Do Methodological Differences in Experiments with Stream Shredders Imply Variability in Outputs? A Microcosm Approach

Experiments are useful scientific tools for testing hypotheses by manipulating variables of interest while controlling for other factors that can bias or confuse the results and their interpretation. To ensures accuracy and reproducibility, experiments must have transparent and repeatable methodologies. Due to the importance of shredder invertebrates in organic matter processing, carbon cycling, and nutrient cycling, we tested experimentally the effect of different methodological approaches in microcosm experiments on the consumption and survival of shredders. We found that the shredder species, the presence or absence of the case, and the use or non-use of air-pumps in the microcosms did not affect shredder performance (i.e., consumption and survival). Furthermore, the type of water (stream or bottled) did not affect shredder performance. On the other hand, the amount of light had a negative effect on shredder performance, with constant light (i.e., 24 h) reducing shredder consumption and survival. Our results demonstrate that the use of different methodologies does not always result in changes in outcomes, thus ensuring comparability. However, luminosity is a critical factor that deserves attention when conducting microcosm experiments. Our findings provide valuable insights that can assist researchers in designing experiments with shredders from neotropical streams and conducting systematic reviews and meta-analyses.

Measuring aliphatic hydrocarbons in sediments by direct thermal desorption-gas chromatography-mass spectrometry: Matrix effects and quantification challenges

Direct sample introduction thermal desorption (TD) coupled to GC-MS was investigated for the analysis of paraffinic hydrocarbons (HCs) from polluted sediments. TD-GC-MS is sometimes used for analysing paraffinic HCs from atmospheric particles but rarely for their direct desorption from sediments. So, the new TD methodology, applied to sediments, required development, optimization and validation. A definitive screening experimental design was performed to discriminate the critical factors on TD efficiency, from model sediments containing various organic matter (OM) amounts. Low molecular weight HCs had extraction behaviours markedly different from high molecular ones (HMW-HCs), but a compromise was found using very few sediment amount (5 mg), high temperature rate (55 °C min-1) and final temperature (350 °C). Linear HCs (n-C10 to n-C40) could be quantified using the matrix-matched calibration method, with very low detection limits (3.8-13.4 ng). The amount of the overall paraffinic alkanes was also determined as a sum of unresolved components between predefined equivalent carbon ranges. The developed solventless methodology was compared to an optimized solvent microwave assisted extraction (MAE). Matrix effects could be higher for TD compared to MAE but it depended on sediment matrix. When matrix effect was strong, particularly on HMW-HCs signal depletion, a dilution with pure non-porous sand was favourable for accurate quantification. The sum of resolved and unresolved HCs gave comparable results between MAE and TD extractions, with an exception of alkanes greater than C30 which were less quantitatively extracted via TD. However, TD-GC-MS was more sensitive than MAE-GC-MS. So TD-GC-MS is useful for analyzing sediments containing a great range of paraffinic HCs (C9-C34) and it has the advantages of being fully automated, with few sample preparation and operator intervention, using very low amounts of solvent, and generating few wastes.

Prediction of the accumulation behavior of pesticides in PDMS-coated stir bars used as passive samplers in freshwaters

Passive samplers accumulate organic contaminants at rates that depend on in-field exposure conditions such as freshwater flow velocity, water temperature and water quality. Time-weighted average concentrations can be determined by using a correction process such as the performance reference compound (PRC) method. This study presented a new approach to predict the accumulation behavior of pesticides in polydimethylsiloxane-coated stir bars under different exposure conditions and assign a specific PRC to each pesticide for quantitative purposes. We used an experimental design with eight simultaneous accumulation kinetics of 13 pesticides and elimination kinetics of three PRC candidates run in a flow-through system to determine the effects of flow velocity, water temperature and dissolved organic matter on the kinetic constants. We identified the parameters that had a significant effect on the accumulation of each pesticide and assigned a PRC candidate to each pesticide. We then used a discriminant function analysis to find the parameters that had a significant effect on accumulation of the 13 pesticides via their physical-chemical properties and to predict through a stochastic approach the parameters for seven other pesticides. This approach provides a better framework for identifying a PRC than conventional methods to determine unbiased concentrations in future monitoring efforts.

