Issues pertaining to the analysis of buprenorphine and its metabolites by gas chromatography–mass spectrometry

“Substitution therapy” and the use of buprenorphine (B) as an agent for treating heroin addiction continue to gain acceptance and have recently been implemented in Taiwan. Mature and widely utilized gas chromatography–mass spectrometry (GC–MS) technology can complement the low cost and highly sensitive immunoassay (IA) approach to facilitate the implementation of analytical tasks supporting compliance monitoring and pharmacokinetic/pharmacogenetic studies. Issues critical to GC–MS analysis of B and norbuprenorphine (NB) (free and as glucuronides), including extraction, hydrolysis, derivatization, and quantitation approaches were studied, followed by comparing the resulting data against those derived from IA and two types of liquid chromatography–tandem mass spectrometry (LC–MS/MS) methods. Commercial solid-phase extraction devices, highly effective for recovering all metabolites, may not be suitable for the analysis of free B and NB; acetyl-derivatization products exhibit the most favorable chromatographic, ion intensity, and cross-contribution characteristics for GC–MS analysis. Evaluation of IA, GC–MS, and LC–MS/MS data obtained in three laboratories has proven the 2-aliquot GC–MS protocol effective for the determination of free B and NB and their glucuronides.     

Reconstruction and analysis of correlation networks based on GC–MS metabolomics data for young hypertensive men

The awareness, treatment, and control rates of hypertension for young adults are much lower than average. It is urgently needed to explore the variances of metabolic profiles for early diagnosis and treatment of hypertension. In current study, we applied a GC–MS based metabolomics platform coupled with a network approach to analyze plasma samples from young hypertensive men and age-matched healthy controls. Our findings confirmed distinct metabolic footprints of young hypertensive men. The significantly altered metabolites between two groups were enriched for the biological module of amino acids biosynthesis. The correlations of GC–MS metabolomics data were then visualized as networks based on Pearson correlation coefficient (threshold = 0.6). The plasma metabolites identified by GC–MS and the significantly altered metabolites (P < 0.05) between patients and controls were respectively included as nodes of a network. Statistical and topological characteristics of the networks were studied in detail. A few amino acids, glycine, lysine, and cystine, were screened as hub metabolites with higher values of degree (k), and also obtained highest scores of three centrality indices. The short average path lengths and high clustering coefficients of the networks revealed a small-world property, indicating that variances of these amino acids have a major impact on the metabolic change in young hypertensive men. These results suggested that disorders of amino acid metabolism might play an important role in predisposing young men to developing hypertension. The combination of metabolomics and network methods would provide another perspective on expounding the molecular mechanism underlying complex diseases.     

Morphine-induced conditioned place preference in mice: Metabolomic profiling of brain tissue to find “molecular switch” of drug abuse by gas chromatography/mass spectrometry

Conditioned place preference (CPP) is a widely used model to explore the mechanism of context-dependent learning. In this work, we developed a GC–MS method to investigate the metabolites in mice brain which was used to study the mechanism of context-dependent learning associated with rewarding effect of morphine. Metabolites were extracted from brain tissues and derivatized followed by analysis by gas chromatography/mass spectrometry (GC–MS). In total, 69 peaks were identified as known compounds. By a Wilcoxon ran sum test with p value ≤0.05, 21 metabolites were selected and considered as the potential biomarkers of morphine in mice brain. Using principal component analysis (PCA) and receiver-operator characteristic (ROC) curves, a model was constructed with a combination of these 21 metabolic markers. Multivariate statistics of the model yielded separation between the two groups with an area under the curve value of 0.947. Some metabolites were further discussed in detail about their pathway. Results showed that our technique can be successfully applied to profile for biomarkers and in understanding molecular mechanisms of drug abuse.     

