Binary Solvents Dispersive Liquid-Liquid Microextraction (BS-DLLME) Method for Determination of Tramadol in Urine Using High-Performance Liquid Chromatography

Optimization and Validation of Dispersive Liquid-Liquid Microextraction for Simultaneous Determination of Aflatoxins B1, B2, G1, and G2 in Senna Leaves and Pods Using HPLC-FLD with Pre-Column Derivatization

Dispersive liquid-liquid microextraction (DLLME) was optimized for the simultaneous extraction of aflatoxins (AFB1, AFB2, AFG1, and AFG2) from powdered senna leaves and pods. Detection was performed using high-performance liquid chromatography with fluorescence detection (HPLC-FLD) and pre-column derivatization. The parameters affecting the DLLME extraction efficiency were evaluated. Chloroform (200 µL) was used as an extraction solvent, 500 µL of distilled water was used as a dispersive solvent, and the extraction was performed at pH 5.6 with no salt added. The optimized method was validated using leaves and pods according to the European Commission guidelines. The linear range for all aflatoxins was 2-50 µg/kg, with values for regression coefficients of determination exceeding 0.995. The recoveries of spiked senna leaves and pods were in the ranges of 91.77-108.71% and 83.50-102.73%, respectively. The RSD values for intra-day and inter-day precisions were in the ranges of 2.30-7.93% and 3.13-10.59%, respectively. The limits of detection and quantification varied in the ranges of 0.70-1.27 µg/kg and 2.13-3.84 µg/kg, respectively. The validated method was successfully applied for the quantification of aflatoxins in 60 real samples of dried senna leaves and pods.

Current development of bioanalytical sample preparation techniques in pharmaceuticals

Sample preparation is considered as the bottleneck step in bioanalysis because each biological matrix has its own unique challenges and complexity. Competent sample preparation to extract the desired analytes and remove redundant components is a crucial step in each bioanalytical approach. The matrix effect is a key hurdle in bioanalytical sample preparation, which has gained extensive consideration. Novel sample preparation techniques have advantages over classical techniques in terms of accuracy, automation, ease of sample preparation, storage, and shipment and have become increasingly popular over the past decade. Our objective is to provide a broad outline of current developments in various bioanalytical sample preparation techniques in chromatographic and spectroscopic examinations. In addition, how these techniques have gained considerable attention over the past decade in bioanalytical research is mentioned with preferred examples. Modern trends in bioanalytical sample preparation techniques, including sorbent-based microextraction techniques, are primarily emphasized.

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Bioanalytical sampling techniques are described with suitable applications in pharmaceuticals.

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The pros and cons of each bioanalytical sampling techniques are described.

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Relevant biological matrices are outlined.

Accurate Quantification of Nervous System Drugs in Aqueous Samples at Trace Levels by Binary Solvent Dispersive Liquid-Liquid Microextraction-Gas Chromatography Mass Spectrometry

Pharmaceutical products are widely consumed globally and are commonly found in wastewaters as a result of constant excretion and disposal into sewers. The present study proposes an efficient binary solvent dispersive liquid-liquid microextraction (BS-DLLME) method that was developed for preconcentration of 7 nervous system drug active compounds from aqueous media for their determination at trace levels by gas chromatography-mass spectrometry. The drug analytes included 3 antidepressants, 2 antipsychotics, 1 antiepileptic, and 1 antidementia. Optimum conditions of the BS-DLLME method were acquired by univariate optimization of parameters including type of binary solvents, ratio of binary solvents, type of disperser solvent, volume of binary solvents, and volume of disperser solvent. Detection and quantification limits were calculated in the range of 0.28 to 6.5 µg/L. Municipal wastewater, medical wastewater, synthetic domestic wastewater, and lake water were utilized as real samples in spike recovery experiments; and the results (94-106%) indicated the method's applicability and accuracy at quantifying the analytes in complex matrices. Environ Toxicol Chem 2021;40:1570-1575. © 2021 SETAC.

Application of Microextraction-Based Techniques for Screening-Controlled Drugs in Forensic Context-A Review

The analysis of controlled drugs in forensic matrices, i.e., urine, blood, plasma, saliva, and hair, is one of the current hot topics in the clinical and toxicological context. The use of microextraction-based approaches has gained considerable notoriety, mainly due to the great simplicity, cost-benefit, and environmental sustainability. For this reason, the application of these innovative techniques has become more relevant than ever in programs for monitoring priority substances such as the main illicit drugs, e.g., opioids, stimulants, cannabinoids, hallucinogens, dissociative drugs, and related compounds. The present contribution aims to make a comprehensive review on the state-of-the art advantages and future trends on the application of microextraction-based techniques for screening-controlled drugs in the forensic context.

