966 resultados para solid-phase extraction


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The volatile composition from four types of multifloral Portuguese (produced in Madeira Island) honeys was investigated by a suitable analytical procedure based on dynamic headspace solid-phase microextraction (HS-SPME) followed by thermal desorption gas chromatography–quadrupole mass spectrometry detection (GC–qMS). The performance of five commercially available SPME fibres: 100 μm polydimethylsiloxane, PDMS; 85 μm polyacrylate, PA; 50/30 μm divinylbenzene/carboxen on polydimethylsiloxane, DVB/CAR/PDMS (StableFlex); 75 μm carboxen/polydimethylsiloxane, CAR/PDMS, and 65 μm carbowax/divinylbenzene, CW/DVB; were evaluated and compared. The highest amounts of extract, in terms of the maximum signal obtained for the total volatile composition, were obtained with a DVB/CAR/PDMS coating fibre at 60 °C during an extraction time of 40 min with a constant stirring at 750 rpm, after saturating the sample with NaCl (30%). Using this methodology more than one hundred volatile compounds, belonging to different biosynthetic pathways were identified, including monoterpenols, C13-norisoprenoids, sesquiterpenes, higher alcohols, ethyl esters and fatty acids. The main components of the HS-SPME samples of honey were in average ethanol, hotrienol, benzeneacetaldehyde, furfural, trans-linalool oxide and 1,3-dihydroxy-2-propanone.

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The analysis of volatile compounds in Funchal, Madeira, Mateus and Perry Vidal cultivars of Annona cherimola Mill. (cherimoya) was carried out by headspace solid-phase microextraction (HS-SPME) combined with gas chromatography–quadrupole mass spectrometry detection (GC–qMSD). HS-SPME technique was optimized in terms of fibre selection, extraction time, extraction temperature and sample amount to reach the best extraction efficiency. The best result was obtained with 2 g of sample, using a divinylbenzene/carboxen/polydimethylsiloxane (DVB/CAR/PDMS) fibre for 30 min at 30 °C under constant magnetic stirring (800 rpm). After optimization of the extraction methodology, all the cherimoya samples were analysed with the best conditions that allowed to identify about 60 volatile compounds. The major compounds identified in the four cherimoya cultivars were methyl butanoate, butyl butanoate, 3-methylbutyl butanoate, 3-methylbutyl 3-methylbutanoate and 5-hydroxymethyl-2-furfural. These compounds represent 69.08 ± 5.22%, 56.56 ± 15.36%, 56.69 ± 9.28% and 71.82 ± 1.29% of the total volatiles for Funchal, Madeira, Mateus and Perry Vidal cultivars, respectively. This study showed that each cherimoya cultivars have 40 common compounds, corresponding to different chemical families, namely terpenes, esters, alcohols, fatty acids and carbonyl compounds and using PCA, the volatile composition in terms of average peak areas, provided a suitable tool to differentiate among the cherimoya cultivars.

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In the present study, a simple and sensitive methodology based on dynamic headspace solid-phase microextraction (HS-SPME) followed by thermal desorption gas chromatography with quadrupole mass detection (GC–qMSD), was developed and optimized for the determination of volatile (VOCs) and semi-volatile (SVOCs) compounds from different alcoholic beverages: wine, beer and whisky. Key experimental factors influencing the equilibrium of the VOCs and SVOCs between the sample and the SPME fibre, as the type of fibre coating, extraction time and temperature, sample stirring and ionic strength, were optimized. The performance of five commercially available SPME fibres was evaluated and compared, namely polydimethylsiloxane (PDMS, 100 μm); polyacrylate (PA, 85 μm); polydimethylsiloxane/divinylbenzene (PDMS/DVB, 65 μm); carboxen™/polydimethylsiloxane (CAR/PDMS, 75 μm) and the divinylbenzene/carboxen on polydimethylsiloxane (DVB/CAR/PDMS, 50/30 μm) (StableFlex). An objective comparison among different alcoholic beverages has been established in terms of qualitative and semi-quantitative differences on volatile and semi-volatile compounds. These compounds belong to several chemical families, including higher alcohols, ethyl esters, fatty acids, higher alcohol acetates, isoamyl esters, carbonyl compounds, furanic compounds, terpenoids, C13-norisoprenoids and volatile phenols. The optimized extraction conditions and GC–qMSD, lead to the successful identification of 44 compounds in white wines, 64 in beers and 104 in whiskys. Some of these compounds were found in all of the examined beverage samples. The main components of the HS-SPME found in white wines were ethyl octanoate (46.9%), ethyl decanoate (30.3%), ethyl 9-decenoate (10.7%), ethyl hexanoate (3.1%), and isoamyl octanoate (2.7%). As for beers, the major compounds were isoamyl alcohol (11.5%), ethyl octanoate (9.1%), isoamyl acetate (8.2%), 2-ethyl-1-hexanol (5.9%), and octanoic acid (5.5%). Ethyl decanoate (58.0%), ethyl octanoate (15.1%), ethyl dodecanoate (13.9%) followed by 3-methyl-1-butanol (1.8%) and isoamyl acetate (1.4%) were found to be the major VOCs in whisky samples.