High-throughput approach for analysis of multicomponent gas chromatographic–mass spectrometric signals

Hyphenated techniques such as gas chromatography–mass spectrometry (GC–MS) or high-performance liquid chromatography–mass spectrometry (LC–MS) produce a large amount of data in a form of two-way data matrix. It has been a great challenge to furthest extract the useful information from the data. In this work, a chemometric approach based on a modification of adaptive immune algorithm (AIA) was proposed for a high-throughput analysis of the multicomponent overlapping GC–MS signals. With the proposed method, the chromatographic profile of each component in an overlapping signal can be extracted independently and sequentially along the retention time. In order to show the efficiency of the method, a stimulated GC–MS data of six components with background and an experimental GC–MS data of 40 pesticides were investigated. It was found that the multicomponent overlapping GC–MS signals could be fast and accurately resolved. Furthermore, the quantitative property of the extracted information was also investigated. The correlation coefficients (r) between the peak area and the added volumes of the sample are in the range 0.9658–0.9953.     

Determination of cholesterol and triglycerides in serum lipoproteins using flow field-flow fractionation coupled to gas chromatography-mass spectrometry

Asymmetric flow field flow fractionation (AsFlFFF) was combined with pyrolysis-gas chromatography mass spectrometry for a sized based fractionation and a detailed compositional study of the triglycerides and cholesterol associated with the various lipoprotein subclasses present in human serum. Serum samples were injected in the AsFlFFF instrument and fractionated with a time-delayed exponential decay cross flow program. The fractions collected after AsFlFFF elution were injected into a programmable temperature vaporizer (PTV) GC-injector, containing a fritted liner. A temperature and split-flow program for the PTV injector was optimized for the thermally assisted hydrolysis and methylation of the compounds of interest. The resulting fatty acid and cholesterol methyl esters were separated by GC and characteristic fragment ions were detected by MS. The system was optimized and calibrated with triglyceride and cholesterol standards for quantitative analysis. The possible interference by phospholipids with the quantitative results was investigated and found to be of minor importance.The concentrations and lipoprotein profiles of triglycerides and cholesterol were determined in a pooled serum sample of healthy volunteers and a serum sample of a sepsis patient. The results obtained with the GC–MS approach were compared with those of a previously developed method based on AsFlFFF with a dual enzymatic reaction detection system. A good agreement of the profiles was found, for cholesterol as well as for the triglycerides, even when the GC–MS method quantifies the fatty acids while with the enzymatic reaction method the glycerol concentrations are determined. Total cholesterol and triglyceride concentration values for the serum samples showed good agreement with the results of the standard enzymatic method as used in practice in the university hospital.     

Towards obtaining more information from gas chromatography–mass spectrometric data of essential oils: An overview of mean field independent component analysis

Mean field independent component analysis (MF-ICA) along with other chemometric techniques was proposed for obtaining more information from multi-component gas chromatographic–mass spectrometric (GC–MS) signals of essential oils (mandarin and lemon as examples). Using these techniques, some fundamental problems during the GC–MS analysis of essential oils such as varying baseline, presence of different types of noise and co-elution have been solved. The parameters affecting MF-ICA algorithm were screened using a 2⁵ factorial design. The optimum conditions for MF-ICA algorithm were followed by deconvolution of complex GC–MS peak clusters. The number of independent components (ICs) (chemical constituents) in each peak cluster was estimated using morphological score method. Eigenvalue profiles of evolving factor analysis (EFA) and pure variables from orthogonal projection approach (OPA) were used as initial mixing matrix (chromatograms) in iterative process. The resolved mass spectra were satisfactorily identified using NIST mass spectral search system. Finally, the results of optimized MF-ICA were compared with those obtained using multivariate curve resolution-alternating least square (MCR-ALS), multivariate curve resolution-objective function minimization (MCR-FMIN) and heuristic evolving latent projection (HELP) methods. It is demonstrated that MF-ICA can be used as an alternative method for a quick and accurate analysis of real multi-component problematic systems such as essential oils.     

