Journal of Chromatography A, 1364 (2014) 117–127

Contents lists available at ScienceDirect

Journal of Chromatography A journal homepage: www.elsevier.com/locate/chroma

Trace analysis of selected hormones and sterols in river sediments by liquid chromatography-atmospheric pressure chemical ionization–tandem mass spectrometry ´ Zorica Jaukovic, ´ Mila Lauˇsevic´ Ivana Matic´ ∗ , Svetlana Grujic, Faculty of Technology and Metallurgy, University of Belgrade, Karnegijeva 4, 11000 Belgrade, Serbia

a r t i c l e

i n f o

Article history: Received 11 July 2014 Received in revised form 15 August 2014 Accepted 18 August 2014 Available online 26 August 2014 Keywords: Steroids Hormones Sterols Sediments LC–MS

a b s t r a c t In this paper, development and optimization of new LC–MS method for determination of twenty selected hormones, human/animal and plant sterols in river sediments were described. Sediment samples were prepared using ultrasonic extraction and clean up with silica gel/anhydrous sodium sulphate cartridge. Extracts were analyzed by liquid chromatography-linear ion trap–tandem mass spectrometry, with atmospheric pressure chemical ionization. The optimized extraction parameters were extraction solvent (methanol), weight of the sediment (2 g) and time of ultrasonic extraction (3× 10 min). Successful chromatographic separation of hormones (estriol and estrone, 17␣- and 17␤-estradiol) and four human/animal sterols (epicoprostanol, coprostanol, ␣-cholestanol and ␤-cholestanol) that have identical fragmentation reactions was achieved. The developed and optimized method provided high recoveries (73–118%), low limits of detection (0.8–18 ng g−1 ) and quantification (2.5–60 ng g−1 ) with the RSDs generally lower than 20%. Applicability of the developed method was confirmed by analysis of six river sediment samples. A widespread occurrence of human/animal and plant sterols was found. The only detected hormone was mestranol in just one sediment sample. © 2014 Elsevier B.V. All rights reserved.

1. Introduction The presence of steroid compounds (hormones and sterols) in the environment is acknowledged as a major environmental and health concern. Natural and synthetic hormones are broadly used in human and veterinary therapy, and are active ingredients of female contraceptive pills. Phytosterols (plant sterols), as margarine constituents, are daily consumed in nutrition, and are also used in prevention of cardiovascular diseases since they show cholesterollowering effect [1]. As products of metabolism, sterols are present in human and animal excretion. Although animal and plant steroids are naturally occurring, increasing levels of hormones and sterols in the environment are indicators of contamination and are primarily explained by constant input from municipal wastewater, i.e. effluents from wastewater treatment plants (WWTPs). Namely, several studies that focused on investigation of their removal in WWTPs have shown that it varies significantly depending on the type of the treatment process [2–6]. Since they are incompletely removed in the treatment, significant amounts of these substances

∗ Corresponding author. Tel.: +381 11 3370410; fax: +381 11 3370387. ´ E-mail address: [email protected] (I. Matic). http://dx.doi.org/10.1016/j.chroma.2014.08.061 0021-9673/© 2014 Elsevier B.V. All rights reserved.

are released into environmental waters. Another route of environmental exposure is the use of remaining WWTP sludge as agricultural fertilizer, which can lead to groundwater contamination by leaching of steroid compounds from sludge-deposited fields [7]. Considering these pathways of surface and groundwater contamination by hormones and sterols, the drinking water is potentially in danger of contamination as well. Additionally, due to their preference to bind to solid matrices [8–10] steroids can accumulate in surface water sediments. They act as environmental reservoirs controlling bioavailability of accumulated hormones and sterols and present risk to biota since they can potentially release considerable amounts of steroids under certain environmental conditions [9]. Natural (estrone, estriol, estradiol, etc.) and synthetic (17␣ethinylestradiol, etc.) hormones can induce endocrine disrupting effects in the aquatic environment, such as stimulation of feminization in fish at very low concentrations [11–13]. It was shown that phytosterols can also act as endocrine and metabolic disruptors in the aquatic environment [14,15]. Traditionally, coliform and enterococci bacteria were used as indicators of environmental fecal contamination [16]. Due to numerous limitations associated with bacteria application as pollution tracers, human and animal sterols are currently being used as indicators of anthropogenic

118

I. Mati´c et al. / J. Chromatogr. A 1364 (2014) 117–127

contamination in various environmental compartments. Together with plant sterols, they are applied for distinguishing between sources of pollution based on their ratios [5,17–21]. Recent development and improvement of analytical methodologies have provided low levels of detection of hormones and sterols in different environmental matrices. The methods applied for extraction and preconcentration of steroids from solid matrices are Soxhlet extraction [18,22,23], ultrasonic extraction (USE) [10,24–28], microwave assisted extraction [29,30] and pressurized liquid extraction [31–33]. Among these techniques, USE is the most frequently used for its simplicity and efficiency in solid sample preparation for instrumental analysis. Commonly reported analytical method for reliable trace analysis of human, animal and plant sterols is gas chromatography–mass spectrometry (GC–MS) regardless whether it is sediment as environmental matrix [18,21,34] or water [19]. However, owing to low volatility and high molecular weight, sterols have to be derivatized prior to GC–MS analysis. It seems that more appropriate choice for sterol analysis is liquid chromatography–mass spectrometry (LC–MS) as a less demanding method than GC–MS, since it does not require analyte derivatization. LC–MS methods have been employed in analysis of both human/animal and plant sterols in biological matrices [35–39]. As for environmental matrices, to the best of our knowledge, there is one paper on analysis of human/animal sterols by LC–MS in water [40], while there are no papers on LC–MS determination of neither human/animal sterols nor phytosterols in sediments. However, phytosterols have been analyzed in plants [41,42] and plant oils [43–48] using LC–MS. LC–MS is more commonly applied for the analysis of hormones. There are a number of papers on hormone determination in biological [49–55], and environmental matrices, such as water [26,56,57] and sediments [9,58–65]. Electrospray ionization (ESI) and atmospheric pressure chemical ionization (APCI) are both equally employed for ionization of hormones and sterols. Given the fact that sterols and hormones belong to the common group of steroid compounds and that they have common sources and routes by which they enter environment, there is a demand for analytical methods for their simultaneous determination. Just a few methods are reported for simultaneous analysis of human, animal and plant sterols and hormones, and all of them are based on GC–MS [5,7,20]. Therefore, the aim of this study was development and application of the analytical method for simultaneous determination of twenty selected hormones and sterols in river sediments by liquid chromatography–tandem mass spectrometry (LC–MS2 ) using atmospheric pressure chemical ionization.