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A suitable analytical procedure based on static headspace solid-phase microextraction (SPME) followed by thermal desorption gas chromatography–ion trap mass spectrometry detection (GC–ITDMS), was developed and applied for the qualitative and semi-quantitative analysis of volatile components of Portuguese Terras Madeirenses red wines. The headspace SPME method was optimised in terms of fibre coating, extraction time, and extraction temperature. The performance of three commercially available SPME fibres, viz. 100 lm polydimethylsiloxane; 85 lm polyacrylate, PA; and 50/30 lm divinylbenzene/carboxen on polydimethylsiloxane, was evaluated and compared. The highest amounts extracted, in terms of the maximum signal recorded for the total volatile composition, were obtained with a PA coating fibre at 308C during an extraction time of 60 min with a constant stirring at 750 rpm, after saturation of the sample with NaCl (30%, w/v). More than sixty volatile compounds, belonging to different biosynthetic pathways, have been identified, including fatty acid ethyl esters, higher alcohols, fatty acids, higher alcohol acetates, isoamyl esters, carbonyl compounds, and monoterpenols/C13-norisoprenoids.

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An analytical methodology based on headspace solid phase microextraction (HS-SPME) combined with comprehensive two-dimensional gas chromatography—time-of-flight mass spectrometry (GC × GC–ToFMS) was developed for the identification and quantification of the toxic contaminant ethyl carbamate (EC) directly in fortified wines. The method performance was assessed for dry/medium dry and sweet/medium sweet model wines, and for quantification purposes, calibration plots were performed for both matrices using the ion extraction chromatography (IEC) mode (m/z 62). Good linearity was obtained with a regression coefficient (r2) higher than 0.981. A good precision was attained (R.S.D. <20%) and low detection limits (LOD) were achieved for dry (4.31 μg/L) and sweet (2.75 μg/L) model wines. The quantification limits (LOQ) and recovery for dry wines were 14.38 μg/L and 88.6%, whereas for sweet wines were 9.16 μg/L and 99.4%, respectively. The higher performance was attainted with sweet model wine, as increasing of glucose content improves the volatile compound in headspace, and a better linearity, recovery and precision were achieved. The analytical methodology was applied to analyse 20 fortified Madeira wines including different types of wine (dry, medium dry, sweet, and medium sweet) obtained from several harvests in Madeira Island (Portugal). The EC levels ranged from 54.1 μg/L (medium dry) to 162.5 μg/L (medium sweet).

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Allergicasthmarepresentsanimportantpublichealthissuewithsignificantgrowthovertheyears,especially in the paediatric population. Exhaled breath is a non-invasive, easily performed and rapid method forobtainingsamplesfromthelowerrespiratorytract.Inthepresentmanuscript,themetabolicvolatile profiles of allergic asthma and control children were evaluated by headspace solid-phase microextraction combined with gas chromatography–quadrupole mass spectrometry (HS-SPME/GC–qMS). The lack ofstudiesinbreathofallergicasthmaticchildrenbyHS-SPMEledtothedevelopmentofanexperimental design to optimize SPME parameters. To fulfil this objective, three important HS-SPME experimental parameters that influence the extraction efficiency, namely fibre coating, temperature and time extractions were considered. The selected conditions that promoted higher extraction efficiency corresponding to the higher GC peak areas and number of compounds were: DVB/CAR/PDMS coating fibre, 22◦C and 60min as the extraction temperature and time, respectively. The suitability of two containers, 1L Tedlar® bags and BIOVOC®, for breath collection and intra-individual variability were also investigated. The developed methodology was then applied to the analysis of children exhaled breath with allergicasthma(35),fromwhich13hadalsoallergicrhinitis,andhealthycontrolchildren(15),allowing to identify 44 volatiles distributed over the chemical families of alkanes (linear and ramified) ketones, aromatic hydrocarbons, aldehydes, acids, among others. Multivariate studies were performed by Partial LeastSquares–DiscriminantAnalysis(PLS–DA)usingasetof28selectedmetabolitesanddiscrimination between allergic asthma and control children was attained with a classification rate of 88%. The allergic asthma paediatric population was characterized mainly by the compounds linked to oxidative stress, such as alkanes and aldehydes. Furthermore, more detailed information was achieved combining the volatile metabolic data, suggested by PLS–DA model, and clinical data.