Determination of benzenic and halogenated volatile organic compounds in animal-derived food products by one-dimensional and comprehensive two-dimensional gas chromatography–mass spectrometry

Animal-derived products are particularly vulnerable to contamination by volatile organic compounds (VOCs). These lipophilic substances, which are generated by an increasing number of sources, are easily transferred to the atmosphere, water, soil, and plants. They are ingested by livestock and become trapped in the fat fraction of edible animal tissues. The aim of this work was to determine the occurrence, risk for human health and entryways of benzenic and halogenated VOCs (BHVOCs) in meat products, milks and sea foods using gas chromatography– mass spectrometry (GC–MS) techniques. In the first part, the occurrence and levels of the BHVOCs in animal products were studied. One muscle and three fat tissues were analysed by GC–Quad/MS in 16 lambs. Of 52 BHVOCs identified, 46 were found in the three fat tissues and 29 in all four tissues, confirming that VOCs are widely disseminated in the body. Twenty-six BHVOCs were quantified in fat tissues, and risk for consumer health was assessed for six of these compounds regulated by the US Environmental Protection Agency (EPA). The BHVOC content was found to be consistent with previous reports and was below the maximum contaminant levels set by the EPA. In the second part, the performance of GC×GC–TOF/MS for comprehensively detecting BHVOCs and showing their entryways in animal-derived food chains was assessed. Meat, milk and oysters were analysed by GC–Quad/MS and GC×GC–TOF/MS. For all these products, at least a 7-fold increase in the contaminants detected was achieved with the GC×GC–TOF/MS technique. The results showed that the production surroundings, through animal feeding or geographical location, were key determinants of BHVOC composition in the animal products.     

Ultra high performance liquid chromatography tandem mass spectrometric detection of glucuronides resistant to enzymatic hydrolysis: Implications to doping control analysis

Controversial results have been reported in the literature regarding the behavior of two testosterone (T) metabolites (3α-glucuronide-6β-hydroxyandrosterone and 3α-glucuronide-6β-hydroxyetiocholanolone) excreted after T administration. Due to their potential as biomarkers of T misuse, a UHPLC–MS/MS method for the direct quantification of these glucuronides was developed and validated. In addition, the main phase II metabolites of T that compose the steroid profile used for doping control purposes (glucuronides of T, epitestosterone, androsterone and etiocholanolone) were included. The method was found to be linear and with suitable LODs and LOQs for all metabolites. The average accuracies were between 86% and 120%, the RSDs for the intra- and inter-day precision were below 15% and 25% respectively. The method showed low matrix effect. Samples obtained before and after the administration of T were analyzed by both the developed UHPLC–MS/MS method and the GC–MS/MS method currently used by anti-doping laboratories. Relevant disagreements between the results obtained for 3α-glucuronide-6β-hydroxyandrosterone and 3α-glucuronide-6β-hydroxyetiocholanolone quantitation were observed. These markers seemed to be more suitable for the screening of T misuse when detected by UHPLC–MS/MS. These discrepancies were further investigated in 50 urine samples from healthy volunteers. The two methods gave highly correlated results for all metabolites that are currently included in the athlete's steroid profile confirming the reliability of the UHPLC–MS/MS method. However, the quantification of 3α-glucuronide-6β-hydroxyandrosterone and 3α-glucuronide-6β-hydroxyetiocholanolone, was only possible by using the UHPLC–MS/MS method since three interfering compounds were observed when performing the GC–MS/MS analysis with the most intense ion transitions. These results confirm the potential of the resistant glucuronides as biomarkers of T misuse. Additionally, they suggest that previously reported reference ranges for these metabolites should be reevaluated.     

Multi-response optimization of the extraction and derivatization protocol of selected polar metabolites from apple fruit tissue for GC–MS analysis

Given the complexity of the plant metabolome exhibiting a wide spectrum of physico-chemical properties, finding the best compromise for GC–MS analysis is a challenging exercise. In this study, the GC–MS protocol for extracting and analyzing polar metabolites from apple tissue is optimized. We found pure methanol extraction to be slightly better as compared to the two phase methanol/chloroform/water extraction in terms of introducing less degradation of the extracted metabolites while being comparable in extraction efficiency and repeatability. The methanol extraction was superior to the single phase methanol/chloroform/water extraction in all performance measures. A multi-response optimization based on a desirability function was applied to optimize the derivatization. This procedure allows searching for optimal parameters while simultaneously considering overall detection enhancement of metabolites from various metabolic classes. A short oximation at a high temperature in combination with a low silylation temperature gave results similar to a longer oximation at low temperature in combination with a high silylation temperature. Increasing silylation time from 0.5 h to 2 h resulted in an improvement of the silylation reaction.     

