reaction monitoring (MRM) technique was utilized for the quantification. Prior to the validation study, the UPLC-MS method conditions were optimised using fractional factorial design (FrFD). The optimized Critical Method Parameters (CMPs) include the percentage of Acetonitrile in MP B, Concentration of Formic acid in MP A, Cone Voltage, Capillary Voltage, Collision gas flow and Desolvation temperature were determined from the numerical optimization to be 12.50 %, 0.13 %, 13.6 V, 2.6 kV, 850 L/hr and 375 °C, respectively. The optimized chromatographic separation achieved on Waters Acquity HSS T3 C18 column (100 mm × 2.1 mm, 1.8 µm) in a gradient elution mode with 0.13% formic acid in water and acetonitrile as mobile phases, column temperature kept at 35 °C and flow rate at 0.5 mL/min. The method was successfully validated as per ICH guidelines, and demonstrated excellent linearity over the concentration range of 0.5-10 ppm for both PGTIs. The Pearson correlation coefficient of each impurity and MOPR was found to be higher than 0.999, and the recoveries were in between the range of 94.62 to 104.05% for both PGTIs and 99.10 to 100.25% for MOPR. It is also feasible to utilise this rapid method to quantify MOPR accurately in biological samples.

Effects of Behavioral Intervention Components for African American/Black and Latino Persons Living with HIV with Non-suppressed Viral Load Levels: Results of an Optimization Trial.

There is an urgent need for efficient behavioral interventions to increase rates of HIV viral suppression for populations with serious barriers to engagement along the HIV care continuum. We carried out an optimization trial to test the effects of five behavioral intervention components designed to address barriers to HIV care continuum engagement for African American/Black and Latino persons living with HIV (PLWH) with non-suppressed HIV viral load levels: motivational interviewing sessions (MI), focused support groups (SG), peer mentorship (PM), pre-adherence skill building (SB), and navigation with two levels, short (NS) and long (NL). The primary outcome was HIV viral suppression (VS) and absolute viral load (VL) and health-related quality of life were secondary outcomes. Participants were 512 African American/Black and Latino PLWH poorly engaged in HIV care and with detectable HIV viral load levels in New York City, recruited mainly through peer referral. Overall, VS increased to 37%, or 45% in a sensitivity analysis. MI and SG seemed to have antagonistic effects on VS (z = - 1.90; p = 0.057); the probability of VS was highest when either MI or SG was assigned, but not both. MI (Mean Difference = 0.030; 95% CI 0.007-0.053; t(440) = 2.60; p = 0.010) and SB (Mean Difference = 0.030; 95% CI 0.007-0.053; t(439) = 2.54; p = 0.012) improved health-related quality of life. This is the first optimization trial in the field of HIV treatment. The study yields a number of insights into approaches to improve HIV viral suppression in PLWH with serious barriers to engagement along the HIV care continuum, including chronic poverty, and underscores challenges inherent in doing so.

Field measures of strengthen plant-microbial remediation of PAHs-FQs compound pollution.

In this study, five PAHs (benzo [b] fluoranthene (BbF), phenanthrene (Phe), fluoranthene (Flu), fluorene (Fl), benzo [A] pyrene (Bap)), and five FQs (ofloxacin (OFL), enrofloxacin (ENR), ciprofloxacin (CIP), norfloxacin (NOR), lomefloxacin (LOM)) were selected as ligands; peroxidase (1NML) was selected as receptor degrading protein. In the plant-microbial degradation, the factors with significant inhibitory effects are NOR, Bap, CIP, ENR, OFL, Flu, LOM, Phe, Fl, and BbF by the fractional factorial design experiment and molecular docking-assisted molecular dynamics methods. Using Taguchi experiment and molecular dynamics simulation methods, the main external field measures were designed and screened to effectively promote the degradation of PAHs-FQs under the combined pollution scenarios of Bap-CIP and BbF-NOR, respectively. The peroxidase mutation design plans with enhanced substrate affinity were then designed and screened using the DS software by predicting the virtual key amino acid of peroxidase. The novel biodegradable enzymes 2YCD-1, 2YCD-4, 2YCD-5, 2YCD-7, and 2YCD-9 had better structures and showed excellent degradability for PAHs and FQs. This study explored the degradation rules of the composite pollutants in the coexistence systems of multiple PAHs and FQs, providing the best external field measures for the control and treatment of the combined pollution effects of different PAHs and FQs. Overall, the current study has important practical significance for promoting the plant-microbial joint remediation of PAHs-FQs pollution and for reducing the combined pollution of PAHs and FQs in farmland systems.