Rapid extraction of copper ions in water, tea, milk and apple juice by solvent-terminated dispersive liquid-liquid microextraction using p-sulfonatocalix (4) arene: optimization by artificial neural networks coupled bat inspired algorithm and response surface methodology

A bat inspired algorithm with the aid of artificial neural networks (ANN-BA) has been used for the first time in chemistry and food sciences to optimize solvent-terminated dispersive liquid-liquid microextraction (ST-DLLME) as a green, fast and low cost technique for determination of Cu²⁺ ions in water and food samples using p-sulfonatocalix (4) arene as a complexing reagent. For this purpose, the influence of four important factors four factors which was influenced on the extraction efficiency such as salt addition, solution pH and disperser and extraction solvent volumes were investigated. Central composite design (CCD) as a comparative technique was employed for optimization of ST-DLLME efficiency. The ANN-BA optimization technique was regarded as a superior model due to its higher value of extraction efficiency (about 7.21%) compared to CCD method. Under ANN-BA optimal conditions, the limit of quantitation (S/N = 10), limit of detection (S/N = 3) and linear range were 0.35, 0.12 and 0.35-1000 µg L^-1, respectively. In these circumstances, the percentage recoveries for drinking tea, apple juice, milk, bottled drinking water, river and well water spiked with 0.05, 0.1 and 0.2 mg L^-1 of Cu²⁺ ions were in the acceptable range (91.4-107.1%). In comparison to other methods, the developed ST-DLLME method showed the lowest solvent and sample consumption, shortest value of extraction time, most suitable determination and detection limits and linear range with simple and low cost apparatus. Additionally, the use of bat inspired algorithm as a powerful metaheuristic algorithm with the aid of artificial networks is another advantage of the present work.

Simultaneous extraction of Cu2+ and Cd2+ ions in water, wastewater, and food samples using solvent-terminated dispersive liquid-liquid microextraction: optimization by multiobjective evolutionary algorithm based on decomposition

Solvent-terminated dispersive liquid-liquid microextraction (ST-DLLME) as a simple, fast, and low-cost technique was developed for simultaneous extraction of Cd²⁺ and Cu²⁺ ions in aqueous solutions. Multiobjective evolutionary algorithm based on decomposition with the aid of artificial neural networks (ANN-MOEA/D) was used for the first time in chemistry, environment, and food sciences to optimize several independent variables affecting the extraction efficiency, including disperser volume and extraction solvent volume, pH, and salt addition. To perform the ST-DLLME operations, xylene, methanol, and dithizone were utilized as an extraction solvent, disperser solvent, and chelating agent, respectively. Non-dominated sorting genetic algorithm versions II and III (NSGA II and NSGA III) as multiobjective metaheuristic algorithms and in addition central composite design (CCD) were studied as comparable optimization methods. A comparison of results from these techniques revealed that ANN-MOEA/D model was the best optimization technique owing to its highest efficiency (97.6% for Cd²⁺ and 98.3% for Cu²⁺). Under optimal conditions obtained by ANN-MOEAD, the detection limit (S/N = 3), the quantitation limit(S/N = 10), and the linear range for Cu²⁺ were 0.05, 0.15, and 0.15-1000 μg L^-1, respectively, and for Cd²⁺ were 0.07, 0.21, and 0.21-750 μg L^-1, respectively. The real sample recoveries at a spiking level of 0.05, 0.1, and 0.3 mg L^-1 of Cu²⁺ and Cd²⁺ ions under the optimal conditions obtained by ANN-MOEA/D ranged from 94.8 to 105%.

Optimization of Solvent Terminated Dispersive Liquid-Liquid Microextraction of Copper Ions in Water and Food Samples Using Artificial Neural Networks Coupled Bees Algorithm

A multivariate method based on solvent terminated dispersive liquid-liquid microextraction was developed for the determination of Cu²⁺ ions in aqueous samples. In the proposed approach, di-2-ethylhexylphosphoric acid, xylene and acetone were used as chelating agent, dispersive and extraction solvents, respectively. The effects of various factors on the extraction efficiency such as extraction and dispersive solvent volumes, salt addition and pH were studied using central composite design (CCD) and artificial neural networks coupled bees algorithm (ANN-BA). Upon comparison of these techniques, ANN-BA model was considered to be better optimization method due to its higher percentage relative recovery (about 5%) as compared to the CCD approach. The linear range and the limits of detection (S/N = 3) and quantitation (S/N = 10) were 0.22-140, 0.08 and 0.22 µg L^-1, respectively. Under the optimal conditions, the recoveries for real samples spiked with 0.1 and 0.3 mg L^-1 were in the range of 85-98%.

Solid-phase microextraction of ultra-trace amounts of tramadol from human urine by using a carbon nanotube/flower-shaped zinc oxide hollow fiber

A new method is successfully developed for the separation and determination of a very low amount of tramadol in urine using functionalized multiwalled carbon nanotubes/flower-shaped zinc oxide before solid-phase microextraction combined with gas chromatography. Under ultrasonic agitation, a sol of multiwalled carbon nanotubes and flower-shaped zinc oxide were forced into and trapped within the pore structure of the polypropylene and the sol solution immobilized into the hollow fiber. Flower-shaped zinc oxide was synthesized and characterized by Fourier transform infrared spectroscopy. The morphology of the fabricated solid-phase microextraction surface was investigated by scanning electron microscopy and X-ray diffraction. The parameters affecting the extraction efficiencies were investigated and optimized. Under the optimized conditions, the method shows linearity in a wide range of 0.12-7680 ng/mL, and a low detection limit (S/N = 3) of 0.03 ng/mL. The precision of the method was determined and a relative standard deviation of 3.87% was obtained. This method was successfully applied for the separation and determination of tramadol in urine samples. The relative recovery percentage obtained for the spiked urine sample at 1000 ng/mL was 94.2%.