Aerated lagoon/adsorption combination method for the treatment of olive mill wastewater: optimizing parameters using study design

The current study focuses on investigating how to improve the efficacy of the combined process of aerated lagooning and adsorption for the treatment of olive mill wastewater (OMWW) from the olive industries in the Loukkos region using the design of experiments approach. The latter made it possible to optimize the experimental conditions, such as the mass concentration of lime, the mass concentration of powdered activated carbon (AC), and the speed of agitation (Va), which are required for the envisaged treatment, in order to control the results after the evaluation of the necessary physicochemical parameters, namely pH, total suspended solids (TSS), chemical oxygen demand (COD), rate of discoloration, and content of polyphenols. The experimental conditions necessary to carry out this study were between 1.4 and 1.75 g/l for AC, between 23 and 32 rpm for the stirring speed, and between 0.88 and 1.3 g/l for the mass concentration of lime. The results of this experiment showed that treating OMWW with the prototype II after adding lime to the mixture resulted in an estimated 85% reduction in the analyzed parameters. The pH, TSS, COD, discoloration rate, and polyphenol content were all reduced from initial values of 4.87, 0.63 (g/l), 80.3 (g (O2/l)), 0.8%, and 1.45 (g/l), respectively, to final values of 6.92, 0.12 (g/l), 12, 0.16%, and 0.25 (g/l). These results are highly significant when compared to those obtained during the treatment of prototype I using only powdered activated carbon, which showed a reduction rate of around 70%.

Combining high intensity ultrasound and experimental design to improve carotenoid extraction efficiency from Buriti (Mauritia flexuosa)

Buriti (Mauritia flexuosa L.) is a significant source of carotenoids, but these compounds have been extracted using laborious and low-effective methods. The present work evaluated the high-intensity ultrasound combined with a chemometric approach to developing an optimal extraction method of carotenoids from buriti pulp. The multivariate optimization was carried out through two steps. First, a simplex-lattice mixture design was used to optimize the extractor solution finding higher extraction yield (903 ± 21 µg g^-1) with the acetone:ethanol (75/25) mixture. After, sample mass (80 mg) and sonication time (30 min) were optimized applying central composite design (CCD) which provided a 14% improvement in the extraction method yield. So, the total carotenoid content (TCC) with optimal extraction conditions was 1026 ± 13 µg g^-1which is almost twice the yield of methods known in the literature for buriti. The RP-HPLC-DAD analysis revealed that the carotenoids are gently extracted and β-carotene is the major compound in the extracts. To confirm the accuracy, buriti samples spiked with β-carotene standard and the developed method showed recovery >84% and precision <6.5%. Furthermore, the optimized ultrasound-assisted extraction (UAE) method was applied to other samples (tomato, guava, carrot, mango, acerola, papaya, and pumpkin) and presented a yield to 5.5-fold higher when compared to the reported methods indicating high robustness. Based on results, the UAE method developed has demonstrated feasibility and reliability for the study of carotenoids in buriti pulp as well as in other plant matrices with high biological relevance.

Direct thermal desorption-gas chromatography-tandem mass spectrometry versus microwave assisted extraction and GC-MS for the simultaneous analysis of polyaromatic hydrocarbons (PAHs, PCBs) from sediments