Quality by design-based capillary electrophoresis method development for the quantitative analysis of four iridoid compounds in Gentiana macrophylla Radix.

In this study, the capillary electrophoresis-photodiode array detector was employed for the analysis of four iridoid compounds in Gentiana macrophylla Radix (RGM), and the method was optimized based on the concept of analytical quality by design (AQbD). The peak areas relative standard deviation (n = 3) and resolution of the four analytes were selected as critical method attributes. Fractional factorial design test combined with Pareto analysis were employed to screen critical method parameters (buffer concentration, pH, sodium dodecyl sulfate [SDS] micelle concentration, temperature, and voltage). Subsequently, three main factors (buffer concentration, buffer pH, and SDS concentration) were selected by central composite design test for constructing the design space. The optimal separation conditions as follows: capillary column (50.2 cm × 50 µm, detection length 40 cm). Working background electrolyte consisted of 51 mmol/L borax solution (pH = 9.47) and 40 mmol/L SDS. The samples were injected by pressure (5 s at 0.5 psi) and the detection was performed at 254 nm. Applied voltage was 20 kV and column temperature was 23°C. The developed method is rapid and reliable for the quantitative analysis of four iridoid compounds in RGM, providing a reference for the application of AQbD concept in the analysis of natural products.

Evaluation of nanoplastics toxicity to the human placenta in systems.

Following the discovery of plastics in the human placenta, this study evaluated the toxicity of ten different nanoplastics (NPs) in the human placenta. Since the placenta performs metabolic and excretion functions by the enzymatic system, the NPs were docked on these human enzymes including soluble epoxide hydrolase, uracil phosphoribosyltransferase, beta 1,3-glucuronyltransferase I, sulfotransferase, N-acetyltransferase 2, and cytochrome P450 1A1at their active sites with toxicity (binding affinity) determined and compared to control compounds. Density functional theory analysis were conducted on the NPs to identify their global reactivity descriptors and Artificial Neural Networks to predict toxicity based on reactivity descriptors. Polycarbonate (PC), polyethylene terephthalate (PET) and polystyrene (PS) showed the highest toxicity to all enzymes and thus the most toxic polymers due to the presence of an electron-withdrawing group in their aromatic rings, which demonstrated an improved recognition of the enzyme active site by pi- and alkyl interactions. A 210-6 fractional factorial design approach was used in conjunction with a fixed effects model to assess the primary and secondary effects of NPs in a composite system on binding affinity to the placental enzymes. The simulation results suggest that NPs mixture may pose significant risks to the placenta through inhibition of its key enzymes.

Effect of metals on mesophilic anaerobic digestion of strawberry extrudate in batch mode.

According to recent studies, the anaerobic digestion of strawberry extrudate is a promising option with potential in the berry industry biorefinery. However, the lack and/or unbalance of concentrations of metals in some agro-industrial residues could hamper methane production during the anaerobic digestion of these kinds of wastes. In this study, a fractional factorial design was applied to screen the supplementation requirements regarding six metals (Co, Ni, Fe, Cu, Mn, and Zn) for methane production from strawberry extrudate (SE). The logistic model was used to fit the experimental data of methane production-time. It allowed identifying two different stages in the anaerobic process and obtaining the kinetic parameters for each step. Maximum methane production obtained in the first (Bmax) kinetic stage, the methane production in the second stage (P), and the maximum methane production rates (Rmax) concluded a statistically significant effect for Ni and Zn. The second set of experiments was carried out with Ni and Zn through a central composite design to study the concentration effect in the anaerobic digestion process of the strawberry extrudate. The parameters P and Rmax demonstrated a positive interaction between Ni and Zn. Although, Bmax did not prove a statistically significant effect between Ni and Zn.

Toxicity evaluation of microplastics to aquatic organisms through molecular simulations and fractional factorial designs.

