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Nasser Goudarzi Sahar Farsimadan Mansour Arab Chamjangali Ghadam Ali Bagherian Faculty of chemistry, University of Shahrood, Shahrood, Iran Received January 7, 2015 Revised February 7, 2015 Accepted February 27, 2015

Research Article

Optimization of modified dispersive liquid–liquid microextraction coupled with high-performance liquid chromatography for the simultaneous preconcentration and determination of nitrazepam and midazolam drugs: An experimental design A simple, sensitive, and rapid microextraction method, namely, ultrasound-assisted surfactant-enhanced emulsification microextraction based on the solidification of floating organic droplet method coupled with high-performance liquid chromatography was developed for the simultaneous preconcentration and determination of nitrazepam and midazolam. The significant parameters affecting the extraction efficiency were considered using Plackett–Burman design as a screening method. To obtain the optimum conditions with consideration of the selected significant variables, a Box–Behnken design was used. The microextraction procedure was performed using 29.1 ␮L of 1-undecanol, 1.36% (w/v) of NaCl, 10.0 ␮L of sodium dodecyl sulfate (25.0 ␮g mL−1 ), and 1.0 ␮L of Tween80 (25.0 ␮g mL−1 ) as an emulsifier in an extraction time of 20.0 min at pH 7.88. In order to investigate the validation of the developed method, some validation parameters including the linear dynamic range, repeatability, limit of detection, and recoveries were studied under the optimum conditions. The detection limits of the method were 0.017 and 0.086 ng mL−1 for nitrazepam and midazolam, respectively. The extraction recovery percentages for the drugs studied were above 91.0 with acceptable relative standard deviation. The proposed methodology was successfully applied for the determination of these drugs in a number of human serum samples. Keywords: Benzodiazepines / Experimental design / Microextraction / Midazolam / Nitrazepam DOI 10.1002/jssc.201500007



Additional supporting information may be found in the online version of this article at the publisher’s web-site

1 Introduction Benzodiazepines belong to a type of drug that acts on the neurotransmitter ␥-aminobutyric acid (GABA) receptors, resulting in sedative, hypnotic, and anxiolytic properties [1]. Midazolam (MDZ) is an ultra-short-acting tricyclic benzodiazepine, commonly used in anesthesia induction, short-term sedation, treatment of acute seizures and moderate to severe Correspondence: Dr. Goudarzi. Faculty of Chemistry, Shahrood University of Technology, P. O. Box 316, Shahrood, Iran Email: [email protected]; [email protected]

Abbreviations: MDZ, midazolam; NTZ, nitrazepam; DLLME, dispersive liquid–liquid microextraction; DLLMESFODs, dispersive liquid–liquid microextraction based on the solidification of floating organic droplets; UAEME, ultrasoundassisted emulsification microextraction; UA-SEME, ultrasoundassisted surfactant-enhanced emulsification microextraction; ANOVA, analysis of variance

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insomnia to induce amnesia before a medical procedure [2]. On the other hand, nitrazepam (NTZ) is an intermediateacting hypnotic drug, which is a benzodiazepine derivative. It belongs to the chloride channel potentiater pharmacological group on the basis of the mechanism of its action and is also classified as the anti-epileptic agent pharmacological group [3]. These drugs are commonly misused because of their sedative and hypnotic effects and their use have rapidly expanded in recent years. Thus, the analytical information derived from the analysis of these illicit drugs is important for legal purposes. Numerous analytical procedures including HPLC, LC– MS/MS, flow injection fluorimetry, and TLC have been developed for the analysis of these drugs in various matrices [3–7]. Generally, the concentration of these drugs in complex biological matrices is very low and so application of separation and preconcentration techniques is necessary. Two conventional sample preparation techniques, namely,