2. Experimental 2.1. Chemicals and reagents Based on the frequency of their use and detection in environmental samples, steroids chosen for the study were: estriol, estrone, equilin, norethindrone, levonorgesterel, 17␣ethinylestradiol, 17␣-estradiol, 17␤-estradiol, mestranol (hormones); cholesterol, cholestanone, epicoprostanol, coprostanol, ␣-cholestanol, ␤-cholestanol (human and animal sterols); desmosterol, stigmasterol, campesterol, ␤-sitosterol, stigmastanol (plant sterols). High purity (>99%) analytical standards were purchased from Steraloids Inc. (Newport, USA). Chemical structures and molecular weights of twenty selected steroids are presented in Table 1. The individual standard solutions were prepared in methanol at the concentration of 100 ␮g ml−1 . The working standard solution was prepared at 1 ␮g ml−1 by mixing the appropriate amounts

of the individual standard solutions and dilution with methanol. All solutions were preserved at −4 ◦ C. All solvents used were HPLC grade from J.T. Baker or Sigma–Aldrich. Anhydrous sodium sulphate was obtained from Sigma–Aldrich. Silica gel (Promochem, LGC Standards GmbH, Germany) had a particle size 0.063–0.2 mm. Prior to use, anhydrous sodium sulphate and silica gel were baked at 450 ◦ C for 6 h and stored in sealed desiccator. Deionized water was obtained by passing the tap water through a GenPure ultrapure water system (TKA, Niederelbert, Germany). 2.2. Method development 2.2.1. Sample collection and pretreatment Six sediment samples were collected from the middle course of the rivers Danube (two samples – Danube I and Danube II), Tisa (one sample), Morava (two samples – Morava I and Morava II) and Sava (one sample). The surface layer of the sediments was sampled. The cities wherefrom sediment samples were collected do not have WWTPs. Samples were air-dried at room temperature in the dark for several days. After drying, the water content in the samples was less than 0.05%. Samples were crushed, homogenized and sieved through 500 ␮m sieve to remove gravel, plant roots and other debris. 2.2.2. Optimization of the sample extraction Extraction parameters optimized in the study were extraction solvent (methanol, ethyl acetate, acetone, acetonitrile, hexane and dichloromethane), weight of the sediment (1.0 g and 2.0 g of the sample) and time of ultrasonic extraction (3× 5 min, 3× 10 min and 3× 15 min). The spiked sediments samples were used for development and optimization of the extraction procedure. They were prepared by adding working standard solution (1 ml) to the sediment (1.0 g), stirring vigorously using vortex mixer and leaving overnight in a fume hood with the purpose of solvent evaporation. Spiked sediments would produce concentration of 2 ␮g ml−1 for each analyte in the final extract. The optimized extraction procedure was as follows: 2.0 g of the spiked sediment sample was extracted with 5 ml of methanol in the ultrasonic bath for 10 min. Sample was then centrifuged for 10 min at 4000 rpm and extract was separated. Extraction was repeated two more times. The resulting extract (15 ml) was evaporated to the volume of 1 ml and transferred onto silica gel/anhydrous sodium sulphate clean up cartridge. Clean up was performed using 10 ml of methanol for elution, evaporation to dryness and reconstitution in 0.5 ml of methanol. All extracts were filtered through 0.45 ␮m polyvinylidene difluoride (PVDF) filter, acquired from Roth (Karlsruhe, Germany) and analyzed. The performance of the finally developed and optimized method was demonstrated with the analysis of target compounds in six river sediment samples. 2.2.3. Optimization of the sample extract clean up Parameters optimized in the clean up procedure were the packing type of the clean up cartridge and elution solvent. Four cartridge packings selected for the testing were silica gel in combination with anhydrous sodium sulphate, Oasis HLB (hydrophilic–lipophilic balance) from Waters (Milford, MA, USA), and C-18 and carbon packings from Supelco (Bellefonte, PA, USA). Commercially available as solid-phase extraction cartridges were Oasis HLB (200 mg/6 ml), Superclean ENVI 18 (C-18, 500 mg/6 ml) and Superclean ENVI Carb (carbon, 500 mg/6 ml). The forth cartridge was self-made by filling the tube with 0.5 g of silica gel and 0.25 g of anhydrous sodium sulphate and using two frits to keep the packing. As elution solvents, methanol and mixtures of methanol/ethyl acetate (1:1) and methanol/hexane (1:1) were tested. The experiments were performed on each cartridge packing using three different elution solvents.

Table 1 Class, chemical structure and molecular weight (Mw ) of selected steroids. Steroid (class)

Chemical structure

Mw

Steroid (class)

Chemical structure

OH

Mw

Steroid (class)

272

␤-Cholestanol (human/animal sterol)

Chemical structure

Mw

OH

OH

Estriol (hormone)

288

17␣-Estradiol (hormone)

HO

HO

O

388 HO

H

OH C

270

Estrone (hormone)

Mestranol (hormone)

CH

310

Desmosterol (plant sterol)

H3CO

HO

384 HO

O

HO

Cholesterol (human/animal sterol)

386

Stigmasterol (plant sterol)

412

HO HO

OH C CH

298

Norethindrone (hormone) O

Cholestanone (human/animal sterol)

386 O

Campesterol (plant sterol)

H

400

HO

OH C

CH

312

Levonorgestrel (hormone) O

Epicoprostanol (human/animal sterol)

388 HO

␤-Sitosterol (plant sterol)

H

414

I. Mati´c et al. / J. Chromatogr. A 1364 (2014) 117–127

268

Equilin (hormone)

HO

OH C CH

17␣Ethinylestradiol (hormone)

296 HO

Coprostanol (human/animal sterol)

388 HO

H

Stigmastanol (plant sterol)

416

HO

H

OH

272

17␤-Estradiol (hormone) HO

␣-Cholestanol (human/animal sterol)

388 HO

H

119

120

I. Mati´c et al. / J. Chromatogr. A 1364 (2014) 117–127

The clean up optimization procedure was as follows: cartridge was preconditioned with 5 ml of the selected elution solvent. Then, 1 ml of the working standard solution was loaded onto packing, followed by elution with 10 ml of the selected solvent. Obtained eluate was evaporated, filtered, and analyzed. After selection of the optimal clean up cartridge (silica gel/anhydrous sodium sulphate), its performance was tested on the real sediment sample extract using two elution solvents which provided the highest recoveries.

2.3. LC-APCI–MS2 analysis Surveyor LC system (Thermo Fisher Scientific, Waltham, MA, USA) was used for chromatographic separation of the analytes on the reverse-phase Zorbax Eclipse® XDB-C18 column, 75 mm × 4.6 mm i.d. and 3.5 ␮m particle size (Agilent Technologies, Santa Clara, CA, USA). In front of the separation column, precolumn was installed, 12.5 mm × 4.6 mm i.d. and 5 ␮m particle size (Agilent Technologies, USA). The mobile phase consisted of methanol and deionized water. Additionally, heptafluorobutyric acid (HFBA) was tested as mobile-phase constituent and ion-pairing reagent at different concentration levels in order to improve chromatographic separation of analytes. An aliquot of 10 ␮l of the final extract was injected into LC system. Mass spectra were obtained by LTQ XL (Thermo Fisher Scientific, USA) linear ion trap mass spectrometer. Both ESI and APCI were tested as ionization techniques. The optimized ESI parameters in both positive and negative ionization mode were source voltage of 4.96 kV and capillary temperature of 290 ◦ C. It was determined that ESI was not efficient in ionization of all eleven sterols, and hormones estriol, estrone, equilin and mestranol, since it could not produce stable ions that could be used for quantification purposes. ESI could be used as the ionization technique for other hormones, such as norethindrone, levonorgestrel, 17␣-ethinylestradiol, 17␣and 17␤-estradiol, but only in the positive mode. Although there are papers on detection of some hormones (17␤-estradiol, estrone, estriol, 17␣-ethinylestradiol) in the ESI negative mode [30,57,65], in this work, under reported conditions, the ES negative ionization mode did not produce stable ions of any of the selected steroids. APCI was found to be efficient for ionization of both hormones and sterols in the positive mode, whereas in the negative mode stable ionization of analytes could not be induced. Fragmentation reaction of the most abundant ion in MS spectra to the most intensive fragment ion was selected for quantification of each analyte in selected reaction monitoring (SRM) mode. Other transitions were used for confirmation purposes. The optimized APCI parameters were capillary temperature of 200 ◦ C and vaporizer temperature of 400 ◦ C.