Molecular docking, molecular dynamics modelling, and fractional factorial design methodologies were used in the current work to examine the harmful effects of ten microplastic (MPs) such as polystyrene (PS), polyvinylchloride (PVC), polyurethane (PU), polymethyl methacrylate (PMMA), polyamide (PA), polyethylene terephthalate (PET), polyethylene (PE), polypropylene (PP), polychloropene (PCP) and polycarbonate (PC) on the aquatic organism (zebrafish). The toxicity was evaluated based on the docking of the MPs on cytochrome P450 (CYP P450) protein crystals. The binding affinities (ΔG) followed the order, PC (-6.9 kcal/mol) > PET (-6.1 kcal/mol) > PP (-5.8 kcal/mol) > PA (-5.6 kcal/mol) > PS (-5.1 kcal/mol) > PU (-4.1 kcal/mol) > PMMA (-3.9 kcal/mol) > PCP (-3.3 kcal/mol) > PVC (-2.4 kcal/mol) > PE (-2.1 kcal/mol). The primary driving factors for the binding of the MPs and the protein were hydrophobic force, and hydrogen bonding based on the molecular dynamics analysis and surrounding amino acid residues. Furthermore, a 210-5 fractional factorial design method was estimated to identify the main effect and second-order effects of MPs in a composite contamination system on binding affinity/energy to CYP450 receptor protein of zebrafish, combined with a fixed effects model. The findings showed that different MPs combinations had varying impacts on aquatic toxicity; as a consequence, the best combination of MPs with the lowest aquatic toxicity effect could be excluded. The factorial designs showed that the PU-PS and PP-PA combination and single PCP, has the most significant main effect on CYP450 receptor protein of zebrafish which translates to an optimum toxicity level of -4.61 kcal/mol. The investigation offers a theoretical foundation for identifying the hazardous impacts of MPs on aquatic life.

Production and Characterization of Rhamnolipids Produced by Pseudomonas aeruginosa DBM 3774: Response Surface Methodology Approach.

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.

Transparent Quality Optimization for Machine Learning-Based Regression in Neurology.

The clinical monitoring of walking generates enormous amounts of data that contain extremely valuable information. Therefore, machine learning (ML) has rapidly entered the research arena to analyze and make predictions from large heterogeneous datasets. Such data-driven ML-based applications for various domains become increasingly applicable, and thus their software qualities are taken into focus. This work provides a proof of concept for applying state-of-the-art ML technology to predict the distance travelled of the 2-min walk test, an important neurological measurement which is an indicator of walking endurance. A transparent lean approach was emphasized to optimize the results in an explainable way and simultaneously meet the specified software requirements for a generic approach. It is a general-purpose strategy as a fractional−factorial design benchmark combined with standardized quality metrics based on a minimal technology build and a resulting optimized software prototype. Based on 400 training and 100 validation data, the achieved prediction yielded a relative error of 6.1% distributed over multiple experiments with an optimized configuration. The Adadelta algorithm (LR=0.000814, fModelSpread=5, nModelDepth=6, nepoch=1000) performed as the best model, with 90% of the predictions with an absolute error of <15 m. Factors such as gender, age, disease duration, or use of walking aids showed no effect on the relative error. For multiple sclerosis patients with high walking impairment (EDSS Ambulation Score ≥6), the relative difference was significant (n=30; 24.0%; p<0.050). The results show that it is possible to create a transparently working ML prototype for a given medical use case while meeting certain software qualities.

Synchronizing the release rates of topotecan and paclitaxel from a self-eroding crosslinked chitosan - PLGA platform.