Metabolite profiling of human plasma by different extraction methods through gas chromatography–mass spectrometry—An objective comparison

For the comprehensive metabolite profiling of human plasma, sample preparation is a crucial step. In this investigation, we have compared 10 different extraction techniques for metabolite profiling by GC–MS. Six one-dimensional (1D) and four two-dimensional (2D) extraction techniques involving solvent precipitation, molecular weight cut off tube (MWCOT) and solid phase extraction (SPE) by using silica, RP C18, cation and anion were investigated. Pooled samples of 50 Healthy Male Plasma (HMP), 50 Healthy Female Plasma (HFP) and 100 Healthy Pakistani Plasma (HPP) were subjected to these extraction methods for comparison purposes. Metabolites obtained were identified through NIST mass spectral (Wiley registry), METLIN and Fiehn RTL libraries. XCMS Software was used for the detection of metabolic features, retention time correction, alignment, annotation and statistical analysis in each method. 116–34 peaks were detected by various methods and approx 33% of the peaks were characterized in each method. Hierarchical clustering of the 10 extraction methods showed a low similarity index (50.1%) which indicated different chemical nature of metabolites, resulting from different methods. Venn diagram highlights the GC–MS peaks (33–77%) common in various methods. Metabolites which were different in male and female groups were detected using a threshold value of p ≤ 0.0001, q ≤ 0.001 and fold change ≥3 by employing Welch's t-test and identified through METLIN. Results indicated that 2D-C18 and 2D-silica offers a comprehensive metabolite profile in term of reproducibility, number of peaks and difference in metabolite pattern of male and female.     

A fast method for the identification of Mycobacterium tuberculosis in sputum and cultures based on thermally assisted hydrolysis and methylation followed by gas chromatography–mass spectrometry

A fast gas chromatography–mass spectrometry (GC–MS) method with minimum sample preparation is described for early diagnosis of tuberculosis (TB). The automated procedure is based on the injection of sputum samples which are then methylated inside the GC injector using thermally assisted hydrolysis and methylation (THM). The THM–GC–MS procedure was optimized for the injection of sputum samples. For the identification of Mycobacterium tuberculosis the known marker tuberculostearic acid (TBSA) and other potential markers were evaluated. Hexacosanoic acid in combination with TBSA was found to be specific for the presence of M. tuberculosis. For validation of the method several sputum samples with different viscosities spiked with bacterial cultures were analyzed. Finally, 18 stored sputum samples collected in Vietnam from patients suspected to suffer from TB were re-analyzed in Amsterdam by microscopy after decontamination/concentration and using the new THM–GC–MS method. No false positives were found by THM–GC–MS and all patients who were diagnosed with TB were also found positive using our newly developed THM–GC–MS method. These results show that the new fast and sensitive THM–GC–MS method holds great potential for the diagnosis of TB.     

Towards identification of traditional European and indigenous Australian paint binders using pyrolysis gas chromatography mass spectrometry

We report a pyrolysis GC–MS method capable of analysing Indigenous Australian and European binders typically used in the manufacture of culturally important painted works. Eleven different traditional European binders and ten different Indigenous Australian binders were examined. The method allows discrimination between highly complex and impure lipid, resin, polysaccharide, wax, and protein-based binders. Each was found to have characteristic pyrolysis products that were unique to the binder material, demonstrating the potential for differentiation of these binders on Australian Aboriginal artworks towards identification and conservation of cultural heritage.     

