In this study, two novel sample extraction methods for the analysis of bisphenol A (BPA) in edible oils were developed by using liquid–liquid extraction followed by a dispersive liquid–liquid microextraction (LLE-DLLME) and reversed-phase dispersive liquid–liquid microextraction (RP-DLLME). RP-DLLME showed a superior characteristic over LLE-DLLME and other previously reported procedures because of its easy operation, short extraction time, high sensitivity, low organic solvent consumption and waste generation. The optimized extraction conditions of RP-DLLME for 1.0g of edible oil diluted in 4mL of n-hexane were: extractant, 100μL 0.2M sodium hydroxide solution (80% methanol, v/v); extraction time, 1min; centrifugation, 3min. The determination of BPA was carried out by high performance liquid chromatography coupled with a DAD detector. The method offered excellent linearity over a range of 0.010–0.5μgg−1 with a correlation coefficient of r>0.997. Intra-day and inter-day repeatability values expressed as relative standard deviation were 1.9% and 5.9%, respectively. The quantitation limit and detection limit were 6.3 and 2.5ngg−1. The target analyte was detected in 5 out of 16 edible oil samples. The recovery rates in real samples ranged from 89.5 to 99.7%.

Two popular calibration strategies are classical least squares (CLS) and inverse least squares (ILS). Underlying CLS is that the net analyte signal used for quantitation is orthogonal to signal from other components (interferents). The CLS orthogonality avoids analyte prediction bias from modeled interferents. Although this orthogonality condition ensures full analyte selectivity, it may increase the mean squared error of prediction. Under certain circumstances, it can be beneficial to relax the CLS orthogonality requisite allowing a small interferent bias if, in return, there is a mean squared error of prediction reduction. The bias magnitude introduced by an interferent for a relaxed model depends on analyte and interferent concentrations in conjunction with analyte and interferent model sensitivities. Presented in this paper is relaxed CLS (rCLS) allowing flexibility in the CLS orthogonality constraints. While ILS models do not inherently maintain orthogonality, also presented is relaxed ILS. From development of rCLS, presented is a significant expansion of the univariate selectivity coefficient definition broadly used in analytical chemistry. The defined selectivity coefficient is applicable to univariate and multivariate CLS and ILS calibrations. As with the univariate selectivity coefficient, the multivariate expression characterizes the bias introduced in a particular sample prediction because of interferent concentrations relative to model sensitivities. Specifically, it answers the question of when can a prediction be made for a sample even though the analyte selectivity is poor? Also introduced are new component‐wise selectivity and sensitivity measures. Trends in several rCLS figures of merit are characterized for a near infrared data set.

Paclitaxel-loaded polymeric micelles (PTX-PM) are commonly used as tumor-targeted nanocarriers and display outstanding antitumor features in clinic, but its accumulation and distribution in vitro are lack of investigation. It is probably due to the complex micellar system and its low concentration at the cellular or subcellular levels. In this study, we developed an improved extraction method, which was a combination of mechanical disruption and liquid-liquid extraction (LLE), to extract the total PTX from micelles in the cell lysate and subcellular compartments. An ultra-performance liquid chromatography tandem mass spectroscopy (UPLC-MS/MS) method was optimized to detect the low concentration of PTX at cellular and subcellular levels simultaneously, using docetaxel as internal standard (IS). The method was proved to release PTX totally from micelles (≥95.93%) with a consistent and reproducible extraction recovery (≥75.04%). Good linearity was obtained at concentrations ranging from 0.2 to 20ng/mL. The relative error (RE%) for accuracy varied from 0.68 to 7.56%, and the intra- and inter-precision (relative standard deviation, RSD%) was less than 8.64% and 13.14%, respectively. This method was fully validated and successfully applied to the cellular uptake and distribution study of PTX-loaded PLGA-PEG micelles in human breast cancer cells (MCF-7).