This study is a continuation of a previous study in which two model drugs, sodium salicylate (highly water-soluble) and indomethacin (low water-soluble) were loaded into an erodible hydrogel, made of ionically crosslinked chitosan (x-Ct). The erosion rate of the x-Ct matrix was controlled by its immersion in calcium chloride solutions (de-crosslinker) of different concentrations, leading to synchronization of the release rates of the two drugs over 2 h. In the present study, a modified platform was developed in order to (a) synchronize the release rates of the two cytotoxic drugs, topotecan (TT, highly water soluble) and paclitaxel (PTX, poorly water soluble); (b) prolong the erosion duration and the derived concomitant release of the two drugs to several days. TT was loaded into a PLGA sphere, which was co-loaded with calcium chloride (CaCl2). The sphere was then placed in an aqueous solution of chitosan (Ct) in which PTX was dispersed. A PLGA core-containing hydrogel was then produced by ionically crosslinking the Ct. The formulation screening section of the study includes a statistically designed Fractional Factorial experiment. It was comprised of the following five experimental factors: (a) the type of Ct and (b) its relative amount in the formulation, (c) the type of ionic crosslinker (citric acid or oxalic acid), (d) the concentration of the ionic crosslinker and (e) the co-loaded amounts of CaCl2 (the constitutional de-crosslinking agent). The difference factor, f1, and the similarity factor, f2, of the TT and PTX release profiles into water, were used as the experimental responses. The computerized prediction models were employed to assess the collective effects of the pre-determined experimental factors on the difference factor, f1, and the similarity factor, f2 (the response factors), by employing a fractional factorial design and multifactorial analysis, without the need to account for the exact mechanisms of the release processes involved. The final composite platform was capable of releasing TT and PTX, at similar (concomitant) rates, over a period of 7 days, a finding which suggests that the novel polymeric platform may serve as a multi-drug implant. An attractive medical application for such a device would be post-operative local treatment that could benefit from localized combination chemotherapy after the removal of malignant tissues, in the surgical treatment of breast cancer, ovarian cancer, glioma and peritoneal carcinomatosis.

Enhanced keratinase production by Bacillus subtilis amr using experimental optimization tools to obtain feather protein lysate for industrial applications.

The poultry industry produces millions of tons of feathers waste that can be transformed into valuable products through bioprocess. The study describes the enhanced keratinase and feather hydrolysate production by Bacillus subtilis AMR. The metabolism of each microorganism is unique, so optimization tools are essential to determine the best fermentation parameters to obtain the best process performance. The evaluation of different propagation media indicated the constitutive production of two keratinases of approximately 80 kDa. The combination of Mn2+, Ca2+, and Mg2+ at 0.5 mM improved the keratinolytic activity and feather degradation 1.5-fold, while Cu2+ inhibited the enzymatic activity completely. Replace yeast extract for sucrose increased the feather hydrolysate production three times. The best feather concentration for hydrolysate production was 1.5% with an inoculum of 108 CFU/mL and incubation at 30 °C. None of the inorganic additional nitrogen sources tested increased hydrolysate production, although (NH4)2SO4 and KNO3 improved enzymatic activity. The optimization process improved keratinolytic activity from 205.4 to 418.7 U/mL, the protein concentration reached 10.1 mg/mL from an initial concentration of 3.9 mg/mL, and the feather degradation improved from 70 to 96%. This study characterized keratinase and feather hydrolysate production conditions offering valuable information for exploring and utilizing AMR keratinolytic strain for feather valorization. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-022-03153-y.

Surface Quality Optimization in Micromachining with Cutting Tool Having Regular Constructive Geometry.

In this paper we studied the influence of micromachining parameters on processed surface quality. Usually in discussions about micro-cutting or micromachining, the grinding or diamond turning processes are considered. Cutting tools used in the mentioned processes do not have regular constructive geometry and, in this case, it is difficult to use constructive geometric parameters such as clearance angle α or rake angle γ to optimize the quality of the machined surface. In order to determine the influence of the cutting tool's constructive geometry on the hardness of the machined material, we used a fractional factorial design of a centered and rotatable type 26-1. A mathematical model based on five independent cutting parameters was created that allowed optimization of surface quality based on obtained roughness. The results can be applied in micromilling or microturning.

Multivariable optimization of activated carbon production from microwave pyrolysis of brewery wastes - Application in the removal of antibiotics from water.

This study aimed at optimizing the one-step chemical activation and microwave pyrolysis of an agro-industrial waste to obtain a microporous activated carbon (AC) with superior textural and adsorptive properties by a fast, low-reagent and low-energy process. Spent brewery grains were used as precursor, and the antibiotics sulfamethoxazole (SMX), trimethoprim (TMP) and ciprofloxacin (CIP) were considered as target adsorbates. A fractional factorial design was applied to evaluate the effect of the main factors affecting the preparation of AC (activating agent, activating agent:precursor ratio, pyrolysis temperature and residence time) on relevant responses. Under optimized conditions (K2CO3 activation, pyrolysis at 800 °C during 20 min and a K2CO3:precursor ratio of 1:2), a microporous AC with specific surface area of 1405 m2 g-1 and large adsorption of target antibiotics (82-94%) was obtained and selected for further studies. Equilibrium times up to 60 min and maximum Langmuir adsorption capacities of 859 µmol g-1 (SMX), 790 µmol g-1 (TMP) and 621 µmol g-1 (CIP) were obtained. The excellent textural and adsorptive properties of the selected material were achieved with a very fast pyrolysis and low load of activating agent, highlighting the importance of optimization studies to decrease the environmental and economic impact of waste-based AC.