Polycyclic aromatic hydrocarbons (PAHs) and polychlorinated biphenyls (PCBs) are regulated contaminants usually investigated in sediments. Conventional approaches often use GC-MS to analyse them with a preliminary extraction step which can be solvent- and time-consuming. Here two extraction methodologies were optimized using experimental designs, and compared: microwave assisted extraction (MAE) and thermal desorption (TD); the latter was rarely used for sediments analyses. Several factors that may influence extraction recoveries were studied including matrix parameters (mass, organic matter (OM) content) and processing parameters. A definitive screening design DSD was performed to screen the 6 most influencing factors and model the extraction recoveries using TD. Whatever the OM content, a minimum sediment mass (5 mg) was better for an optimal extraction, with a minimum temperature rate (15 °C min^-1), a maximum final temperature (350 °C) associated with a minimum hold time (5 min), and a maximum vent flow (150 mL min^-1) between the TD unit and the cryogenic trap. Thereafter matrix effects were evaluated using standard addition, and quality assurance and control were implemented for comparing MAE and TD. TD-GC-MS/MS sensitivity was higher than MAE-GC-MS with detection limits in the range 5-1160 pg and 20-125 pg for PAHs and PCBs, respectively. When considering the appropriate strategy for quantification, TD was also reliable for sediments analysis. Although MAE was less sensitive to matrix effects, TD could significantly improve the analytical process, due to direct coupling with GC-MS/MS and complete automation. Moreover, TD offered possible higher spatial resolution than MAE, particularly for sediment cores analysis, due to the 1000-times lower sample size. At last, TD-GC-MS/MS appeared as a greener analytical procedure.

Testing experimental designs in liquid chromatography (II): Influence of the design geometry on the prediction performance of retention models

In liquid chromatography, the reliability of predictions carried out with retention models depends critically on the quality of the training experimental design. The search of the best design is more complex when gradient runs are used instead of isocratic experiments. In Part I of this work (JCA 1624 (2020) 461180), a general methodology based on the error propagation theory was developed and validated for assessing the quality of training designs involving gradients. The treatment relates the mathematical properties of a retention model with the geometry of the training designs and their subsequent predictions. In that work, only five usual designs were considered. Part II investigates in detail the effects on predictions when the features of the training design (number and distribution of the experiments, initial and final modifier content, gradient slope(s), and location of gradient nodes and pulses) are varied systematically. Several groups of related designs containing one or more isocratic steps, linear or multi-linear gradients, or mixed isocratic/gradient runs, among others (in total 38 designs) were evaluated. Box and whiskers and triple plots of expected relative uncertainties were used to evidence the differences in prediction performance. The purpose was to give recommendations to construct designs with good prediction performance. The best designs sample (considering all runs) concentrations as diverse as possible, at any gradient time.

Effectiveness of different alpha lattice designs in the evaluation of maize (Zea mays L.) genotypes in a rainforest agro-ecology

Plant breeding experiments require the use of appropriate experimental designs that will efficiently block variation due to wide heterogeneity nature of tropical soils. The primary objective of this study was to assess the effectiveness of eight different alpha-lattice designs relative to randomized complete block design for evaluating 108 genotypes of maize under rainforest agro-ecology. The maize genotypes were field-tested using three replications at two locations. Data were collected on grain yield and other agronomic traits. Data collected were subjected to analysis of variance (ANOVA) assuming randomized complete block design (RCBD) and eight alpha-lattice designs. Pearson's correlation and stepwise multiple regression analyses were used to analyze relationship among different designs and efficiency of the lattice designs over RCBD was computed. Result showed that all the alpha lattice designs except 27 × 4 were effective in evaluating the genotypes for plant height. There was significant difference (p < 0.001) among genotypes for grain yield only when data were analyzed based on 9 × 12 alpha lattice design. In addition, results showed that the proportion of variation due to blocking and R-square values of the model increased with increase in the number of blocks for grain yield. In contrast, coefficient of variation decreased with increase in the number of blocks. The result showed an increase in efficiency of the alpha lattice designs as the number of blocks increased. It could then be concluded that the more the number of blocks within replicate, the proportion of total variation due to blocking increased, the coefficient of variation (CV) reduced, coefficient of determination (R-square) increased and thus, effectiveness increased. Appropriateness of designs was trait dependent. The 9 × 12 alpha lattice design was identified to be the best in the evaluation of grain yield for the maize genotypes.