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BACKGROUND: Non-invasive diagnostic strategies aimed at identifying biomarkers of cancer are of great interest for early cancer detection. Urine is potentially a rich source of volatile organic metabolites (VOMs) that can be used as potential cancer biomarkers. Our aim was to develop a generally reliable, rapid, sensitive, and robust analytical method for screening large numbers of urine samples, resulting in a broad spectrum of native VOMs, as a tool to evaluate the potential of these metabolites in the early diagnosis of cancer. METHODS: To investigate urinary volatile metabolites as potential cancer biomarkers, urine samples from 33 cancer patients (oncological group: 14 leukaemia, 12 colorectal and 7 lymphoma) and 21 healthy (control group, cancer-free) individuals were qualitatively and quantitatively analysed. Dynamic solid-phase microextraction in headspace mode (dHS-SPME) using a carboxenpolydimethylsiloxane (CAR/PDMS) sorbent in combination with GC-qMS-based metabolomics was applied to isolate and identify the volatile metabolites. This method provides a potential non-invasive method for early cancer diagnosis as a first approach. To fulfil this objective, three important dHS-SPME experimental parameters that influence extraction efficiency (fibre coating, extraction time and temperature of sampling) were optimised using a univariate optimisation design. The highest extraction efficiency was obtained when sampling was performed at 501C for 60min using samples with high ionic strengths (17% sodium chloride, wv 1) and under agitation. RESULTS: A total of 82 volatile metabolites belonging to distinct chemical classes were identified in the control and oncological groups. Benzene derivatives, terpenoids and phenols were the most common classes for the oncological group, whereas ketones and sulphur compounds were the main classes that were isolated from the urine headspace of healthy subjects. The results demonstrate that compound concentrations were dramatically different between cancer patients and healthy volunteers. The positive rates of 16 patients among the 82 identified were found to be statistically different (Po0.05). A significant increase in the peak area of 2-methyl3-phenyl-2-propenal, p-cymene, anisole, 4-methyl-phenol and 1,2-dihydro-1,1,6-trimethyl-naphthalene in cancer patients was observed. On average, statistically significant lower abundances of dimethyl disulphide were found in cancer patients. CONCLUSIONS: Gas chromatographic peak areas were submitted to multivariate analysis (principal component analysis and supervised linear discriminant analysis) to visualise clusters within cases and to detect the volatile metabolites that are able to differentiate cancer patients from healthy individuals. Very good discrimination within cancer groups and between cancer and control groups was achieved.