Determination of hydroxylated benzophenone UV filters in sea water samples by dispersive liquid–liquid microextraction followed by gas chromatography–mass spectrometry

A new analytical method for the determination of four hydroxylated benzophenone UV filters (i.e. 2-hydroxy-4-methoxybenzophenone (HMB), 2,4-dihydroxybenzophenone (DHB), 2,2′-dihydroxy-4-methoxybenzophenone (DHMB) and 2,3,4-trihydroxybenzophenone (THB)) in sea water samples is presented. The method is based on dispersive liquid–liquid microextraction (DLLME) followed by gas chromatography–mass spectrometry (GC–MS) determination. The variables involved in the DLLME process were studied. Under optimized conditions, 1000 μL of acetone (disperser solvent) containing 60 μL of chloroform (extraction solvent) were injected into 5 mL of aqueous sample adjusted to pH 4 and containing 10% NaCl. Before injecting into the GC–MS system, the DLLME extracts were evaporated under an air stream and then reconstituted with N,O-bis-(trimethylsilyl)trifluoroacetamide (BSTFA), thus allowing the target analytes to be converted into their trimethylsilyl derivatives. The best conditions for the derivatization reaction were 75 °C and 30 min. High enrichment factors for all the target analytes (ranging from 58 to 64) and good repeatability (RSD around 6%) were obtained. The limits of detection were in the range of 32–50 ng L⁻¹, depending on the analyte. The recoveries obtained by using the proposed DLLME–GC–MS method evidenced the presence of matrix effects for some of the target analytes, and thereby the standard addition calibration method was employed. Finally, the validated method was applied to the analysis of sea water samples.     

Development of a method for enhancing metabolomics coverage of human sweat by gas chromatography–mass spectrometry in high resolution mode

Sweat has recently gained popularity as clinical sample in metabolomics analysis as it is a non-invasive biofluid the composition of which could be modified by certain pathologies, as is the case with cystic fibrosis that increases chloride levels in sweat. However, the whole composition of sweat is still unknown and there is a lack of analytical strategies for sweat analysis. The aim of the present study was to develop and validate a method for metabolomic analysis of human sweat by gas chromatography–time of flight/mass spectrometry (GC–TOF/MS) in high resolution mode. Thus, different sample preparation strategies were compared to check their effect on the profile of sweat metabolites. Sixty-six compounds were tentatively identified by the obtained MS information. Amino acids, dicarboxylic acids and other interesting metabolites such as myo-inositol and urocanic acid were identified. Among the tested protocols, methyoxiamination plus silylation after deproteinization was the most suited option to obtain a representative snapshot of sweat metabolome. The intra-day repeatability of the method ranged from 0.60 to 16.99% and the inter-day repeatability from 2.75 to 31.25%. As most of the identified metabolites are involved in key biochemical pathways, this study opens new possibilities to the use of sweat as a source of metabolite biomarkers of specific disorders.     

Chemometric strategy for untargeted lipidomics: Biomarker detection and identification in stressed human placental cells

A lipidomic study was developed in a human placental choriocarcinoma cell line (JEG-3) exposed to tributyltin (TBT) and to a mixture of perfluorinated chemicals (PFCs). The method was based on the application of multivariate curve resolution-alternating least squares (MCR-ALS) to data sets obtained by ultra-high performance liquid chromatography coupled to time-of-flight mass spectrometry (UHPLC–TOF-MS) using an untargeted approach. Lipids from exposed JEG-3 cells were solid–liquid extracted and analyzed by UHPLC–TOF-MS in full scan mode, together with control samples. Raw UHPLC–TOF-MS data of the different cell samples were subdivided into 20 distinct chromatographic windows and each window was further organized in a column-wise augmented data matrix, where data from every sample was in an individual data matrix. Then, the 20 new augmented data matrices were modeled by MCR-ALS. A total number of 86 components were resolved and a statistical comparative study of their elution profiles showed distinct responses for the lipids of exposed versus control cells, evidencing a lipidome disruption attributed to the presence of the xenobiotics. Results from one-way ANOVA followed by a multiple comparisons test and from discriminant partial least squares (PLS-DA) analysis were compared as usual strategies for the determination of potential biomarkers. Identification of 24 out of the 33 proposed biomarkers contributed to the better understanding of the effects of PFCs and TBT in the lipidome of human placental cells. Overall, this study proposes an innovative untargeted LC–MS MCR-ALS approach valid for -omic sciences such as lipidomics.     

