Dispersive liquid-liquid microextraction and Monte Carlo simulation of margin of safety for octocrylene, EHMC, 2ES, and homosalate in sunscreens.

Dispersive liquid-liquid microextraction (DLLME) using a floating organic drop has been optimized and used for the sample preparation of four commonly used ultraviolet filter (UVF) substances in sunscreens. Plackett-Burman experimental design was used to screen 10 variables in DLLME. The most significant variables were then optimized by using a response surface method with a Box-Behnken design. DLLME followed by an optimized HPLC identified octocrylene, 2-ethylhexyl-4-methoxycinnamate, ethylhexyl salicylate, and homosalate as the frequently found UVFs in commercial sunscreens. The systemic exposure dosage and margin of safety (MoS) for the identified UVFs were estimated using in-use concentrations and application patterns. The average systemic exposure dosage values for octocrylene, 2-ethylhexyl-4-methoxycinnamate, ethylhexyl salicylate, and homosalate were 0.52, 0.61, 0.020, and 0.079 mg/kg body weight per day, respectively. Whereas the average MoS values for individual UVFs ranging from 296 to 3160 were all significantly higher than the limit value of 100, the combined exposure risks were slightly above the limit. The probabilistic health risk assessment using Monte Carlo simulation revealed that the combined MoS values were (mean, 10‰, 90‰) 342, 119, and 441, respectively. Regarding the usage of sunscreen cosmetics containing the UVFs studied, these results indicate a safety concern for those who apply multiple UVF products.

Untreated wastewater impact and environmental risk assessment of artificial sweeteners in river water and sediments of the Danube River Basin in Serbia.

Artificial sweeteners are receiving increasing attention as newly recognized emerging contaminants that mainly reach the aquatic environment through the discharge of municipal wastewater containing large amount of these compounds. In this study, the impact of raw untreated wastewater discharges on the levels and the water/sediment distribution of artificial sweeteners in the Danube River and its largest tributaries in Serbia was evaluated, and a comprehensive assessment of environmental risks for freshwater and benthic organisms was performed. Acesulfame and sucralose were detected in all river water samples (100%), while saccharin (59%) and cyclamate (12%) were less frequently found, indicating long-term continuous sewage-derived pollution. Aspartame (100%) and neotame (60%) were the only artificial sweeteners recorded in the sediment samples due to their preference to sorb to particulate matter in the water/sediment system. In terms of ecotoxicological risk, a low risk for aquatic organisms was determined at the detected levels of saccharin in river water, while a high to medium risk was found for benthic biota at the concentrations of neotame and aspartame detected in sediments. The largest contribution to the pollution of the Danube River Basin with artificial sweeteners, and consequently the highest environmental risk, was determined in the two largest cities, the capital Belgrade and Novi Sad, which raises the issue of transboundary pollution.

Predicting liquid chromatography-electrospray ionization/mass spectrometry signal from the structure of model compounds and experimental factors; case study of aripiprazole and its impurities.

A priori estimation of analyte response is crucial for the efficient development of liquid chromatography-electrospray ionization/mass spectrometry (LC-ESI/MS) methods, but remains a demanding task given the lack of knowledge about the factors affecting the experimental outcome. In this research, we address the challenge of discovering the interactive relationship between signal response and structural properties, method parameters and solvent-related descriptors throughout an approach featuring quantitative structure-property relationship (QSPR) and design of experiments (DoE). To systematically investigate the experimental domain within which QSPR prediction should be undertaken, we varied LC and instrumental factors according to the Box-Behnken DoE scheme. Seven compounds, including aripiprazole and its impurities, were subjected to 57 different experimental conditions, resulting in 399 LC-ESI/MS data endpoints. To obtain a more standard distribution of the measured response, the peak areas were log-transformed before modeling. QSPR predictions were made using features selected by Genetic Algorithm (GA) and providing Gradient Boosted Trees (GBT) with training data. Proposed model showed satisfactory performance on test data with a RMSEP of 1.57 % and a of 96.48 %. This is the first QSPR study in LC-ESI/MS that provided a holistic overview of the analyte's response behavior across the experimental and chemical space. Since intramolecular electronic effects and molecular size were given great importance, the GA-GBT model improved the understanding of signal response generation of model compounds. It also highlighted the need to fine-tune the parameters affecting desolvation and droplet charging efficiency.

Adsorption of estrone, 17ß-estradiol, and 17α-ethinylestradiol from water onto modified multi-walled carbon nanotubes, carbon cryogel, and carbonized hydrothermal carbon.

Carbon materials of different structural and textural properties (multi-walled carbon nanotubes, carbon cryogel, and carbonized hydrothermal carbon) were used as adsorbents for the removal of estrone, 17ß-estradiol, and 17α-ethinylestradiol from aqueous solutions. Chemical modification and/or activation were applied to alter surface characteristics and to increase the adsorption and desorption efficiency of carbon materials. Surfaces of treated and untreated carbon materials were characterized through the examination of the textural properties, the nature of surface functional groups, and surface acidity. It was found that the adsorption capacity of tested carbon materials is not directly proportional to the specific surface area and the content of surface oxygen groups. However, a high ratio of surface mesoporosity affected the adsorption process most prominently, by increasing adsorption capacity and the rate of the adsorption process. Adsorption of estrone, 17ß-estradiol, and 17α-ethinylestradiol followed pseudo-second-order kinetic model, while the equilibrium adsorption data were best fitted with the Langmuir isotherm model. Calculated mean adsorption energy values, along with the thermodynamic parameters, indicated that removal of selected hormones was dominated by the physisorption mechanism. High values of adsorption efficiency (88-100 %) and Langmuir adsorption capacities (29.45-194.7 mg/g) imply that examined materials, especially mesoporous carbon cryogel and multi-walled carbon nanotubes, can be used as powerful adsorbents for relatively fast removal of estrogen hormones from water.

Solid-phase extraction of multi-class pharmaceuticals from environmental water samples onto modified multi-walled carbon nanotubes followed by LC-MS/MS.

In this paper, pristine and chemically treated multi-walled carbon nanotubes (MWCNTs) were employed as solid-phase extraction sorbents for the isolation and enrichment of multi-class pharmaceuticals from the surface water and groundwater, prior to liquid chromatography-tandem mass spectrometry analysis. Thirteen pharmaceuticals that belong to different therapeutical classes (erythromycin, azithromycin, sulfamethoxazole, diazepam, lorazepam, carbamazepine, metoprolol, bisoprolol, enalapril, cilazapril, simvastatin, clopidogrel, diclofenac) and two metabolites of metamizole (4-acetylaminoantipyrine and 4-formylaminoantipyrine) were selected for this study. The influence of chemical treatment on MWCNT surface characteristics and extraction efficiency was studied, and it was shown that HCl treatment of MWCNT leads to a decrease in the amount of surface oxygen groups and at the same time favorably affects the efficiency toward extraction of selected pharmaceuticals. After the optimization of the SPE procedure, the following conditions were chosen: 50 mg of HCl-treated MCWNT as a sorbent, 100 mL of water sample at pH 6, and 15 mL of the methanol-dichloromethane mixture (1:1, v/v) as eluent. Under optimal conditions, high recoveries (79-119%), as well as low detection (0.2 to 103 ng L-1) and quantitation (0.5-345 ng L-1) limits, were obtained. The optimized method was applied to the analysis of five surface water and two groundwater samples, and three pharmaceuticals were detected, the antiepileptic drug carbamazepine and two metabolites of antipyretic metamizole.