2.4. Method calibration In the method optimization, external calibration was used with appropriate matrix-matched standards prepared by adding 0.5 ml of the working standard solution to the blank extracts obtained by sample preparation procedure. Peak areas of analytes detected in blank samples were subtracted from both spiked sample and matrix-matched standard. The standard addition method was used for analysis of the real sediment samples. The calibration solutions were prepared by spiking the sediment sample at 50, 250, 1000 and 2000 ng g−1 . The appropriate standard solutions were added to the sediment samples prior to extraction and samples were prepared using optimized extraction procedure.

2.5. Method validation The optimized method performance was tested by spiking the sediment sample at six concentration levels (50, 100, 250, 500, 1000 and 2000 ng g−1 ) and determination of extraction recoveries using matrix-matched standards. The experiment was performed in triplicate, in three successive days, and results were used for determination of the method repeatability, expressed as the relative standard deviation (RSD), as interday precision study. The results were also used for determination of the method linearity by plotting peak areas of analytes in spiked samples vs. determined analyte concentrations. The correlation coefficients (R2 ) were calculated for all selected steroids. In addition, linearity of the method was assessed by calculation of the residual values for each point of the calibration curve. The residual value represents the difference between the actual peak area of analyte in spiked sample and the peak area of the analyte predicted from the linear regression curve, for each of determined analyte concentrations [66]. According to the literature [26,30,33], limits of detection (LODs) and quantification (LOQs) were calculated as minimum detectable concentrations of analytes producing signal to noise ratios of 3 and 10, respectively. Sediment sample spiked at the concentration of 50 ng g−1 was used for this purpose. In order to estimate the matrix effect, i.e. suppression or enhancement of the analyte signal in the matrix solution, the following equation (Eq. (1)) was applied: Matrix effect (%) =

Areamatrix − Areablank × 100 − 100 Areasolvent

(1)

The analyte peak areas of the matrix-matched standard i.e. spiked blank extract (Areamatrix ) reduced by the peak areas of analytes present in the blank (Areablank ), were divided by the analyte peak areas of the standard solution i.e. solution of analytes in methanol (Areasolvent ). From the obtained number (in %), the value of 100 was subtracted in order to determine percentage of signal suppression (negative values) or enhancement (positive values) by matrix components. The matrix effect was evaluated using matrixmatched standard as well as standard solution at the concentration of 100 ng ml−1 . 3. Results and discussion 3.1. Optimization of the sample extraction The optimized extraction parameters were extraction solvent, weight of the sediment and time of ultrasonic extraction. The extraction solvents tested in the method optimization were selected according to the literature [10,17,18,25,26] which indicates that for extraction of hormones and sterols from sediments single extraction solvents or their mixtures are used. The aim was to select two most efficient solvents and then test their mixture for achieving the highest recoveries for all analytes. The results of testing methanol, ethyl acetate, acetone, acetonitrile, hexane and dichloromethane as single extraction solvents are presented in Fig. 1. As distinctly nonpolar solvent, hexane was not appropriate for extraction of hormones (0%, Fig. 1). Also, low recoveries were obtained for extraction of human and animal sterols (43–69%), as well as plant sterols (19–63%), whereas cholestanone and desmosterol were not extracted. Dichloromethane was not efficient for extraction of majority of hormones from sediments (15–53%, Fig. 1). However, high recoveries were obtained for equilin (101%), 17␣ethinylestradiol (78%) and mestranol (83%), as well as for all selected human and animal (95–137%) and plant sterols (90–101%). The highest recoveries for all analytes were obtained using methanol as extraction solvent (80–119%, Fig. 1) with very good

I. Mati´c et al. / J. Chromatogr. A 1364 (2014) 117–127

121

Fig. 1. Recoveries of selected steroids using six different extraction solvents.

RSD values ( 20%) for nine analytes. When acetone was used as extraction solvent, recoveries were good for most of hormones and sterols (79–121%), except in the case of estrone (69%) and cholestanone (57%). RSD values were over 20% for six investigated analytes. Recoveries achieved using acetonitrile were satisfactory for majority of steroids (71–127%), with the exception of estriol (57%) and mestranol (69%), while method repeatability was not good for six hormones and sterols. Obtained results indicated that methanol was the most efficient solvent for extraction of all investigated steroids from sediment sample. Even though optimization was performed in order to select two most efficient solvents and then test their mixture for achieving the highest recoveries, it was finally determined that methanol should be used as single extraction solvent. After the selection of extraction solvent, weight of the sediment sample was optimized with the purpose of achieving greater preconcentration factor. Obtained results are presented in Supplementary Material (Fig. S1a). It was determined that there was no significant difference in obtained recoveries using 1.0 g (85–116%) or 2.0 g (88–117%) of sediment sample. Method repeatability was not good for one or two analytes, when extraction was performed on 1.0 g and 2.0 g of sediment, respectively. It was decided that 2.0 g was the optimal weight of the sediment, as it provided greater preconcentration factor while achieving good recoveries for all selected steroids. In the final experiment, time of ultrasonic extraction was selected with the aim of performing extraction in shorter time. Results obtained for testing of three extraction times (3 × 5 min, 3 × 10 min and 3 × 15 min) are presented in Supplementary Material (Fig. S1b). By comparing recoveries obtained for the extraction time of 3× 15 min (88–117%), with the ones achieved in 3× 10 min (81–120%) and 3× 5 min (74–136%), it was found that although both shorter extraction times provided efficient extraction, more acceptable recoveries were achieved in 3× 10 min. Additionally, method repeatability was better for extraction in 3× 10 min (RSDs < 20% for all analytes), than for shorter time of 3× 5 min (RSD > 20% for one analyte). Therefore, the optimized sample extraction procedure consisted of 3× 10 min extraction

of 2.0 g of sediment sample using methanol as single extraction solvent. 3.2. Optimization of the sample extract clean up Complex nature of the sediment matrix can affect the results of analysis and cause deterioration of the analytical equipment. Therefore, clean up of the sediment sample extracts is required. Results of the clean up experiments performed on four cartridge packings, selected according to the literature [5,18,26,29,31,67], are presented in Supplementary Material (Fig. S2). It was evident that carbon packing (ENVI Carb, Supplementary Material, Fig. S2d) displays great affinity for adsorption of sterols, since they could not be eluted from the packing, regardless of the solvent used. Also, adsorption of some hormones was high, as five of them showed very low recoveries using methanol (4–25%) or methanol/ethyl acetate mixture (3–27%). However, the recoveries were good for the rest of hormones (90–116% using methanol, and 93–110% using methanol/ethyl acetate mixture), as well as for all hormones when methanol/hexane mixture was applied as the elution solvent (81–119%). When ENVI 18 was used as cartridge for extract clean up, obtained recoveries were high (Supplementary Material, Fig. S2c), in the range 82–118% using methanol, 83–119% using methanol/ethyl acetate mixture, and 84–113%, using methanol/hexane mixture for elution. The exceptions were 17␣-ethinylestradiol (136%) with methanol/ethyl acetate as elution solvent, and especially cholestanone exhibiting lower recoveries for all tested solvents (59–69%). High recoveries for all steroids were obtained using Oasis HLB as clean up cartridge (see Supplementary Material, Fig. S2b). They were in the range 86–119% for methanol, 79–127% for methanol/ethyl acetate mixture, and 93–121% for methanol/hexane mixture as elution solvent. The highest recoveries for all selected steroids were achieved using self-made silica gel/anhydrous sodium sulphate cartridge for extract clean up (Supplementary Material, Fig. S2a), with methanol (99–110%), as well as methanol/ethyl acetate mixture (96–122%) as elution solvent. When methanol/hexane mixture was used, recoveries were generally high (88–115%), with the exception of norethindrone (49%) and levonorgestrel (48%). Given the fact that the objective was to achieve extract clean up with no significant loss of selected