Systematic development of lectin conjugated microspheres for nose-to-brain delivery of rivastigmine for the treatment of Alzheimer's disease

The current study focuses on development of nasal mucoadhesive microspheres for nose-to-brain delivery of rivastigmine for Alzheimer treatment. A systematic development was employed for optimization of the formulation and process parameters influential on the quality attributes of the microspheres. The risk assessment study revealed major influence of the polymer concentration (ethylcellulose: chitosan), the concentration of surfactant solution (polyvinyl alcohol), and stirring speed as the critical factors for optimization of the microspheres. These factors were systematically optimized using Box-Behnken design and microspheres were evaluated for the particle size, entrapment efficiency, and in vitro drug release as the response variables. The optimized microspheres containing 4.4% wt/vol polymers, 1% wt/vol surfactant, and stirring speed at 1500 rpm showed particle size of 19.9 µm, entrapment efficiency of 77.8%, and drug release parameters as T_80% of 7.3 h. The surface modification of microspheres was performed with lectin by carbodiimide activation reaction and confirmed by difference in surface charge before and after chemical functionalization by zeta potential measurement which was found to be - 25.7 mV and 20.5 mV, respectively. Ex vivo study for bioadhesion strength evaluation on goat nasal mucosa indicated a significant difference (p < 0.001) between the plain (29%) and lectin functionalized microspheres (64%). In vivo behavioral and biochemical studies in the rats treated with lectin functionalized microspheres showed markedly better memory-retention vis-à-vis test and pure drug solution treated rats (p < 0.001). In a nutshell, the present studies showed successful development of nasal microspheres for enhanced brain delivery of rivastigmine for Alzheimer's treatment.

Paclitaxel and naringenin-loaded solid lipid nanoparticles surface modified with cyclic peptides with improved tumor targeting ability in glioblastoma multiforme

The present work describes the systematic development of paclitaxel and naringenin-loaded solid lipid nanoparticles (SLNs) for the treatment of glioblastoma multiforme (GBM). So far only temozolomide therapy is available for the GBM treatment, which fails by large amount due to poor brain permeability of the drug and recurrent metastasis of the tumor. Thus, we investigated the drug combination containing paclitaxel and naringenin for the treatment of GBM, as these drugs have individually demonstrated significant potential for the management of a wide variety of carcinoma. A systematic product development approach was adopted where risk assessment was performed for evaluating the impact of various formulation and process parameters on the quality attributes of the SLNs. I-optimal response surface design was employed for optimization of the dual drug-loaded SLNs prepared by micro-emulsification method, where Percirol ATO5 and Dynasan 114 were used as the solid lipid and surfactant, while Lutrol F188 was used as the stabilizer. Drug loaded-SLNs were subjected to detailed in vitro and in vivo characterization studies. Cyclic RGD peptide sequence (Arg-Gly-Asp) was added to the formulation to obtain the surface modified SLNs which were also evaluated for the particle size and surface charge. The optimized drug-loaded SLNs exhibited particle size and surface charge of 129 nm and 23 mV, drug entrapment efficiency >80% and drug loading efficiency >7%. In vitro drug release study carried out by micro dialysis bag method indicated more than 70% drug was release observed within 8 h time period. In vivo pharmacokinetic evaluation showed significant improvement (p < 0.05) in drug absorption parameters (C_max and AUC) from the optimized SLNs over the free drug suspension. Cytotoxicity evaluation on U87MG glioma cells indicated SLNs with higher cytotoxicity as compared to that of the free drug suspension (p < 0.05). Evaluation of uptake by florescence measurement indicated superior uptake of SLNs tagged with dye over the plain dye solution. Overall, the dual drug-loaded SLNs showed better chemoprotective effect over the plain drug solution, thus construed superior anticancer activity of the developed nanoformulation in the management of glioblastoma multiforme.