Analytical performance of a triple quadrupole mass spectrometer compared to a high resolution mass spectrometer for the analysis of polybrominated diphenyl ethers in fish

Polybrominated diphenyl ethers (PBDEs) are a class of flame retardants used globally in many consumer products and industrial applications. Traditionally, gas chromatography–high resolution mass spectrometry (GC–HR-MS) is the method of choice for analysis of PBDEs in environmental samples because it offers high sensitivity and selectivity, resulting in less interferences. However, the specificity offered by gas chromatography-triple quadrupole tandem mass spectrometry (GC–QQQ-MS/MS), operated in selected reaction monitoring mode, provides a more affordable alternative to GC–HR-MS for the analysis of PBDEs in complex environmental samples. In this study, an analytical method was developed for the analysis of 41 PBDE congeners in fish using GC–QQQ-MS/MS. Results from the analysis of three fish species [lake trout (Salvelinus namaycush), yellow perch (Perca flavescens), and round goby (Neogobius melanostomus)] using GC–QQQ-MS/MS were compared with those obtained by GC–HR-MS. These species were selected because they represent varying levels of lipid-rich matrix and contaminant loads. Instrumental limits of detection for the GC–QQQ-MS/MS ranged from 0.04 pg to 41 pg, whereas those for the GC–HR-MS ranged from 5 pg to 85 pg. The PBDE values obtained from these two methods were highly correlated, R² values >0.7, for all three fish species, supporting the suitability of GC–QQQ-MS/MS for analysis of PBDEs in fish with varying fat content.     

Rapid automatic identification and quantification of compounds in complex matrices using comprehensive two-dimensional gas chromatography coupled to high resolution time-of-flight mass spectrometry with a peak sentinel tool

Comprehensive two-dimensional gas chromatography coupled to mass spectrometry (GC × GC–MS) is a powerful tool for comprehensive analysis of organic pollutants. In this study, we developed a powerful analytical method using GC × GC for rapid and accurate identification and quantification of compounds in environmental samples with complex matrices. Specifically, we have developed an automatic peak sentinel tool, T-SEN, with free programming software, R. The tool, which consists of a simple algorithm for on peak finding and peak shape identification, allows rapid screening of target compounds, even for large data sets from GC × GC coupled to high resolution time of flight mass spectrometry (HRTOFMS). The software tool automatically assigns and quantifies compounds that are listed in user databases. T-SEN works on a typical 64 bit workstation, and the reference calculation speed is 10–20 min for approximately 170 compounds for peak finding (five ion count setting) and integration from 1–2 GB of sample data acquired by GC × GC–HRTOFMS. We analyzed and quantified 17 PCDD/F congeners and 24 PCB congeners in a crude lake sediment extract by both GC × GC coupled to quadrupole mass spectrometry (qMS) and GC × GC–HRTOFMS with T-SEN. While GC × GC–qMS with T-SEN resulted in false identification and inaccurate quantification, GC × GC–HRTOFMS with T-SEN provided correct identification and accurate quantification of compounds without sample pre-treatment. The differences between the values measured by GC × GC–HRTOFMS with T-SEN and the certified values for the certified reference material ranged from 7.3 to 36.9% for compounds with concentrations above the limit of quantification. False positives/negatives were not observed, except for when co-elution occurred. The technique of GC × GC–HRTOFMS in combination with T-SEN provides rapid and accurate screening and represents a powerful new approach for comprehensive analysis.     

Liquid chromatography–tandem quadrupole mass spectrometry and comprehensive two-dimensional gas chromatography–time-of-flight mass spectrometry measurement of targeted metabolites of Methylobacterium extorquens AM1 grown on two different carbon sources