122

I. Mati´c et al. / J. Chromatogr. A 1364 (2014) 117–127

Table 2 LC and MS operating parameters for selected steroids in two instrumental methods: LC mobile-phase gradients, MS parameters for data acquisition, selected analytes’ fragmentation reactions for quantification and conformation purposes, and analytes’ chromatographic retention times (RT). Steroid

1st instrumental method

Estriol Estrone Equilin Norethindrone Levonorgestrel Desmosterol Cholesterol Stigmasterol Cholestanone

2nd instrumental method

17␣Ethinylestradiol 17␤-Estradiol 17␣-Estradiol Mestranol Epicoprostanol Coprostanol + ␣cholestanol ␤-Cholestanol Campesterol ␤-Sitosterol Stigmastanol

LC

MS

Time (min)

Flow (ml/min)

CH3 OH RT (min) Time segment (%) (min)

0.00 7.00 7.01 10.50 10.51 15.00 15.01 25.00

1.1 1.1 1.6 1.6 1.1 1.1 1.1 1.1

65 65 100 100 100 100 65 65

1.24 3.37 3.11 3.16 4.72 11.74 12.71 13.28 14.13 8.52

0.00 12.00 12.01 22.00 22.01 32.00

1.1 1.1 1.1 1.1 1.1 1.1

55 55 100 100 55 55

8.08 9.54 14.84 19.12 20.39 21.02 20.19 20.31 20.28

analytes, carbon and C-18 packings were discarded as clean up cartridges. Although Oasis HLB and silica gel/anhydrous sodium sulphate cartridges were acceptable, HLB cartridge was rejected owing to the high price, and silica gel/anhydrous sodium sulphate cartridge was selected as optimal for sediment extract clean up. The clean up performance of selected silica gel/anhydrous sodium sulphate cartridge was tested on the real sediment sample extract using both methanol and methanol/ethyl acetate mixture for elution. Methanol/hexane mixture was not used since it was not efficient in elution of two hormones. The results are shown in Supplementary Material (Fig. S3). When river sediment extract, containing impurities of the sediment matrix, was subjected to clean up procedure, more acceptable recoveries were obtained using methanol (84–118%) than methanol/ethyl acetate mixture (79–149%) as elution solvent. The recoveries were higher than 120% for five sterols when methanol/ethyl acetate mixture was used. Since acceptable recoveries are in the range 70–120%, elevated values could be explained by the complexity of the sediment matrix and its interactions with sterol analytes, as well as by the errors in experimental procedure. It was finally chosen that optimal clean up procedure should include self-made silica gel/anhydrous sodium sulphate cartridge and methanol as elution solvent. 3.3. LC-APCI–MS2 analysis Liquid chromatographic and mass spectrometric operating parameters that were optimized in the instrumental method development are presented in Table 2. The fragmentation reaction of the most abundant, precursor ion to the most intensive fragment ion, with optimized collision energy, was selected for quantification of each analyte. Fragmentation of precursor ion to the second intensive fragment ion was used for confirmation of positive results. The most abundant ion in MS spectra for 75% of steroids (almost all sterols and half of hormones) was dehydrated protonated molecule ([M−H2 O+H]+ ). The protonated molecule ([M+H]+ ) was the precursor ion for the rest of the analytes. It was determined that hormones estriol and estrone, as well as 17␣- and 17␤-estradiol, have identical MS spectra. As a consequence, their

Precursor ion (m/z) Quantification reaction

Collision energy (%)

Conformation reaction

271 [M−H2 O+H]+ 271 [M+H]+ 269 [M+H]+ 299 [M+H]+ II and III (2.5–6.5) 313 [M+H]+ IV (6.5–12.5) 367 [M−H2 O+H]+ IV and V 369 [M−H2 O+H]+ (6.5–16.0) V (12.5–16.0) 395 [M−H2 O+H]+ 387 [M+H]+

271 → 253 271 → 253 269 → 251 299 → 281 313 → 295 367 → 257 369 → 243

20 20 23 23 22 26 24

271 → 197 271 → 197 269 → 211 299 → 263 313 → 277 367 → 161 369 → 287

395 → 297 387 → 369

24 19

395 → 311 387 → 243

279 [M–H2 O+H]+

279 → 133

25

279 → 205

255 [M−H2 O+H]+ 255 [M−H2 O+H]+ 293 [M−H2 O+H]+ 371 [M−H2 O+H]+ 371 [M−H2 O+H]+

255 → 159 255 → 159 293 → 147 371 → 149 371 → 149

22 22 26 24 24

255 → 133 255 → 133 293 → 173 371 → 261 371 → 261

371 [M−H2 O+H]+ 383 [M−H2 O+H]+ 397 [M−H2 O+H]+ 399 [M−H2 O+H]+

371 → 149 383 → 243 397 → 243 399 → 149

24 25 25 24

371 → 261 383 → 257 397 → 257 399 → 163

I (0.0–2.5) I and II (0.0–4.5) II (2.5–4.5)

I (0.0–12.0)

II (12.0–17.0) III (17.0–24.0)

precursor ions (m/z 271 for estriol and estrone, and m/z 255 for 17␣- and 17␤-estradiol) are the same, as well as their quantification and confirmation reactions. Additional difficulty was identical MS spectra of four human/animal sterols: epicoprostanol, coprostanol, ␣- and ␤-cholestanol. Although analytes have identical fragmentation reactions, their retention times can be different and chromatographic separation possible by changing the mobilephase composition. It is well known that sensitivity of MS detector decreases with increasing number of simultaneously recorded fragmentation reactions. Therefore, SRM detection should be separated into time segments acquiring data for the least number of analytes. However, when chromatographic separation of all nine hormones was performed, regardless of the mobile-phase gradient, their retention times were too close and SRM detection could not be separated in sufficient number of time segments to ensure instrument sensitivity. For that reason, it was decided that analysis of twenty selected steroids should be performed using two instrumental methods. Data acquisition for the first and the second method was divided into five and three time segments, respectively (Table 2). In just one segment, data were acquired for a maximum of four analytes. In the beginning of the LC method development it was observed that regardless of the mobile-phase composition hormones have low affinity to C-18 LC column, and elute with short retention times. On the other hand, sterols show great affinity to the column and elute with longer retention times, always after hormones. Evidently, contrary to hormones, it is hard to remove less polar sterols from C-18 chromatographic column. It was finally determined that elution of sterols, within reasonable time, can be achieved only when mobile-phase gradient reaches 100% of organic solvent (methanol or acetonitrile). The optimized mobile-phase gradients of both instrumental methods are shown in Table 2. With these mobile-phase gradients, successful chromatographic separation of analytes that have identical fragmentation reactions (estriol and estrone, as well as 17␣- and 17␤-estradiol) was achieved, as shown in Fig. 2. Namely, during optimization of chromatographic separation it was established that 17␣- and 17␤-estradiol could not be separated if methanol content in the mobile phase was higher than 55%. Although separation of estriol and estrone (retention time

I. Mati´c et al. / J. Chromatogr. A 1364 (2014) 117–127

123

Fig. 2. Mass chromatograms of selected hormones and sterols obtained by: (a) the first instrumental method (the standard solution of 400 ng ml−1 ) and (b) the second instrumental method (the standard solution of 1 ␮g ml−1 ).