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SPE and liquid-phase extraction have many drawbacks such as consuming a large amount of toxic organic solvents and the requirement of many hours to achieve satisfactory recoveries [8]. Also these methods are tedious, expensive and time-consuming. To overcome these drawbacks, many developments have been introduced to miniaturized extraction procedures like SPME, single drop liquid-phase microextraction, hollow fiber liquid-phase microextraction and dispersive liquid–liquid microextraction (DLLME) as simple and fast extraction procedures compared with the conventional ones. Recently, the introduction of DLLME by Assadi and coworkers has attracted interests in the preconcentration and determination of a large variety of compounds [9]. Therefore, because of the short analysis time, high enrichment factor, simplicity and low consumption of organic solvent, DLLME has been introduced as a powerful sample preparation method. However, it is noteworthy that the extraction solvents used in DLLME must have a higher density than water (like CHCl3 , CCl4 , CH2 Cl2 ), and also these solvents are toxic and environmentally unfriendly [10]. Recently, to reduce these disadvantages, dispersive liquid–liquid microextraction based on the solidification of floating organic droplets (DLLMESFODs) has been introduced and applied to the environmental sample analysis [11]. In this procedure, a low density and less toxic solvent with a melting point near room temperature (in the range of 10–30⬚C) is used. Recently, a new mode of LPME termed ultrasound-assisted emulsification microextraction (UAEME) has been developed [12]. UAEME is based on the emulsification of a few micro-volume of organic solvent in an aqueous sample solution using ultrasound irradiation. In UAEME, the extraction solvent is dispersed into the aqueous solution by the ultrasound irradiation without using any disperser solvent. This procedure has been considered as a simple, fast and efficient preconcentration procedure for the determination of many compounds in various aqueous matrices [13–15]. Surfactants are chemicals that are active at the surface or the interface between two phases. They are amphiphilic, and contain both the hydrophobic and hydrophilic groups and so these compounds are soluble both in water and organic solvents [16]. Recently, surfactants have been used as an emulsifier to enhance the dispersion of a water-immiscible phase into an aqueous phase, replacing the disperser solvents in DLLME. Because of the solubility of the disperser solvents such as methanol, ethanol, and acetone in an aqueous solution, consumption of these organic solvents decreases the partition coefficient of analytes in the extraction solvents [17]. Therefore, a new mode of UAEME, named ultrasound-assisted surfactant-enhanced emulsification microextraction has been developed (UA-SEME) [18]. The role of surfactant is to accelerate the dispersion of an extraction solvent into a sample solution using the ultrasound irradiation. This method has been proved to be a simple and rapid procedure for the preconcentration and determination of various compounds [19–22]. The aim of the present study is to develop an ultrasoundassisted surfactant-enhanced emulsification microextraction  C 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

technique based on the solidification of floating organic droplet method with both the advantageous of UA-SEME and DLLME-SFOD. It is clear that, like the other microextraction methods, a large number of variables can affect the preconcentration efficiency. Firstly, a Plackett–Burman design (PBD) was used as the screening design to evaluate the main experimental variables. Then the experimental conditions for the preconcentration procedure were optimized using a Box–Behnken design (BBD) as a powerful tool for determining the optimized conditions. Now, for the first time, the UA-SEME-SFOD method coupled with HPLC equipped with an UV multiple wavelength detector (UV-MWD) was used for the simultaneous preconcentration and determination of NTZ and MDZ in human serum samples.