Systematic development of a bioanalytical UPLC-MS/MS method for estimation of risperidone and its active metabolite in long-acting microsphere formulation in rat plasma

A systematic approach to develop a UPLC-MS/MS method was applied for quantifying of risperidone (RISP), its active metabolite, 9-hydroxy risperidone (9-OH-RISP) and internal standard (propranolol) in rat plasma. Liquid-liquid extraction was performed using methyl tert-butyl ether for quantification of drug and its active metabolite by MS detection in the positive ion mode. Acquity UPLC system with BEH C18 (2.1 mm × 100 mm, particle size 1.7 μm) column was used along with acetonitrile (0.1% formic acid)-2 mM (milli mole) ammonium acetate in isocratic condition was used as the mobile phase. Detection was performed by multiple reactions monitoring with precursor-to-product ion transitions with m/z 411.2 → 191.0 for RISP, m/z 427.2 → 207.0 for 9-OH-RISP and m/z 260.1 → 116.0 for IS. The method was validated as per the FDA guidance on bioanalytical method validation. Linearity (r² = 0.999) was observed in the drug concentration ranging between 0.1 and 50 ng mL^-1, while all other parameters were found to be within the acceptable ranges. Method robustness was optimized by Box-Behnken design to monitor the influential variables to achieve maximal recovery of the analytes in the rat plasma. Pharmacokinetic evaluation of the analytes from long-acting microparticles in rat plasma showed two peaks indicating an initial burst effect within 24 h of administration followed by controlled drug release pattern upto 45 days, while marketed formulation (Risperdal Consta®) showed no plasma concentration during the lag-time of 21 days followed by maximal drug absorption between 28 and 40 days.

Ultrasound assisted maceration for improving the aromatization of extra-virgin olive oil with rosemary and basil

Aromatization of extra-virgin olive oil (EVOO) with aromatic plants is commonly used to enrich the oil with aromatic and antioxidant compounds. Ultrasound can be an alternative to accelerate this process. The objective of this work was to determine if ultrasound is able to accelerate EVOO aromatization with rosemary and basil and how it affects the migration of volatile and other compounds, the oxidative stability and the antioxidant capacity of the aromatized products. Ultrasound parameters (amplitude, time, and temperature of extraction) were optimized for each herb with central composite designs. Free fatty acid, peroxide value, K₂₃₂, K₂₇₀, ΔK, fatty acid profile, total phenolics, antioxidant capacity, polar compounds, oxidative stability and volatile compounds profile were evaluated in all samples. Physical effects of ultrasound on the herbs were observed by scanning electron microscopy. In the optimization, variables related to the oxidative processes were minimized and compounds migration and oxidative stability were maximized. Results were 70.09% amplitude, 36.6 min and 35 °C for rosemary and 95.98% amplitude, 9.9 min and 30 °C for basil. These conditions were compared to 7 and 15 days of conventional maceration (CM). Aromatization of EVOO with rosemary, both by ultrasound assisted maceration (UAM) or CM, improved total phenolics, terpenes, esters, ketones, stability and induction times, as well as decreased the values for the quality parameters. The use of UAM accelerated the process to 37 min. However, aromatization with basil by CM increased the values for the quality parameters and reduced the total phenolics, the antioxidant capacity and the induction and stability times. UAM with basil reached better results than those observed for CM, in only 10 min. In conclusion, rosemary is more appropriate than basil for EVOO aromatization, and UAM was the best choice to accelerate the processes when compared to CM.

Benefits of solvent concentration pulses in retention time modelling of liquid chromatography

The advantages and disadvantages of the use of isocratic experimental designs including transient increments of organic solvent (i.e., pulses) in the mobile phase(s) of lowest elution strength are explored with modelling purposes. For retained solutes, this type of mixed design offers similar or better predictive capability than gradient designs, shorter measurement time than pure isocratic designs, and retention model parameters that agree with those derived from pure isocratic experiments, with similar uncertainties. The predicted retention times are comparable to those offered by models adjusted from pure isocratic designs, and the solvent waste is appreciably lower. Under a practical standpoint, mixed designs including pulse(s) can be easily constructed by replacing the slowest isocratic runs with runs containing a pulse of short duration at an intermediate time. This allows the elution of the fastest solutes with appreciable retention in the initial sector of the elution program, previous to the pulse, and the elution of the slow solutes after the pulse, also in acceptable times. The fitting of the retention data obtained with pulses is simpler compared to gradient elution, and involves solving the integral equation of gradient elution, simplified by the presence of isocratic sectors. Experiments involving pulses reveal the existence of discrepancies in the predictions for solutes eluting in the nearby of the pulse, offered by the fundamental equation of gradient elution when this is solved using numerical integration. The correction of such discrepancies implies the inclusion of intra-column delays, in the arrival of changes in the concentration of organic modifier in the gradient to the instantaneous position of the solute, along the whole migration.