124

I. Mati´c et al. / J. Chromatogr. A 1364 (2014) 117–127

Table 3 Method performance parameters (n = 3): recoveries at six concentration levels, method repeatability (relative standard deviations, RSDs), method linearity (correlation coefficients, R2 ), limits of detection (LODs) and quantification (LOQs), and matrix effect (ME). Steroid

50 Estriol Estron Equilin Norethindrone Levonorgestrel 17␣-Ethinylestradiol 17␤-Estradiol 17␣-Estradiol Mestranol Cholesterol Cholestanone Epicoprostanol Coprostanol + ␣-cholestanol ␤-Cholestanol Desmosterol Stigmasterol Campesterol ␤-Sitosterol Stigmastanol

R2

Recovery, % (RSD, %) Spiking level (ng g−1 )

103 (4) 87 (6) 96 (4) 85 (5) 92 (8) 78 (11) 89 (9) 88 (2) 88 (7) 107 (10) 94 (1) 100 (7) 107 (7) 100 (6) 81 (9) 76 (8) 98 (6) 102 (7) 107 (4)

100 99 (21) 80 (6) 78 (2) 83 (7) 86 (6) 90 (6) 85 (1) 86 (1) 86 (5) 92 (28) 101 (2) 90 (27) 109 (10) 111 (6) 92 (6) 100 (5) 104 (9) 104 (26) 98 (7)

250

500

101 (6) 88 (10) 73 (13) 75 (4) 85 (3) 89 (5) 86 (7) 88 (4) 90 (6) 108 (8) 89 (4) 100 (5) 99 (4) 94 (3) 96 (14) 85 (3) 103 (4) 95 (21) 97 (6)

105 (4) 86 (9) 76 (10) 84 (6) 86 (4) 104 (1) 91 (1) 102 (1) 108 (1) 74 (7) 78 (14) 106 (1) 116 (1) 93 (1) 88 (5) 92 (5) 106 (1) 118 (1) 92 (1)

1000 92 (2) 92 (9) 91 (6) 88 (8) 89 (4) 89 (9) 86 (7) 92 (3) 100 (16) 111 (13) 96 (7) 95 (6) 91 (2) 102 (9) 99 (6) 112 (4) 93 (8) 108 (15) 110 (4)

LOD (ng g−1 )

LOQ (ng g−1 )

ME (%)

2000 93 (10) 84 (5) 88 (8) 89 (5) 88 (3) 93 (5) 89 (2) 96 (11) 92 (2) 97 (15) 87 (1) 93 (5) 93 (6) 105 (2) 88 (9) 110 (6) 101 (7) 101 (5) 109 (14)

0.985 9.5 0.993 12.5 0.992 9.5 0.988 0.8 0.987 4.8 0.998 2.2 0.983 1.3 0.981 0.7 0.984 1.4 0.999 1.7 0.994 2.6 0.998 6.4 0.988 5.2 0.999 4.4 0.987 17.7 0.936 1.7 0.981 5.0 0.995 3.8 0.948 8.1

31.6 41.6 26.2 2.5 16.1 7.5 4.2 2.3 4.8 5.7 8.6 21.3 17.2 14.8 59.0 5.5 16.6 12.6 27.1

16 7 5 10 1 −2 3 2 0 2 −27 67 15 −12 −2 4 15 68 29

Table 4 Concentration (± standard deviation, SD) of target compounds detected in sediment samples from the rivers Danube, Tisa, Morava and Sava (n = 2). Steroid

Mestranol Cholesterol Cholestanone Epicoprostanol Coprostanol + ␣-cholestanol ␤-Cholestanol Desmosterol Stigmasterol Campesterol ␤-Sitosterol Stigmastanol a

Concentration ± SD (ng g−1 ) Danube I

Danube II

Tisa

Morava I

Morava II

Sava

NDa 1507 ± 532 899 ± 168 929 ± 200 1873 ± 446 1250 ± 253 524 ± 7 607 ± 67 733 ± 173 1140 ± 240 645 ± 137

10 ± 3 425 ± 40 79 ± 23 95 ± 8 51 ± 4 132 ± 31 175 ± 7 207 ± 7 100 ± 2 872 ± 96 470 ± 15

ND 810 ± 164 1182 ± 95 109 ± 23 112 ± 38 271 ± 51 170 ± 35 262 ± 23 172 ± 25 1359 ± 197 269 ± 45

ND 750 ± 169 291 ± 13 245 ± 43 642 ± 162 344 ± 76 117 ± 5 243 ± 22 277 ± 28 787 ± 126 936 ± 102

ND 1430 ± 256 ND 1230 ± 153 2940 ± 225 760 ± 43 ND 680 ± 74 221 ± 16 680 ± 59 520 ± 71

ND 386 ± 35 114 ± 25 197 ± 46 251 ± 58 495 ± 61 30 ± 8 137 ± 32 97 ± 12 529 ± 39 541 ± 38

ND – not detected.

difference of 0.5 min) could be achieved with 85% methanol content, the optimal mobile-phase gradient was determined to be the one with 65% of methanol producing retention time difference of about 2 min. In the case of four human/animal sterols that also have identical quantification and conformation reactions, a triplet was observed in mass chromatogram. Coprostanol and ␣-cholestanol could not be chromatographically separated and were quantified as a sum. Still, degree of separation achieved for coprostanol/␣cholestanol, epicoprostanol and ␤-cholestanol was sufficient to ensure their indisputable identification (Fig. 2b). It should be also noted that changing of the mobile-phase composition, such as the use of acetonitrile, as well as HFBA at different concentrations, did not influence retention times nor chromatographic separation of analytes. 3.4. Method validation Method performance parameters are presented in Table 3. Recoveries obtained in tested concentration range (50–2000 ng g−1 ) using the optimized method were high (73–118%) for all investigated hormones and sterols. RSD values were generally lower than 20%, with a few exceptions, proving methods’ repeatability. Linearity of the developed method was good, with correlation coefficients in the range 0.936–0.999. Calculated residual values indicate random distribution around the regression curves without systematic trends (see Supplementary

Material, Table S1), confirming linearity of the method. Low LODs (0.8–18 ng g−1 ) and LOQs (2.5–60 ng g−1 ) were achieved for all selected steroids. Estimated matrix effect was generally not pronounced, ranging from–12% for ␤-cholestanol to 16% for estriol (Table 3). Signal enhancement was more frequently observed, for fourteen out of twenty analytes. Significant matrix effect was observed in the case of cholestanone (–27%), stigmastanol (29%), epicoprostanol (67%) and ␤-sitosterol (68%). 3.5. Real sample analysis The developed and optimized method was finally applied in determination of steroid compounds in sediments of the Danube River and its tributaries the Tisa, the Morava and the Sava. The results are shown in Table 4 and can be explained by physicochemical properties of target compounds (Supplementary Material, Table S2). Out of twenty monitored steroids, twelve were detected in river sediments (Fig. 3). Mestranol was the only hormone detected in just one sediment sample (Danube II, Table 4, Fig. 3). Compared to other hormones, its high sorption affinity and preference to adsorb onto sediments can be explained by lower water solubility (0.3 mg l−1 , Supplementary Material, Table S2) and higher log Kow (4.61). To our knowledge, mestranol was not detected in river sediments in any study. Absence of other hormones from sediments is

I. Mati´c et al. / J. Chromatogr. A 1364 (2014) 117–127

125

Fig. 3. Mass chromatograms of detected hormones and sterols in the sediment sample Danube II.