Resveratrol Nanocrystal Incorporated into Mesoporous Material: Rational Design and Screening through Quality-by-Design Approach.

Bioflavonoids from grape seeds feature powerful antioxidant and immunostimulant activities, but they present problems related to solubility and bioavailability. Nanocrystal (NC) incorporated into a mesoporous carrier is a promising strategy to address these issues. However, the preparation of this formulation involves the selection of factors affecting its critical quality attributes. Hence, this study aimed to develop an NC formulation incorporating resveratrol into a soluble mesoporous carrier based on rational screening design using a systematic and continuous development process, the quality-by-design paradigm. A mesoporous soluble carrier was prepared by spray-drying mannitol and ammonium carbonate. The NC was obtained by introducing the evaporated solvent containing a drug/polymer/surfactant and mesoporous carrier to the medium. A 26-2 fractional factorial design (FFD) approach was carried out in the screening process to understand the main effect factors. The type and concentration of polymer and surfactant, resveratrol loading, and solvent were determined on the NC characteristics. The results indicated that drug loading, particle size, and solubility were mainly affected by RSV loading, PEG concentration, and Kolliphor EL concentration. The polymer contributed dominantly to reducing the particle size and enhancing solubility in this screening design. The presence of surfactants in this system made it possible to prolong the supersaturation process. According to the 26-2 FFD, the factors selected to be further developed using a statistical technique according to the quality-by design-approach, Box Behnken Design, were Kolliphor EL, PEG400, and RSV loading.

Desirability Function in analytical method development for determination of glitazones and metabolites employing HF-LPME

Abstract Thiazolidinedione, often shortened to TZD or glitazone, helps lower insulin resistance, which is the underlying problem for many people with type 2 diabetes. The two most known glitazones are pioglitazone (PGZ), with the brand name medicine Actos®, and rosiglitazone (RSG), which is Avandia®. This study presented a multivariate optimization in the microextraction procedure employing Fractional Factorial Design (FFD) combined with Desirability Function (DF) to determine TZD and metabolites in biological samples. Microextraction requires several parameters to be optimized; however, most of them still use univariate optimization. Finding optimum conditions by simple response is relatively simple, but the problems, in case of microextractions, are often more complex when it has more responses. For example, changing one factor that promotes one response may suppress the effect of the others. Thus, this multivariate optimization was applied for two bioanalytical methods for determination of TZD and metabolites, one by HPLC and other by CE, both using Hollow Fiber Liquid-Phase Microextraction (HF-LPME). The results establish the optimal values and elucidate how the factors that affect HF-LPME procedure perform in extraction efficiency for TZDs. Additionally, this study demonstrates that DF can be an important tool to optimize microextraction procedures.

3D Printing Optimization for Environmental Sustainability: Experimenting with Materials of Protective Face Shield Frames.

The motivation for research on 3D printing of protective face shields was the urgent societal demand for healthcare in the fight against the spread of COVID19 pandemic. Research is based on a literature review that shows that objects produced by additive technologies do not always have consistent quality suitable for the given purpose of use. Besides, they have different effects on the environment and leave different footprints. The overall goal of the research was to find out the most suitable thermoplastic material for printing shield frames in terms of mechanical properties, geometric accuracy, weight, printing time, filament price, and environmental sustainability. Fused deposition modeling (FDM) technology was used for 3D printing, and three different filaments were investigated: polylactic acid (PLA), polyethylene terephthalate (PETG), and polyhydroxyalkanoate (PHA). The weighted sum method for multi-objective optimization was used. Finally, PHA material was chosen, mainly due to its environmental sustainability, as it has the most negligible impact on the environment.