An overview of the impact of rare disease characteristics on research methodology

Background

About 30 million individuals in the United States are living with a rare disease, which by definition have a prevalence of 200,000 or fewer cases in the United States ([National Organization for Rare Disorders], [About NORD], [2016]). Disease heterogeneity and geographic dispersion add to the difficulty of completing robust studies in small populations. Improving the ability to conduct research on rare diseases would have a significant impact on population health. The purpose of this paper is to raise awareness of methodological approaches that can address the challenges to conducting robust research on rare diseases.

Approach

We conducted a landscape review of available methodological and analytic approaches to address the challenges of rare disease research. Our objectives were to: 1. identify algorithms for matching study design to rare disease attributes and the methodological approaches applicable to these algorithms; 2. draw inferences on how research communities and infrastructure can contribute to the efficiency of research on rare diseases; and 3. to describe methodological approaches in the rare disease portfolio of the Patient-Centered Outcomes Research Institute (PCORI), a funder promoting both rare disease research and research infrastructure.

Results

We identified three algorithms for matching study design to rare disease or intervention characteristics (Gagne, et.al, BMJ 349:g6802, 2014); (Gupta, et.al, J Clin Epidemiol 64:1085-1094, 2011); (Cornu, et. al, Orphet J Rare Dis 8:48,2012) and summarized the applicable methodological and analytic approaches. From this literature we were also able to draw inferences on how an effective research infrastructure can set an agenda, prioritize studies, accelerate accrual, catalyze patient engagement and terminate poorly performing studies. Of the 24 rare disease projects in the PCORI portfolio, 11 are randomized controlled trials (RCTs) using standard designs. Thirteen are observational studies using case-control, prospective cohort, or natural history designs. PCORI has supported the development of 9 Patient-Powered Research Networks (PPRNs) focused on rare diseases.

Conclusion

Matching research design to attributes of rare diseases and interventions can facilitate the completion of RCTs that are adequately powered. An effective research infrastructure can improve efficiency and avoid waste in rare disease research. Our review of the PCORI research portfolio demonstrates that it is feasible to conduct RCTs in rare disease. However, most of these studies are using standard RCT designs. This suggests that use of a broader array of methodological approaches to RCTs --such as adaptive trials, cross-over trials, and early escape designs can improve the productivity of robust research in rare diseases.

Design of experiments in medical physics: Application to the AAA beam model validation

PURPOSE

The purpose of this study is to evaluate the usefulness of the design of experiments in the analysis of multiparametric problems related to the quality assurance in radiotherapy. The main motivation is to use this statistical method to optimize the quality assurance processes in the validation of beam models.

METHOD

Considering the Varian Eclipse system, eight parameters with several levels were selected: energy, MLC, depth, X, Y₁ and Y₂ jaw dimensions, wedge and wedge jaw. A Taguchi table was used to define 72 validation tests. Measurements were conducted in water using a CC04 on a TrueBeam STx, a TrueBeam Tx, a Trilogy and a 2300IX accelerator matched by the vendor. Dose was computed using the AAA algorithm. The same raw data was used for all accelerators during the beam modelling.

RESULTS

The mean difference between computed and measured doses was 0.1±0.5% for all beams and all accelerators with a maximum difference of 2.4% (under the 3% tolerance level). For all beams, the measured doses were within 0.6% for all accelerators. The energy was found to be an influencing parameter but the deviations observed were smaller than 1% and not considered clinically significant.

CONCLUSION

Designs of experiment can help define the optimal measurement set to validate a beam model. The proposed method can be used to identify the prognostic factors of dose accuracy. The beam models were validated for the 4 accelerators which were found dosimetrically equivalent even though the accelerator characteristics differ.