probably due to high water solubility and low log Kow values (shown in Supplementary Material, Table S2), resulting in their increased affinity to the aqueous phase. However, some authors have found trace levels of hormones in river sediments, the most frequently being 17␣-ethinylestradiol [25,27,62,63,68], estrone [27,62,63,68] and 17␤-estradiol [25,63,68]. All investigated human/animal and plant sterols were detected in all analyzed sediment samples (Table 4), with the exception of cholestanone and desmosterol which were not detected in the sample Morava II. Human and animal sterols were present in river

sediments in the range 51–2940 ng g−1 , whereas plant sterols were present in the range 30–1359 ng g−1 . Sterol abundance in sediments can be explained by very low water solubility and high values of log Kow and log Koc (see Supplementary Material, Table S2). Generally, the most abundant human/animal and plant sterols were cholesterol (386–1507 ng g−1 ) and ␤-sitosterol (529–1359 ng g−1 ), respectively. These levels are comparable with concentrations of cholesterol and ␤-sitosterol detected in river sediments from similar locations in Brazil (4–474 ng g−1 and 9–759 ng g−1 ) [34] and USA (260–8290 ng g−1 and 640–13 330 ng g−1 ) [21]. As cholesterol

126

I. Mati´c et al. / J. Chromatogr. A 1364 (2014) 117–127

is the most abundant sterol in human organism, its high levels in environment are indicators of wastewater contamination. Besides terrestrial organic matter, the source of elevated concentrations of ␤-sitosterol can be municipal pollution. Very high concentrations were also noted for the sum of coprostanol and ␣-cholestanol (up to 2940 ng g−1 ). Levels of coprostanol and ␣-cholestanol are similar to the ones detected in Brazil (1–76 ng g−1 and 11–998 ng g−1 ) [34] and USA (20–80 ng g−1 and 60–1940 ng g−1 ) [21]. As for epicoprostanol, concentrations found in this study (up to 1230 ng g−1 ) are higher than those reported in Brazil (2–132 ng g−1 ) [34] and USA (50–290 ng g−1 ) [21]. Contrary to coprostanol which is present in human/animal waste at high concentrations, epicoprostanol is present at trace levels [17]. It can also be formed during sewage degradation or process of microbial digestion of coprostanol. Therefore, high levels of epicoprostanol detected in all investigated sediments indicate strong sewage contamination. 4. Conclusion In this paper, LC–MS method for simultaneous determination of human, animal and plant sterols and hormones was developed and optimized. The optimized sample preparation consisted of ultrasonic extraction (3× 10 min) of 2 g of the sediment sample with methanol as extraction solvent. The extract clean up should be performed using silica gel/anhydrous sodium sulphate cartridge and methanol as elution solvent. Successful chromatographic separation of analytes that have identical fragmentation reactions (estriol and estrone, as well as 17␣- and 17␤-estradiol) was achieved. In the case of four human/animal sterols that also have identical fragmentation reactions, a triplet was observed in mass chromatogram. Coprostanol and ␣-cholestanol could not be chromatographically separated and were quantified as a sum. However, separation achieved for coprostanol/␣-cholestanol, epicoprostanol and ␤-cholestanol was sufficient to ensure their reliable identification. The developed and optimized method provided high recoveries (73–118%), low limits of detection (0.8–18 ng g−1 ) and quantification (2.5–60 ng g−1 ) with the RSDs generally lower than 20%. Method displayed good linearity (R2 > 0.936) in the tested concentration range (50–2000 ng g−1 ). Applicability of the developed method was confirmed by analysis of six river sediments. Human/animal and plant sterols were detected in all investigated samples. Cholesterol and ␤-sitosterol were found at the highest concentrations, up to 1507 ng g−1 and 1359 ng g−1 , respectively. High levels of epicoprostanol detected in all river sediments (up to 1230 ng g−1 ) indicate strong sewage contamination. Mestranol was the only hormone detected in just one sediment sample. Acknowledgements The authors greatly appreciate the financial support from the Ministry of Education, Science and Technological Development of the Republic of Serbia (Project No. 172007). Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.chroma. 2014.08.061. References [1] T.A. Miettinen, T.E. Strandberg, H. Gylling, Noncholesterol sterols and cholesterol lowering by long-term simvastatin treatment in coronary patients: relation to basal serum cholestanol, Arterioscler. Thromb. Vasc. Biol. 20 (2000) 1340–1346.

[2] S.K. Khanal, B. Xie, M.L. Thompson, S. Sung, S.-K. Ong, J. van Leeuwen, Fate, transport, and biodegradation of natural estrogens in the environment and engineered systems, Environ. Sci. Technol. 40 (2006) 6537–6546. [3] S. Combalbert, G. Hernandez-Raquet, Occurrence, fate, and biodegradation of estrogens in sewage and manure, Appl. Microbiol. Biotechnol. 86 (2010) 1671–1692. [4] H. Chang, Y. Wan, S. Wu, Z. Fan, J. Hu, Occurrence of androgens and progestogens in wastewater treatment plants and receiving river waters: comparison to estrogens, Water Res. 45 (2011) 732–740. [5] V. Furtula, J. Liu, P. Chambers, H. Osachoff, C. Kennedy, J. Harkness, Sewage treatment plants efficiencies in removal of sterols and sterol ratios as indicators of fecal contamination sources, Water Air Soil Pollut. 223 (2012) 1017–1031. [6] T. Manickum, W. John, Occurrence, fate and environmental risk assessment of endocrine disrupting compounds at the wastewater treatment works in Pietermaritzburg (South Africa), Sci. Total Environ. 468–469 (468) (2014) 584–590. [7] N. Gottschall, E. Topp, M. Edwards, M. Payne, S. Kleywegt, P. Russell, D.R. Lapen, Hormones, sterols, and fecal indicator bacteria in groundwater, soil, and subsurface drainage following a high single application of municipal biosolids to a field, Chemosphere 91 (2013) 275–286. [8] G.-G. Ying, R.S. Kookana, Y.-J. Ru, Occurrence and fate of hormone steroids in the environment, Environ. Int. 28 (2002) 545–551. [9] R.L. Gomes, E. Avcioglu, M.D. Scrimshaw, J.N. Lester, Steroid estrogen determination in sediment and sewage sludge: a critique of sample preparation and chromatographic/mass spectrometry considerations, incorporating a case study in method development, TrAC: Trends Anal. Chem. 23 (2004) 737–744. [10] Y. Yu, Q. Huang, J. Cui, K. Zhang, C. Tang, X. Peng, Determination of pharmaceuticals, steroid hormones, and endocrine-disrupting personal care products in sewage sludge by ultra-high-performance liquid chromatography–tandem mass spectrometry, Anal. Bioanal. Chem. 399 (2011) 891–902. [11] K.L. Thorpe, R.I. Cummings, T.H. Hutchinson, M. Scholze, G. Brighty, J.P. Sumpter, C.R. Tyler, Relative potencies and combination effects of steroidal estrogens in fish, Environ. Sci. Technol. 37 (2003) 1142–1149. [12] J.P. Nash, D.E. Kime, L.T. Van der Ven, P.W. Wester, F. Brion, G. Maack, P. Stahlschmidt-Allner, C.R. Tyler, Long-term exposure to environmental concentrations of the pharmaceutical ethynylestradiol causes reproductive failure in fish, Environ. Health Perspect. 112 (2004) 1725–1733. [13] S. Jobling, R. Williams, A. Johnson, A. Taylor, M. Gross-Sorokin, M. Nolan, C.R. Tyler, R. van Aerle, E. Santos, G. Brighty, Predicted exposures to steroid estrogens in U.K. rivers correlate with widespread sexual disruption in wild fish populations, Environ. Health Perspect. 114 (2006) 32–39. [14] D.L. MacLatchy, G.J. Van Der Kraak, The phytoestrogen ␤-sitosterol alters the reproductive endocrine status of goldfish, Toxicol. Appl. Pharm. 134 (1995) 305–312. [15] P. Nieminen, A.-M. Mustonen, P. Lindström-Seppä, J. Asikainen, H. MussaloRauhamaa, J.V.K. Kukkonen, Phytosterols act as endocrine and metabolic disruptors in the European polecat (Mustela putorius), Toxicol. Appl. Pharm. 178 (2002) 22–28. [16] O. Savichtcheva, S. Okabe, Alternative indicators of fecal pollution: relations with pathogens and conventional indicators, current methodologies for direct pathogen monitoring and future application perspectives, Water Res. 40 (2006) 2463–2476. [17] S. Froehner, R. Martins, M. Errera, Assessment of fecal sterols in Barigui River sediments in Curitiba, Brazil, Environ. Monit. Assess. 157 (2009) 591–600. [18] S. Froehner, M. Maceno, R. Martins, Sediments as a potential tool for assessment of sewage pollution in Barigüi River, Brazil, Environ. Monit. Assess. 170 (2010) 261–272. [19] D. Sullivan, P. Brooks, N. Tindale, S. Chapman, W. Ahmed, Faecal sterols analysis for the identification of human faecal pollution in a non-sewered catchment, Water Sci. Technol. 61 (2010) 1355–1361. [20] V. Furtula, H. Osachoff, G. Derksen, H. Juahir, A. Colodey, P. Chambers, Inorganic nitrogen, sterols and bacterial source tracking as tools to characterize water quality and possible contamination sources in surface water, Water Res. 46 (2012) 1079–1092. [21] C. Biache, R.P. Philp, The use of sterol distributions combined with compound specific isotope analyses as a tool to identify the origin of fecal contamination in rivers, Water Res. 47 (2013) 1201–1208. [22] C. Marvin, J. Coakley, T. Mayer, M. Brown, L. Thiessen, Application of faecal sterol ratios in sediments and effluents as source tracers, Water Qual. Res. J. Canada 36 (2001) 781–792. [23] C.C. Martins, J.A.F. Braun, B.H. Seyffert, E.C. Machado, G. Fillmann, Anthropogenic organic matter inputs indicated by sedimentary fecal steroids in a large South American tropical estuary (Paranaguá Estuarine System, Brazil), Mar. Pollut. Bull. 60 (2010) 2137–2143. [24] J. Xu, L. Wu, W. Chen, A.C. Chang, Simultaneous determination of pharmaceuticals, endocrine disrupting compounds and hormone in soils by gas chromatography–mass spectrometry, J. Chromatogr. A 1202 (2008) 189–195. [25] J. Martín, J.L. Santos, I. Aparicio, E. Alonso, Multi-residue method for the analysis of pharmaceutical compounds in sewage sludge, compost and sediments by sonication-assisted extraction and LC determination, J. Sep. Sci. 33 (2010) 1760–1766. [26] S. Liu, G.-G. Ying, J.-L. Zhao, F. Chen, B. Yang, L.-J. Zhou, H.-J. Lai, Trace analysis of 28 steroids in surface water, wastewater and sludge samples by rapid resolution liquid chromatography–electrospray ionization tandem mass spectrometry, J. Chromatogr. A 1218 (2011) 1367–1378.