2 Materials and methods 2.1 Reagents and solutions The standard compounds MDZ and NTZ used in this study were supplied as gifts from Abureihan Company (Tehran, Iran). HPLC-grade acetonitrile was purchased from CALEDON Company (Georgetown, Ontario, Canada). Methanol (HPLC grade), 1-undecanol, hydrochloric acid (37%), sodium hydroxide, SDS, Tween 80, and sodium hydrogen phosphate, all of analytical grade, were purchased from Merck (Darmstadt, Germany). Standard solutions of each drug (1.0 mg mL−1 ) were prepared in acetonitrile, stored in a refrigerator, and brought to ambient temperature just before use. The daily standard working solutions with different concentrations were prepared by dilution of the appropriate volumes of the standard stock solution with acetonitrile. 2.2 Instrumentation HPLC analysis was performed using an Agilent 1100 HPLC system equipped with an UV-MWD. For processing the chromatographic data, an Agilent ChemStation program for LC was used. Chromatography separations were carried out using a C18 column (4.5 mm × 150 mm with 5 ␮m particle size) at room temperature. A mixture of acetonitrile/phosphate buffer (pH 5.5; 0.06 M; 1:1), with the flow rate of 1.5 mL min−1 was used as the mobile phase. The UV-MWD was set at 218 and 258 nm for NTZ and MDZ, respectively. An ultrasonic water bath (BANDELIN Electronic, Germany) was used for assisting the emulsification procedure. Also for centrifuging the extracting solution, a centrifuging machine (Hettich EBA 20, Germany) was used. Adjustment and measurement of pH values for the sample solution and mobile phase were carried out using a Metrohm-774 pH-meter equipped with a combined glass electrode. 2.3 UA-SEME-SFOD procedure For the proposed procedure, a 10.0 mL aliquot of the aqueous sample solution containing NTZ and MDZ (1.0 ␮g mL−1 ) www.jss-journal.com

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and NaCl 1.36% w/v was placed in a glass test tube. A mixture of 10.0 ␮L SDS (with concentration of 25.0 ␮g mL−1 ), 1.0 ␮L Tween 80 (25.0 ␮g mL−1 ) as an emulsifier and 29.1 ␮L 1-undecanol as extraction solvent were added to the sample solution. The resulting mixture was immersed in an ultrasonic water bath for 20.0 min at room temperature. Then the tube containing the sample was centrifuged at 4000.0 rpm for 5.0 min. Subsequently, the glass test tube was transferred into an ice bath for about 5.0 min, which caused the organic phase to solidify. After that, the solidified organic phase was transferred into a conical vial for melting at room temperature. Finally, 5.0 ␮L of the organic phase including the extracted drugs was injected into the HPLC system for separation and determination. To the best of our knowledge, we introduced, for the first time, a microextraction method (coupled to HPLC) for the simultaneous preconcentration and determination of these drugs.

3 Results and discussion 3.1 UA-SEME-SFOD optimization 3.1.1 Selection of type of extraction solvent and surfactant Several requirements depending on the extraction method were considered in choosing the extraction solvent. The extraction solvent in DLLME-SFOD must have a density lower than water and its melting point must be near or below the room temperature to solidify and make it easy to collect the extractant phase [23]. Taking into account these considerations, 1,10-dichlorodecane, 1-dodecanol, and 1-undecanol were tested as the extraction solvents. According to the results obtained from the preliminary studies, 1-undecanol showed to have the best recovery and thus was selected as the extraction solvent in the UA-SEME-SFOD. On the other hand, surfactant plays an important role in the SEME-SFOD procedure and maybe replaced instead of disperser solvent and other assisted emulsification agents. In this study, cetyl trimethyl ammonium bromide, SDS, Tween 80, Triton-X114, and some of their combinations were tested to accelerate the dispersion of the extraction solvent in the bulk of the sample solution. The results obtained revealed that combination of Tween 80 and SDS as mixed anionic-nonionic compounds show the highest extraction efficiency and therefore was used in this procedure.

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Figure 1. Standardized (P = 0.05) Pareto chart in the Plackett– Burman factorial design.

classical optimization approach for all factors is tedious and time consuming. Consequently, by paying attention to the number of factors, a PBD was applied to determine the main factors. In this screening design, the interactions between the factors can be thoroughly ignored and so the main effects can be calculated with a reduced number of experiments. This means that they are only partially aliased with higher order interactions [24]. To evaluate the present work, the sum of peak areas for two studied drugs was considered as an experimental response. In this study, the levels of factors were determined using the preliminary studies and design matrix were presented in Table 1. The experimental response (Y) was represented by the following linear polynomial model: Y = 2707.36 + 420.994A − 45.5943B + 9.01445C −6.55955D − 26.4568E − 260.699F