Methamphetamine abuse is one of the most medical and social problems many countries face. In spite of the ban on the use of methamphetamine, it is widely available in Iran's drug black market. There are many analytical methods for the detection of methamphetamine in biological specimen. Oral fluid has become a popular specimen to test for the presence of methamphetamine. The purpose of the present study was to develop a method for the extraction and detection of methamphetamine in oral fluid samples using liquid-liquid extraction (LLE) and gas chromatography/mass spectrometry (GC/MS) methods. An analytical study was designed in that blank and 50 authentic oral fluid samples were collected to be first extracted by LLE and subsequently analysed by GC/MS. The method was fully validated and showed an excellent intra- and inter-assay precision (reflex sympathetic dystrophy ˂ 10%) for external quality control samples. Recovery with LLE methods was 96%. Limit of detection and limit of quantitation were 5 and 15 ng/mL, respectively. The method showed high selectivity, no additional peak due to interfering substances in samples was observed. The introduced method was sensitive, accurate and precise enough for the extraction of methamphetamine from oral fluid samples in forensic toxicology laboratories.

The presence of contaminants of emerging concern (CECs) in wastewater effluent and surface waters is an important field of research for analytical scientists. This study takes a suspect screening approach to wastewater and surface water analysis using comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry (GC × GC-TOFMS). Two extraction procedures, traditional liquid-liquid extraction (LLE) and stir bar sorptive extraction (SBSE), were utilized and evaluated for their application to wastewater and surface water samples. Both techniques were evaluated regarding their recovery rates, range of compound classes extracted, and on their application to discovery of CECs. For the 14 surrogate compounds analyzed, LLE was able to extract all of them in each matrix with a recovery range of 19% to 159% and a median value of 74%. For SBSE, the recovery rates ranged from 19% to 117% with the median value at 66%, but only 8 of the compounds were able to be extracted because of the polarity bias for this extraction method. A new method of SBSE calibration was also developed using direct liquid injection of the internal standards before desorption of the stir bars. Initial findings indicate increased sensitivity and a greater range of unknown analyte recovery for SBSE, especially in the more dilute effluent and surface water samples. With the methods used in this study, SBSE has a concentration factor of approximately 416, improving that of LLE, which is 267. Suspect screening analysis was utilized to tentatively identify 32 CECs in the samples, the majority of which were pharmaceuticals and personal care products. More CECs were found using SBSE than LLE, especially in the surface water samples where 13 CECs were tentatively identified in the SBSE samples compared to 6 in the LLE samples.

A rapid and specific liquid chromatographic mass/mass (LC-MS/MS) method is described for the assessment of valsartan (VAL) in human plasma after protein precipitation (PPT) and liquid-liquid extraction (LLE) techniques. The column used in PPT method was Eclipse Plus column, (C18, 50 mm x 2.1 mm, 1.8 μm) with a mobile phase ratio of 0.1% formic acid: methanol (15:85, v/v) while the column used in LLE method was Agilent column, (C18, 50 mm x 4.6 mm, 5 μm) with a mobile phase ratio of 0.1 % formic acid: acetonitrile (20:80, v/v). The assay was found to be linear over the ranges of 20-10000 and 25-8000 ng/ mL VAL using the PPT and LLE, respectively. The developed method was validated following the united states food and drug administration (US - FDA) recommendations and directions from the European Medical Agency (EMA). The method was validated for sensitivity, selectivity, linearity, accuracy and precision, recovery, dilution integrity, matrix effect, carryover in the matrix, and analyte stability during both short- and long-term sample processing and storage.