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A headspace solid-phase microextraction (HS-SPME) procedure based on five commercialised fibres (85 μm polyacrylate – PA, 100 μm polydimethylsiloxane – PDMS, 65 μm polydimethylsiloxane/divinylbenzene – PDMS/DVB, 70 μm carbowax/divinylbenzene – CW/DVB and 85 μm carboxen/polydimethylsiloxane – CAR/PDMS) is presented for the characterization of the volatile metabolite profile of four selected Madeira island fruit species, lemon (Citrus limon), kiwi (Actinidia deliciosa), papaya (Carica papaya L.) and Chickasaw plum (Prunus angustifolia). The isolation of metabolites was followed by thermal desorption gas chromatography–quadrupole mass spectrometry (GC–qMS) methodology. The performance of the target fibres was evaluated and compared. The SPME fibre coated with CW/DVB afforded the highest extraction efficiency in kiwi and papaya pulps, while in lemon and plum the same was achieved with PMDS/DVB fibre. This procedure allowed for the identification of 80 compounds, 41 in kiwi, 24 in plums, 23 in papaya and 20 in lemon. Considering the best extraction conditions, the most abundant volatiles identified in kiwi were the intense aldehydes and ethyl esters such as (E)-2-hexenal and ethyl butyrate, while in Chicasaw plum predominate 2-hexenal, 2-methyl-4-pentenal, hexanal, (Z)-3-hexenol and cyclohexylene oxide. The major compounds identified in the papaya pulp were benzyl isothiocyanate, linalool oxide, furfural, hydroxypropanone, linalool and acetic acid. Finally, lemon was shown to be the most divergent of the four fruits, being its aroma profile composed almost exclusively by terpens, namely limonene, γ-terpinene, o-cymene and α-terpinolene. Thirty two volatiles were identified for the first time in the fruit or close related species analysed and 14 volatiles are reported as novel volatile metabolites in fruits. This includes 5 new compounds in kiwi (2-cyclohexene-1,4-dione, furyl hydroxymethyl ketone, 4-hydroxydihydro-2(3H)-furanone, 5-acetoxymethyl-2-furaldehyde and ethanedioic acid), 4 in plum (4-hydroxydihydro-2(3H)-furanone, 5-methyl-2-pyrazinylmethanol, cyclohexylene oxide and 1-methylcyclohexene), 4 in papaya (octaethyleneglycol, 1,2-cyclopentanedione, 3-methyl-1,2-cyclopentanedione and 2-furyl methyl ketone) and 2 in lemon (geranyl farnesate and safranal). It is noteworthy that among the 15 volatile metabolites identified in papaya, 3-methyl-1,2-cyclopentanedione was previously described as a novel PPARγ (peroxisome proliferator-activated receptor γ) agonist, having a potential to minimize inflammation.

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In this study the effect of the cultivar on the volatile profile of five different banana varieties was evaluated and determined by dynamic headspace solid-phase microextraction (dHS-SPME) combined with one-dimensional gas chromatography–mass spectrometry (1D-GC–qMS). This approach allowed the definition of a volatile metabolite profile to each banana variety and can be used as pertinent criteria of differentiation. The investigated banana varieties (Dwarf Cavendish, Prata, Maçã, Ouro and Platano) have certified botanical origin and belong to the Musaceae family, the most common genomic group cultivated in Madeira Island (Portugal). The influence of dHS-SPME experimental factors, namely, fibre coating, extraction time and extraction temperature, on the equilibrium headspace analysis was investigated and optimised using univariate optimisation design. A total of 68 volatile organic metabolites (VOMs) were tentatively identified and used to profile the volatile composition in different banana cultivars, thus emphasising the sensitivity and applicability of SPME for establishment of the volatile metabolomic pattern of plant secondary metabolites. Ethyl esters were found to comprise the largest chemical class accounting 80.9%, 86.5%, 51.2%, 90.1% and 6.1% of total peak area for Dwarf Cavendish, Prata, Ouro, Maçã and Platano volatile fraction, respectively. Gas chromatographic peak areas were submitted to multivariate statistical analysis (principal component and stepwise linear discriminant analysis) in order to visualise clusters within samples and to detect the volatile metabolites able to differentiate banana cultivars. The application of the multivariate analysis on the VOMs data set resulted in predictive abilities of 90% as evaluated by the cross-validation procedure.