Complementary methods using liquid chromatography–tandem quadrupole mass spectrometry (LC–MS/MS) and comprehensive two-dimensional gas chromatography–time-of-flight mass spectrometry (GC × GC–TOF-MS) were developed and applied to determine targeted metabolites involved in central carbon metabolism [including tricarboxylic acid cycle, serine cycle, ethylmalonyl-coenzyme A (ethylmalonyl-CoA) pathway and poly-β-hydroxybutyrate cycle] of the bacterium Methylobacterium extorquens AM1 grown on two carbon sources, ethylamine (C2) and succinate (C4). Nucleotides, acyl-CoAs and a few volatile metabolites in cell extracts of M. extorquens AM1 were readily separated using either hydrophilic interaction liquid chromatography or reversed-phase liquid chromatography, and detected with good sensitivity by MS/MS. However, volatile intermediates within a low mass range (<300 m/z), especially at low abundance (such as glyoxylic acid and others <500 nM), were more effectively analyzed by GC × GC–TOF-MS which often provided better sensitivity, resolution and reproducibility. The complementary nature of the LC-based and GC-based methods allowed the comparison of 39 metabolite concentrations (the lowest level was at 139.3 nM). The overlap between the LC-based and GC-based methods of seven metabolites provided a basis to check for consistency between the two methods, and thus provided some validation of the quantification accuracy. The abundance change of 20 intermediates further suggested differences in pathways linked to C2 and C4 metabolism.     

A reliable and simple method for the assay of neuroendocrine tumor markers in human urine by solid-phase microextraction–gas chromatography-triple quadrupole mass spectrometry

Homovanillic acid (HVA), vanylmandelic acid (VMA), and 5-hydroxyindoleacetic acid (5-HIAA) are the metabolites of some catecholamines such as epinephrine, nor-epinephrine, dopamine and serotonin and their quantification is used in the diagnosis and management of patients with neurocrine tumors. A novel approach in the assay of these biomarkers in human urine samples by solid phase microextraction (SPME) combined with gas chromatography-triple quadrupole mass spectrometry (GC–QqQ-MS) is presented. A preliminary derivatization with ethyl chloroformate/ethanol was used and the corresponding derivatives were then extracted by SPME in immersion mode. The performance of five SPME fibers and three chloroformates were evaluated in univariate mode and the best results were obtained using the polyacrylate fiber and ethyl chloroformate. The variables affecting the efficiency of SPME analysis were optimized by the multivariate approach of “Experimental design” and, in particular, a central composite design (CCD) was applied. The optimum working conditions in terms of response values were achieved by performing analysis at room temperature with addition of NaCl (9.5%) and with an extraction time of 25.8 min. Identification and quantification of analytes were carried out by using a gas chromatography-triple quadrupole mass spectrometry (GC–QqQ MS) system in multiple reaction monitoring (MRM) acquisition. An evaluation of all analytical parameters shows that the proposed method provides satisfactory results. Very good linearities were, in fact, achieved in the tested calibration ranges with correlation coefficient values >0.99 for all the analytes and accuracies and RSDs calculated for between-run and tested at concentrations of 1, 10, and 80 mg L⁻¹ were ranging from 91.3% to 106.6%, and from 0.5 to 8.9%, respectively. Moreover, the LOD values obtained can be considered very satisfactory (1.3, 0.046 and 24.3 μg L⁻¹ for HVA, VMA and 5-HIAA, respectively). The developed protocol represents, therefore, a simple, rapid and selective tool for assaying these acidic biomarkers in urine samples for neuroendocrine cancer diagnosis.     

Determination of trace levels of acetamide,propanamide, and butyramide in surface and drinking water using gas chromatography–mass spectrometry after derivatization with 9-xanthydrol

A sensitive gas chromatographic mass spectrometric (GC–MS) method has been established for the simultaneous determination of acetamide (AA), propanamide (PA), and butyramide (BA) in surface and drinking water based on derivatization with 9-xanthydrol. Deuterated acrylamide was chosen as the internal standard for analyzing the water sample. The derivatization of AA, PA, and BA was performed directly in water and the reaction conditions (10.0-mM 9-xanthydrol, 0.5-M HCl, 20-min reaction time, and ambient temperature) were established. Under these conditions, the detection limit of the analytes was 0.03 μg L⁻¹, and the interday relative standard deviation was less than 16% at concentrations of 1.0, 5.0 and 10.0 μg L⁻¹. The proposed GC–MS method enables the reliable analysis of trace AA, PA, and BA in environmental water.