I. Mati´c et al. / J. Chromatogr. A 1364 (2014) 117–127 [27] L. Viglino, M. Prevost, S. Sauve, High throughput analysis of solid-bound endocrine disruptors by LDTD-APCI–MS/MS, J. Environ. Monit. 13 (2011) 583–590. [28] A. Arditsoglou, D. Voutsa, Occurrence and partitioning of endocrine-disrupting compounds in the marine environment of Thermaikos Gulf, Northern Aegean Sea, Greece, Mar. Pollut. Bull. 64 (2012) 2443–2452. [29] A. Hibberd, K. Maskaoui, Z. Zhang, J.L. Zhou, An improved method for the simultaneous analysis of phenolic and steroidal estrogens in water and sediment, Talanta 77 (2009) 1315–1321. [30] T. Vega-Morales, Z. Sosa-Ferrera, J.J. Santana-Rodríguez, Determination of various estradiol mimicking-compounds in sewage sludge by the combination of microwave-assisted extraction and LC–MS/MS, Talanta 85 (2011) 1825– 1834. [31] J. Beck, K.U. Totsche, I. Kögel-Knabner, A rapid and efficient determination of natural estrogens in soils by pressurised liquid extraction and gas chromatography–mass spectrometry, Chemosphere 71 (2008) 954–960. [32] A. Nieto, F. Borrull, E. Pocurull, R.M. Marcé, Determination of natural and synthetic estrogens and their conjugates in sewage sludge by pressurized liquid extraction and liquid chromatography–tandem mass spectrometry, J. Chromatogr. A 1213 (2008) 224–230. [33] Z. Zhang, S.M. Rhind, C. Kerr, M. Osprey, C.E. Kyle, Selective pressurized liquid extraction of estrogenic compounds in soil and analysis by gas chromatography–mass spectrometry, Anal. Chim. Acta 685 (2011) 29–35. [34] C.C. Martins, G. Fillmann, R.C. Montone, Natural and anthropogenic sterols inputs in surface sediments of Patos Lagoon, Brazil, J. Braz. Chem. Soc. 18 (2007) 106–115. [35] J.G. McDonald, B.M. Thompson, E.C. McCrum, D.W. Russell, Extraction and analysis of sterols in biological matrices by high performance liquid chromatography electrospray ionization mass spectrometry, Methods Enzymol. 432 (2007) 145–170. [36] J.G. McDonald, D.D. Smith, A.R. Stiles, D.W. Russell, A comprehensive method for extraction and quantitative analysis of sterols and secosteroids from human plasma, J. Lipid Res. 53 (2012) 1399–1409. [37] A. Honda, K. Yamashita, H. Miyazaki, M. Shirai, T. Ikegami, G. Xu, M. Numazawa, T. Hara, Y. Matsuzaki, Highly sensitive analysis of sterol profiles in human serum by LC-ESI–MS/MS, J. Lipid Res. 49 (2008) 2063–2073. ˜ C. Nerín, Development of a fast sample treatment for [38] I. Mendiara, C. Domeno, the analysis of free and bonded sterols in human serum by LC–MS, J. Sep. Sci. 35 (2012) 3308–3316. [39] A. Meljon, G.L. Watson, Y. Wang, C.H.L. Shackleton, W.J. Griffiths, Analysis by liquid chromatography–mass spectrometry of sterols and oxysterols in brain of the newborn Dhcr73–5/T93M mouse: a model of Smith–Lemli–Opitz syndrome, Biochem. Pharmacol. 86 (2013) 43–55. [40] C. Wang, P.R. Gardinali, Comparison of multiple API techniques for the simultaneous detection of microconstituents in water by on-line SPE–LC–MS/MS, J. Mass Spectrom. 47 (2012) 1255–1268. [41] R. Rozenberg, N.L. Ruibal-Mendieta, G. Petitjean, P. Cani, D.L. Delacroix, N.M. Delzenne, M. Meurens, J. Quetin-Leclercq, J.-L. Habib-Jiwan, Phytosterol analysis and characterization in spelt (Triticum aestivum ssp. spelta L.) and wheat (T. aestivum L.) lipids by LC/APCI–MS, J. Cereal Sci. 38 (2003) 189–197. [42] R.B. Jäpelt, D. Silvestro, J. Smedsgaard, P.E. Jensen, J. Jakobsen, LC–MS/MS with atmospheric pressure chemical ionisation to study the effect of UV treatment on the formation of vitamin D3 and sterols in plants, Food Chem. 129 (2011) 217–225. ˜ [43] B. Canabate-Díaz, A. Segura Carretero, A. Fernández-Gutiérrez, A. Belmonte Vega, A. Garrido Frenich, J.L. Martínez Vidal, J. Duran Martos, Separation and determination of sterols in olive oil by HPLC–MS, Food Chem. 102 (2007) 593–598. [44] A. Segura Carretero, A. Carrasco-Pancorbo, S. Cortacero, A. Gori, L. Cerretani, A. Fernández-Gutiérrez, A simplified method for HPLC–MS analysis of sterols in vegetable oil, Eur. J. Lipid Sci. Technol. 110 (2008) 1142–1149. [45] J.L. Martínez-Vidal, A. Garrido-Frenich, M.A. Escobar-García, R. RomeroGonzález, LC–MS determination of sterols in olive oil, Chromatographia 65 (2007) 695–699. [46] S. Mo, L. Dong, W.J. Hurst, R.B. van Breemen, Quantitative analysis of phytosterols in edible oils using APCI liquid chromatography–tandem mass spectrometry, Lipids 48 (2013) 949–956. [47] W. Zarrouk, A. Carrasco-Pancorbo, M. Zarrouk, A. Segura-Carretero, A. Fernández-Gutiérrez, Multi-component analysis (sterols, tocopherols and triterpenic dialcohols) of the unsaponifiable fraction of vegetable oils by liquid chromatography–atmospheric pressure chemical ionization–ion trap mass spectrometry, Talanta 80 (2009) 924–934. [48] L.-F. Zhang, C.-F. Liu, Y.-B. Meng, Isolation and determination of sterols in rapeseed oil by HPLC–MS, Anal. Lett. 42 (2009) 1650–1661. [49] J.M. Ronan, B. McHugh, A sensitive liquid chromatography/tandem mass spectrometry method for the determination of natural and synthetic steroid