Causal inferences on the effectiveness of complex social programs: Navigating assumptions, sources of complexity and evaluation design challenges

This paper explores avenues for navigating evaluation design challenges posed by complex social programs (CSPs) and their environments when conducting studies that call for generalizable, causal inferences on the intervention's effectiveness. A definition is provided of a CSP drawing on examples from different fields, and an evaluation case is analyzed in depth to derive seven (7) major sources of complexity that typify CSPs, threatening assumptions of textbook-recommended experimental designs for performing impact evaluations. Theoretically-supported, alternative methodological strategies are discussed to navigate assumptions and counter the design challenges posed by the complex configurations and ecology of CSPs. Specific recommendations include: sequential refinement of the evaluation design through systems thinking, systems-informed logic modeling; and use of extended term, mixed methods (ETMM) approaches with exploratory and confirmatory phases of the evaluation. In the proposed approach, logic models are refined through direct induction and interactions with stakeholders. To better guide assumption evaluation, question-framing, and selection of appropriate methodological strategies, a multiphase evaluation design is recommended.

Removal of Mefenamic acid from aqueous solutions by oxidative process: Optimization through experimental design and HPLC/UV analysis

Mefenamic acid (MEF) is a non-steroidal anti-inflammatory drug indicated for relief of mild to moderate pain, and for the treatment of primary dysmenorrhea. The presence of MEF in raw and sewage waters has been detected worldwide at concentrations exceeding the predicted no-effect concentration. In this study, using experimental designs, different oxidative processes (H2O2, H2O2/UV, fenton and Photo-fenton) were simultaneously evaluated for MEF degradation efficiency. The influence and interaction effects of the most important variables in the oxidative process (concentration and addition mode of hydrogen peroxide, concentration and type of catalyst, pH, reaction period and presence/absence of light) were investigated. The parameters were determined based on the maximum efficiency to save time and minimize the consumption of reagents. According to the results, the photo-Fenton process is the best procedure to remove the drug from water. A reaction mixture containing 1.005 mmol L(-1) of ferrioxalate and 17.5 mmol L(-1) of hydrogen peroxide, added at the initial reaction period, pH of 6.1 and 60 min of degradation indicated the most efficient degradation, promoting 95% of MEF removal. The development and validation of a rapid and efficient qualitative and quantitative HPLC/UV methodology for detecting this pollutant in aqueous solution is also reported. The method can be applied in water quality control that is generated and/or treated in municipal or industrial wastewater treatment plants.

Preparation, characterization and optimization of glipizide controlled release nanoparticles

The purpose of the present study was to develop glipizide controlled release nanoparticles using alginate and chitosan thorough ionotropic controlled gelation method. Glipizide is a frequently prescribed second generation sulfonylurea which lowers the blood glucose in type-two diabetics. Quick absorption of the drug from the gastrointestinal tract along with short half- life of elimination makes it a good candidate for controlled release formulations. Alginate-chitosan nanoparticles (ACNP) are convenient controlled delivery systems for glipizide, due to both the release limiting properties of the system, and the bioadhesive nature of the polymers. In the present study, glipizide loaded alginate-chitosan nanoparticles (GlACNP) were prepared, and the particle characteristics including particle size (PS), zeta potential (ZP), entrapment efficiency (EE%), loading percent (LP), and mean release time (MRT), as well as the morphology of the nanoparticles, the drug-excipient compatibility, and the release kinetics along with the drug diffusion mechanism were evaluated. The results suggested that ionotropic controlled gelation method offers the possibility of preparing the nanoparticles in mild conditions in an aqueous environment, and can lead to the preparation of particles with favorable size, controlled release characteristics, and high entrapment efficiency, serving as a convenient delivery system for glipizide. The particle and release characteristics can be efficiently optimized using the Box-Behnken design. Based on the findings of the present study, it is expected that this novel formulation be a superior therapeutic alternative to the currently available glipizide delivery systems.