(1)

It is noteworthy that the coefficients for different factors were calculated using the stratigraphic centurion x5 software. Then the analysis of variance (ANOVA) test was applied to the experimental data (the results obtained were tabulated in Supporting Information Table 1). The normalized results for the experimental design were evaluated at the 5% level of significance and analyzed by the standardized Pareto chart (Fig. 1). According to the results obtained from the Pareto chart, pH, volume of the extraction solvent, and amount of salt content were shown to be significant (P < 0.05), with positive or negative effects and lie above the t-value limit. The extraction time showed a positive and non-significant effect on the extraction efficiency. Also, as appeared in the Pareto chart, the volumes of Tween 80 and SDS have no significant effects and were considered at low levels in the following study. 3.1.3 Optimization design

3.1.2 Screening design The efficiency of this microextraction method can be influenced by several variables such as pH, volumes of the extraction solvent and surfactant, amount of salt and extraction time. Thus, selection of the experimental conditions is a crucial step and must be considered. Therefore, it is clear that in the extraction procedures, depends on numerous factors, the  C 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

To investigate the significant independent variables using the PBD, an experimental design based on the response surface methodology was proposed for optimization of the extraction efficiency. BBD is a three-level incomplete factorial design, which is useful for estimating the coefficients in a second degree polynomial model to predict the response of experiment. It is an empirical modeling technique that can be used to www.jss-journal.com

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Table 1. Independent variables, their symbols and their levels and design matrix for the Plackett–Burman design

Variable level Variable

Effect symbol

–1

+1

pH Volume of extraction solvent (␮L) Volume of SDS (␮L) Volume of Tween 80 (␮L) Extraction time (min) Salt (%w/v)

A B C D E F

6 15 10 1 1 0.05

11 75 200 70 20 1.5

Run Number

A

B

C

D

E

F

Response

1 2 3 4 5 6 7 8 9 10 11 12

11 11 6 6 11 11 6 6 11 6 6 11

15 15 75 15 75 15 75 15 75 75 15 75

200 10 200 200 10 200 200 10 10 10 10 200

70 1 1 70 70 1 70 1 70 1 70 1

1 20 20 20 20 1 1 1 1 1 20 20

1.5 1.5 0.05 0.05 0.05 0.05 1.5 0.05 0.05 1.5 1.5 1.5

8050.05 9740.10 2105.60 4563.10 4029.30 7346.20 3048.30 4876.91 2917.45 2893.37 6146.88 4548.93

Table 2. Design matrix and responses for the Box–Behnken design

Run number

A

B

F

Response

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

– 0 + 0 + 0 + – 0 0 – – 0 + 0

– 0 + – 0 0 – + + + 0 0 – 0 0

0 0 0 + + 0 0 0 – + – + – – 0

4056.29 5560.71 4485.06 5577.27 3638.79 5219.06 4058.18 474.41 2565.01 3718.80 2477.41 4797.05 3092.48 3702.22 5577.27

Table 3. Analysis of variance for the Box–Behnken design

Source

Sum of Squares

Df

Mean Square

F-Ratio

P-Value

A B C AA AB AC BB BC CC blocks Total error Total (corr.)

3.32663 × 106 6.88229 × 106 8.4148 × 106 1.03422 × 107 9.61242 ×106 2.58484 ×106 9.47867 ×106 885794 3.03145 × 106 76.9409 4.24752 × 106 5.60474 × 107

1 1 1 1 1 1 1 1 1 1 19 29

3.32663 × 106 6.88229 × 106 8.4148 × 106 1.03422 × 107 9.61242 × 106 2.58484 × 106 9.47867 × 106 885794 3.03145 × 106 76.9409 223554

14.88 30.79 37.64 46.26 43.00 11.56 42.40 3.96 13.56 0.00

0.0011 0.0000 0.0000 0.0000 0.0000 0.0030 0.0000 0.0611 0.0016 0.9854

Also by applying multiple regression analysis, a second-order equation was obtained, as follows: Response = − 9800.53 + 2986.68A − 20.9411B + 6243.82F

evaluate the relationship between the experimental and predicted results [25]. Based upon the results obtained using PBD, pH, volume of extraction solvent and amount of salt had significant effects on the extraction recovery at 95% confidence level and so had to be optimized. All the other variables and their interactions were not significant factors in the studied conditions. To obtain the exact optimum conditions, a BBD was applied using three significant factors that selected by screening PBD. Table 2 shows the design matrix for BBD.