[50]

[51]

[52]

[53]

[54]

[55]

[56]

[57]

[58]

[59]

[60]

[61]

[62]

[63]

[64]

[65]

[66]

[67]

[68]

127

estrogens in seawater and marine biota, with a focus on proposed Water Framework Directive Environmental Quality Standards, Rapid Commun. Mass Spectrom. 27 (2013) 738–746. N. Quignot, M. Tournier, C. Pouech, C. Cren-Olivé, R. Barouki, E. Lemazurier, Quantification of steroids and endocrine disrupting chemicals in rat ovaries by LC–MS/MS for reproductive toxicology assessment, Anal. Bioanal. Chem. 403 (2012) 1629–1640. H. Wang, X. Zhou, Y. Zhang, H. Chen, G. Li, Y. Xu, Q. Zhao, W. Song, H. Jin, L. Ding, Dynamic microwave-assisted extraction coupled with salting-out liquid–liquid extraction for determination of steroid hormones in fish tissues, J. Agric. Food Chem. 60 (2012) 10343–10351. Y. Zhao, J.M. Boyd, M.B. Sawyer, X.-F. Li, Liquid chromatography tandem mass spectrometry determination offree and conjugated estrogens in breast cancer patients before and after exemestane treatment, Anal. Chim. Acta 806 (2014) 172–179. D.T. Harwood, D.J. Handelsman, Development and validation of a sensitive liquid chromatography–tandem mass spectrometry assay to simultaneously measure androgens and estrogens in serum without derivatization, Clin. Chim. Acta 409 (2009) 78–84. B.-H. Zheng, L.-H. An, H. Chang, Y. Liu, Z.-Q. Jiang, Evidence for the presence of sex steroid hormones in Zhikong scallop, Chlamys farreri, J. Steroid Biochem. Mol. Biol. 143 (2014) 199–206. P. Keski-Rahkonen, K. Huhtinen, R. Desai, D.T. Harwood, D.J. Handelsman, M. Poutanen, S. Auriola, LC–MS analysis of estradiol in human serum and endometrial tissue: comparison of electrospray ionization, atmospheric pressure chemical ionization and atmospheric pressure photoionization, J. Mass Spectrom. 48 (2013) 1050–1058. E. Vulliet, L. Wiest, R. Baudot, M.-F. Grenier-Loustalot, Multi-residue analysis of steroids at sub-ng/L levels in surface and ground-waters using liquid chromatography coupled to tandem mass spectrometry, J. Chromatogr. A 1210 (2008) 84–91. N.A. Al-Odaini, M.P. Zakaria, M.I. Yaziz, S. Surif, Multi-residue analytical method for human pharmaceuticals and synthetic hormones in river water and sewage effluents by solid-phase extraction and liquid chromatography–tandem mass spectrometry, J. Chromatogr. A 1217 (2010) 6791–6806. F.J. López-Jiménez, M. Rosales-Marcano, S. Rubio, Restricted access property supramolecular solvents for combined microextraction of endocrine disruptors in sediment and sample cleanup prior to their quantification by liquid chromatography–tandem mass spectrometry, J. Chromatogr. A 1303 (2013) 1–8. D. Matˇejíˇcek, J. Vlˇcek, A. Bureˇsová, P. Pelcova, Online molecularly imprinted solid-phase extraction coupled to liquid chromatography–tandem mass spectrometry for the determination of hormones in water and sediment samples, J. Sep. Sci. 36 (2013) 1509–1515. J. Koyama, A. Kitoh, M. Nakai, K. Kohno, H. Tanaka, S. Uno, Relative contribution of endocrine-disrupting chemicals to the estrogenic potency of marine sediments of Osaka Bay, Japan, Water Air Soil Pollut. 224 (2013) 1570. P. Labadie, E.M. Hill, Analysis of estrogens in river sediments by liquid chromatography–electrospray ionisation mass spectrometry. Comparison of tandem mass spectrometry and time-of-flight mass spectrometry, J. Chromatogr. A 1141 (2007) 174–181. M.J. Lopez de Alda, A. Gil, E. Paz, D. Barcelo, Occurrence and analysis of estrogens and progestogens in river sediments by liquid chromatography–electrospray–mass spectrometry, Analyst 127 (2002) 1299–1304. ˇ Combined isolation and purification D. Matˇejíˇcek, P. Houserová, V. Kubán, procedures prior to the high-performance liquid chromatographic–ion-trap tandem mass spectrometric determination of estrogens and their conjugates in river sediments, J. Chromatogr. A 1171 (2007) 80–89. M. Petrovic, S. Tavazzi, D. Barcelo, Column-switching system with restricted access pre-column packing for an integrated sample cleanup and liquid chromatographic–mass spectrometric analysis of alkylphenolic compounds and steroid sex hormones in sediment, J. Chromatogr. A 971 (2002) 37–45. M. Gorga, S. Insa, M. Petrovic, D. Barceló, Analysis of endocrine disrupters and related compounds in sediments and sewage sludge using on-line turbulent flow chromatography–liquid chromatography–tandem mass spectrometry, J. Chromatogr. A 1352 (2014) 29–37. I. Taverniers, M. De Loose, E. Van Bockstaele, Trends in quality in the analytical laboratory. II. Analytical method validation and quality assurance, TrAC: Trends Anal. Chem. 23 (2004) 535–552. C.H. Vane, A.W. Kim, S. McGowan, M.J. Leng, T.H.E. Heaton, C.P. Kendrick, P. Coombs, H. Yang, G.E.A. Swann, Sedimentary records of sewage pollution using faecal markers in contrasting peri-urban shallow lakes, Sci. Total Environ. 409 (2010) 345–356. T.A. Ternes, H. Andersen, D. Gilberg, M. Bonerz, Determination of estrogens in sludge and sediments by liquid extraction and GC/MS/MS, Anal. Chem. 74 (2002) 3498–3504.