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Hop(HumuluslupulusL.,Cannabaceaefamily)isprizedforitsessentialoilcontents,usedin beer production and, more recently, in biological and pharmacological applications. In this work,a methodinvolvingheadspace solid-phase microextractionand gas chromatography– mass spectrometry was developed and optimized to establish the terpenoid (monoterpenes and sesquiterpenes) metabolomic pattern of hop-essential oil derived from Saaz variety as a mean to explore this matrix as a powerful biological source for newer, more selective, biodegradable and naturally produced antimicrobial and antioxidant compounds. Different parameters affecting terpenoid metabolites extraction by headspace solid-phase microextraction were considered and optimized: type of fiber coatings, extraction temperature, extraction time, ionic strength, and sample agitation. In the optimized method, analytes were extracted for 30 min at 40 C in the sample headspace with a 50/30 m divinylbenzene/carboxen/polydimethylsiloxane coating fiber. The methodology allowed the identification of a total of 27 terpenoid metabolites, representing 92.5% of the total Saaz hop-essential oil volatile terpenoid composition. The headspace composition was dominated by monoterpenes (56.1%, 13 compounds), sesquiterpenes (34.9%, 10), oxygenated monoterpenes (1.41%, 3), and hemiterpenes (0.04%, 1) some of which can probably contribute to the hop of Saaz variety aroma. Mass spectrometry analysis revealed that the main metabolites are the monoterpene -myrcene (53.0±1.1% of the total volatile fraction), and the cyclic sesquiterpenes, -humulene (16.6 ± 0.8%), and -caryophyllene (14.7 ± 0.4%), which together represent about 80% of the total volatile fraction from the hop-essential oil. Thesefindingssuggestthatthismatrixcanbeexploredasapowerfulbiosourceofterpenoid metabolites.

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The volatile composition of different apple varieties of Malus domestica Borkh. species from different geographic regions at Madeira Islands, namely Ponta do Pargo (PP), Porto Santo (PS), and Santo da Serra (SS) was established by headspace solid-phase microextraction (HS-SPME) procedure followed by GC-MS (GC-qMS) analysis. Significant parameters affecting sorption process such as fiber coating, extraction temperature,extractiontime,sampleamount,dilutionfactor,ionicstrength,anddesorption time,wereoptimizedanddiscussed.TheSPMEfibercoatedwith50/30 lmdivinylbenzene/carboxen/PDMS (DVB/CAR/PDMS) afforded highest extraction efficiency of volatile compounds, providing the best sensitivity for the target volatiles, particularly whenthesampleswereextractedat508Cfor30 minwithconstantmagneticstirring. A qualitative and semi-quantitative analysis between the investigated apple species has been established. It was possible to identify about 100 of volatile compounds amongpulp(46,45,and39),peel(64,60,and64),andentirefruit(65,43,and50)inPP, PS,andSSapples,respectively.Ethylesters,terpenes,andhigheralcoholswerefound tobethemostrepresentativevolatiles. a-Farnesene,hexan-1-olandhexyl2-methylbutyratewerethecompoundsfoundinthevolatileprofileofstudiedappleswiththelargestGCarea,representing,onaverage,24.71,14.06,and10.80%ofthetotalvolatilefractionfromPP,PS,andSSapples.InPPentireapple,themostabundantcompoundsidentified were a-farnesene (30.49%), the unknown compound m/z (69, 101, 157) (21.82%) andhexylacetate(6.57%).RegardingPSentireapplethemajorcompoundswere a-farnesene(16.87%),estragole(15.43%),hexan-1-ol(10.94),andE-2-hexenal(10.67).a-Farnesene(30.3%),hexan-1-ol(18.90%),2-methylbutanoicacid(4.7%),andpentan-1-ol(4.6%) werealsofoundasSSentireapplevolatilespresentinahigherrelativecontent.Principal component analysis (PCA) of the results clustered the apples into three groups according to geographic origin. Linear discriminant analysis (LDA) was performed in order to detect the volatile compounds able to differentiate the three kinds of apples investigated. The most important contributions to the differentiation of the PP, PS, and SS apples were ethyl hexanoate, hexyl 2-methylbutyrate, E,E-2,4-heptadienal, pethylstyrene,andE-2-hexenal.