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−189.349A2 + 14.6154AB − 313.613AF −1.25883B 2 − 15.299B F − 1218.95F 2

(2)

From the normal probability graph, it is obvious that the residuals followed a normal distribution. The data obtained was evaluated by the ANOVA test (Table 3) and the effects were also shown using a Pareto chart (figure S1). The determination coefficient (R2 ) and the adjusted determination

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Figure 2. Estimated response surface plotting of main factors.

2 coefficient (Radj ) values for the obtained model were 0.9242 and 0.8843, respectively. This means that there is an excellent correlation between the experimental and predicted response values. In other words, the model could describe 92.42% of the variability in the response. Based upon the Pareto chart, each of the three factors mentioned above had a significant effect on the extraction recovery. Fig. 2 shows typical response surface profile drawn vs. the main factors. As it can be observed, the highest extraction efficiency is achievable in the region with low volumes of extraction solvent and also the high values of salt and pH. Noteworthy, interaction between the amount of salt and pH had a positive effect on the extraction recovery. Consequently, the optimal working conditions were obtained by adding 1.36% w/v of NaCl and 29.14 ␮L of the extraction solvent at pH 7.88.

3.2 Method validation To investigate the practicality of the developed method, some validation parameters including the linear dynamic range (LDR), repeatability, LOD, LOQ and recoveries were studied under the optimum conditions of extraction. The data obtained for investigation of these parameters using the UASEME-SFOD procedure are summarized in Table 4. Under the optimum conditions for extraction, calibration curves were plotted by extracting ten spiking levels in triplicate, and the linear dynamic range for the method was obtained to be 0.5–6.5 × 10 3 and 0.8–5.5 × 103 ng mL−1 for NTZ and MDZ, respectively, with a good square correlation coefficient. The LOD is defined as the minimum concentration of analyte, which is detectable by the studied method. The LOD can be obtained from the equation (3): LOD =

3s b m

(3)

where sb is the SD of blank sample for ten replicates, and m is the slope of calibration curve, the value of which for NTZ and MDZ were calculated to be 0.017 and 0.086 ng mL−1 , respectively. The repeatability of the developed method was expressed and calculated as the inner-day and intra-day

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RSD in one day and on different days. The intra-day and inner-day RSDs for the five replicates were between 2.06– 6.5% and 1.3–3.5%, respectively. The chromatogram of the blank serum and serum samples spiked with a known amount of drugs are shown in Fig. 3, confirming the absence of interference from any endogenous of the serum. These results show that the proposed method has a high sensitivity and good repeatability. As mentioned above, most of the previous reports are on the direct determination or SPE of these drugs. The results obtained reveal that the proposed method is comparable with other previously published methods (Table S2) [3–7, 27–33]. The low LODs and wide linear ranges were obtained for these drugs indicate that the suggested procedure is a powerful tool for the analysis of these drugs in biological matrices.

3.3 Effect of interfering compounds To test the applicability of the proposed method in different matrix, the effects of the interfering foreign species on the simultaneous pre-concentration and determination of these drugs were considered under the optimum conditions. For this purpose, first the peak areas were measured for 0.5 ng mL−1 solution of each drug after microextraction in the absence and presence of each foreign species. Each analytical signal (peak area) obtained was measured six times, and the mean signal and SD were calculated. When the mean peak area change exceeds ±3s (where s is the SD belonging to six replicate determinations for 0.5 ng mL−1 of each drug), the foreign species causes interference. The results obtained show that the presence of 500-fold barbituric acid, cysteine, diazepam, sertaline, and chlorodiazopoxide; 250-fold citalopram, L-alanine, methionine, ascorbic acid, and citric acid; and finally, 50-fold vitamin B6 , thiourea, glucose, and lactose has no interference.