Liquid–liquid equilibrium (LLE) data are critical for the design and optimization of processes for extracting aromatics. Partial LLE data for the non-aromatic–aromatic–sulfolane ternary system were acquired at 313.15 K and 101.3 kPa. The LLE data for the extraction of aromatics using sulfolane were predicted using the COSMO-RS model. Correspondingly, the predicted and experimental data were analyzed using the root mean square deviation (RMSD), distribution coefficient (D), and separation factor (S). The COSMO-RS model could better predict the LLE data for the extraction of aromatics by sulfolane. The results of quantum chemical calculation show that hydrogen bonds and van der Waals interactions between sulfolane–benzene and sulfolane–toluene were responsible for the strong selectivity of sulfolane for benzene and toluene over alkanes. The LLE data predicted by the COSMO-RS method using the UNIQUAC thermodynamic model were subjected to correlation analysis. The calculated RMSD values were all less than 0.0180, and the relative deviation (δ) between the simulated value of the main process index for the extraction column and the actual data was less than 2.5%, indicating that the obtained binary interaction parameters can be reliably used in designing and optimizing the extraction of aromatics using sulfolane.

Dinotefuran is a compound belonging to the third generation of nicotinoid insecticides, and has been effective in combating pests that are resistant to conventional insecticides, such as organophosphates, carbamates, and pyrethroids. This molecule presents high-water solubility (39,830 mg L−1 at 25 °C) compared to other pesticides, which facilitates its drag and leaching to lower soil layers. Therefore, the present study aimed to optimize and validate liquid–liquid extraction with low temperature purification (LLE–LTP) to determine dinotefuran residues in water by high performance liquid chromatography with diode array detection (HPLC–DAD). The results revealed that the analyte recovery ranged from 85.44 to 89.72% with a relative standard deviation <5.8. LLE–LTP was selective, precise, accurate, and linear in the range from 10.0 to 210 µg L−1, and presented limits of detection and quantification of 5.00 and 10.00 µg L−1, respectively. The matrix effect was <14%. The stability study of dinotefuran in water revealed significant stability of this molecule in water in the absence of light (>130 days), and a half-life of 7 days in water with sunlight. LLE–LTP coupled to HPLC–DAD was a simple, easy, and efficient method for extracting and analyzing dinotefuran in water samples.

Rilmenidine is an alpha 2 adrenoreceptor agonist used in the treatment of mild and moderate hypertension. In this study, a fast and accurate liquid chromatographic method with tandem mass spectrometric detection has been validated in order to assure quantification of rilmenidine in human serum. The fragmentation pathway of protonated rilmenidine was studied using high-resolution mass spectrometry (HRMS). This study compared selectivity, linearity, accuracy, precision, extraction efficiency, matrix effect and sensitivity using common liquid-liquid extraction (LLE) and solid-phase extraction (SPE) procedures. The limit of quantitation for both extraction techniques was 0.1 ng/ml. Several differences between the LLE and SPE have been observed in terms of linearity, accuracy, precision and matrix effect. Additionally, the advantages of SPE included less manual work load and increased recovery of rilmenidine in human serum to approximately 80% (LLE, 57%). The developed method involving SPE was found to be accurate (relative error (RE) < 5%), reproducible (relative standard deviation, RSD < 7%), robust and suitable for quantitative analysis of rilmenidine in serum samples obtained from patients under antihypertensive treatment.

A sensitive and reproducible liquid chromatography–mass spectrometric (LC-MS) method has been developed and validated for the quantifi cation of doxycycline in human plasma, after liquid-liquid extraction (LLE). Best chromatographic resolution was achieved on a reverse-phase Phenomenex C18 column using the mobile phase acetonitrile–5mM ammonium acetate (80:20) in isocratic elution with a total run time of 3.5 min. The analyte, doxycycline was detected by using an electrospray ionization mass spectrometer in the selected ion monitoring (SIM) mode. Linear plot was obtained in the concentration range of 0.5–5.0 µg/ml (r2 = 0.998). Lower limit of quantifi cation (LLOQ) was found to be 100 ng/ml in 500µl of plasma. Average recovery of the analyte was found to range from 96.08 to 104.60% in plasma at the concentrations of 1.0, 3.0 and 5.0 µg/ml. Intra- and inter-day relative standard deviation was found to be 0.13-0.74 and 0.11-0.34 respectively. The present method was successfully applied in the pharmacokinetic study of doxycycline in human plasma.