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Dynamic headspace solid-phase microextraction (HS-SPME) followed by thermal desorption gas chromatography-quadrupole mass spectrometry analysis (GC-qMS), was used to investigate the aroma profile of different species of passion fruit samples. The performance of five commercially available SPME fibres: 65 μm polydimethylsiloxane/divinylbenzene, PDMS/DVB; 100 μm polydimethylsiloxane, PDMS; 85 μm polyacrylate, PA; 50/30 μm divinylbenzene/carboxen on polydimethylsiloxane, DVB/CAR/PDMS (StableFlex); and 75 μm carboxen/polydimethylsiloxane, CAR/PDMS; was evaluated and compared. Several extraction times and temperature conditions were also tested to achieve optimum recovery. The SPME fibre coated with 65 μm PDMS/DVB afforded the highest extraction efficiency, when the samples were extracted at 50 °C for 40 min with a constant stirring velocity of 750 rpm, after saturating the sample with NaCl (17%, w/v — 0.2 g). A comparison among different passion fruit species has been established in terms of qualitative and semi-quantitative differences in volatile composition. By using the optimal extraction conditions and GC-qMS it was possible to tentatively identify seventy one different compounds in Passiflora species: 51 volatiles in Passiflora edulis Sims (purple passion fruit), 24 in P. edulis Sims f. flavicarpa (yellow passion fruit) and 21 compounds in Passiflora mollissima (banana passion fruit). It was found that the ethyl esters comprise the largest class of the passion fruit volatiles, including 82.8% in P. edulis variety, 77.4% in P. edulis Sims f. flavicarpa variety and 39.9% in P. mollissima. The semi-quantitative results were then submitted to principal component analysis (PCA) in order to establish relationships between the compounds and the different passion fruit species under investigation.

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The volatiles (VOCs) and semi-volatile organic compounds (SVOCs) responsible for aroma are mainly present in skin of grape varieties. Thus, the present investigation is directed towards the optimisation of a solvent free methodology based on headspace-solid-phase microextraction (HS-SPME) combined with gas chromatography–quadrupole mass spectrometry (GC–qMS) in order to establish the global volatile composition in pulp and skin of Bual and Bastardo Vitis vinifera L. varieties. A deep study on the extraction-influencing parameters was performed, and the best results, expressed as GC peak area, number of identified compounds and reproducibility, were obtained using 4 g of sample homogenised in 5 mL of ultra-pure Milli-Q water in a 20 mL glass vial with addition of 2 g of sodium chloride (NaCl). A divinylbenzene/carboxen/polydimethylsiloxane fibre was selected for extraction at 60 °C for 45 min under continuous stirring at 800 rpm. More than 100 VOCs and SVOCs, including 27 monoterpenoids, 27 sesquiterpenoids, 21 carbonyl compounds, 17 alcohols (from which 2 aromatics), 10 C13 norisoprenoids and 5 acids were identified. The results showed that, for both grape varieties, the levels and number of volatiles in skin were considerably higher than those observed in pulp. According to the data obtained by principal component analysis (PCA), the establishment of the global volatile signature of grape and the relationship between different part of grapes—pulp and skin, may be an useful tool to winemaker decision to define the vinification procedures that improves the organoleptic characteristics of the corresponding wines and consequently contributed to an economic valorization and consumer acceptance.

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Direct immersion SPME-GC-MS-MS was used for the analysis of steroids in water at part-per-trillion(ppt) and lower concentrations. The method was validated and extended to real sample analysis. The method were linear from 0.01 to 5 ng/ml with precision less than 10% relative standard deviation for a steroid mixture at 1 ng/ml. Limit of quantitation and limit of detection was found to be 200- 1200 pg/L and 30-200 pg/L respectively and recoveries ranged from 88-103 %. To understand the extraction efficiency of the fiber, a depletion study was performed. The fiber/ sample partition coefficients for the steroids were determined to be 1.0 x 104 to 1.5 x 104 . The extraction was performed without derivatization or the use of an internal standard. SPMEGC-MS-MS effectively demonstrated ultra-trace level detection of steroids in water.

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Polythiophene (PTh) phase electropolymerized on the stainless steel wire was evaluated as solid-phase microextraction (SPME), and analysis by liquid chromatography with spectrophotometric detection (LC-UV) for determination of new-generation antidepressants, selective serotonin reuptake inhibitors (SSRIs) (citalopram, paroxetine, fluoxetine and sertraline), in plasma samples. The influence of electropolymerization variables (scan rate, potential range and scan cycles) was evaluated on SPME performance. The SPME variables (extraction time, temperature, matrix pH, ionic strength and desorption procedure), as well as the influence of plasma proteins on sorption mechanisms were also evaluated. The SPME/LC-UV method developed for determination of antidepressants in plasma sample presented a linear range between the limit of quantification (LOQ, 200-250 ng mL(-1)) to 4000 ng mL(-1), and interday precision with coefficient of variation (CV) ranged from 11 to 15%. The proposed method can be a useful tool for the determination of antidepressants in human plasma samples in urgent toxicological analysis after the accidental or suicidal intake of higher doses of medications.