3.4 Analysis of real samples To evaluate the applicability and accuracy of the proposed method in real samples, blood from ten volunteers was drawn and collected into test tubes without the addition of anticoagulant. After centrifuging at 1000.0 rpm for about 15 min, the supernatant phase was collected and stored at –8⬚C for analysis. For this reason, the serum sample was spiked into the drugs at three different levels using the working solution. Then 1.0 mL of the serum and an appropriate amount of drug solution were mixed with 0.6 mL of acetonitrile to remove proteins and other compounds. Then the mixture solution was centrifuged at 4000.0 rpm for 5 min [26]. The transparent solution was transferred into a sample vial, and the preconcentration procedure was performed under the optimum conditions. The triplicate serum samples were analyzed for

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Table 4. Quantitative results for the proposed method

NTZ MDZ

Equation

R2

Linear range (ng mL−1 )

LOD (ng mL−1 )

LOQ (ng mL−1 )

Enrichment factor

Y = 1815.6x+833.07 Y = 2734.6x+223.72

0.997 7 0.9966

0.8–5.5 × 103 0.5–6.5 × 103

0.017 0.086

0.057 0.287

114 112

Figure 3. Chromatograms of the blank serum samples (a) and serum samples spiked with 0.05 mg L−1 of NTZ and MDZ, respectively, in 220 and 258 nm.

NTZ and MDZ, and the relative recovery (RR) was calculated from equation (4): % RR =

Cfound − Creal × 100 Cadded

(4)

where Cfound , Creal , and Cadded are the concentrations of the analytes determined after spiking the known amount of the NTZ and MDZ into the real sample, the determined concentration of the analytes in real sample, and the spiked concentration into the real sample, respectively. The results obtained for determination of the drugs in the serum samples are given in Table 5. As it can be seen, the relative recovery value ranged between 91.0–108.0% with RSD between 0.8– 3.6, which demonstrated the repeatability of the proposed method.

4 Conclusion In the present study, for the first time, a microextraction method named ultrasound-assisted surfactant-enhancement emulsification based on the solidification of floating organic droplet method (UA-SEME-SFOD) coupled with  C 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

Table 5. Relative recoveries and SDs of NTZ and MDZ in human serum samples

Analytes NTZ

MDZ

Cadded (␮g mL−1 )

Cfound (␮g mL−1 )

Relative recovery (%)

RSD (%)

0.5 1.0 1.5 0.5 1.0 1.5

0.473 1.08 1.61 0.497 0.91 1.49

94.6 108 107.3 99.4 91.0 99.33

2.6 1.6 2.8 0.8 3.6 1.8

HPLC equipped with a UV multiple wavelength detector (UV-MWD) was developed for the determination and preconcentration of NTZ and MDZ in human serum samples. The proposed method is fast, low cost and with a low consumption of organic solvent. However, the combination of SDS and Tween 80 was used instead of the disperser solvent as the emulsifier agent. The proposed method provided low LODs, a good repeatability, and an acceptable enrichment factor in a short analysis time. According to the results obtained, this method is a powerful technique for the www.jss-journal.com

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simultaneous preconcentration and determination of NTZ and MDZ in human serum samples. Also, this method can be successfully applied for the simultaneous preconcentration and determination of the other drugs or organic compounds.

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Optimization of modified dispersive liquid-liquid microextraction coupled with high-performance liquid chromatography for the simultaneous preconcentration and determination of nitrazepam and midazolam drugs: An experimental design.

A simple, sensitive, and rapid microextraction method, namely, ultrasound-assisted surfactant-enhanced emulsification microextraction based on the sol...
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