Exploring metabolic syndrome serum profiling based on gas chromatography mass spectrometry and random forest models

Metabolic syndrome (MetS) is a constellation of the most dangerous heart attack risk factors: diabetes and raised fasting plasma glucose, abdominal obesity, high cholesterol and high blood pressure. Analysis and representation of the variances of metabolic profiles is urgently needed for early diagnosis and treatment of MetS. In current study, we proposed a metabolomics approach for analyzing MetS based on GC–MS profiling and random forest models. The serum samples from healthy controls and MetS patients were characterized by GC–MS. Then, random forest (RF) models were used to visually discriminate the serum changes in MetS based on these GC–MS profiles. Simultaneously, some informative metabolites or potential biomarkers were successfully discovered by means of variable importance ranking in random forest models. The metabolites such as 2-hydroxybutyric acid, inositol and d-glucose, were defined as potential biomarkers to diagnose the MetS. These results obtained by proposed method showed that the combining GC–MS profiling with random forest models was a useful approach to analyze metabolites variances and further screen the potential biomarkers for MetS diagnosis.     

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.     

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.     

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.     

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.     

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.     

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.     

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.     

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.     

Automated SPME–GC–MS monitoring of headspace metabolomic responses of E. coli to biologically active components extracted by the coating

Monitoring extracellular metabolites of bacteria is very useful for not only metabolomics research but also for assessment of the effects of various chemicals, including antimicrobial agents and drugs. Herein, we describe the automated headspace solid-phase microextraction (HS-SPME) method coupled with gas chromatography–mass spectrometry (GC–MS) for the qualitative as well as semi-quantitative determination of metabolic responses of Escherichia coli to an antimicrobial agent, cinnamaldehyde. The minimum inhibitory concentration of cinnamaldehyde was calculated to be 2 g L⁻¹. We found that cinnamaldehyde was an important factor influencing the metabolic profile and growth process. A higher number of metabolites were observed during the mid-logarithmic growth phase. The metabolite variations (types and concentrations) induced by cinnamaldehyde were dependent on both cell density and the dose of cinnamaldehyde. Simultaneously, 25 different metabolites were separated and detected (e.g., indole, alkane, alcohol, organic acids, esters, etc.) in headspace of complex biological samples due to intermittent addition of high dose of cinnamaldehyde. The study was done using an automated system, thereby minimizing manual workup and indicating the potential of the method for high-throughput analysis. These findings enhanced the understanding of the metabolic responses of E. coli to cinnamaldehyde shock effect and demonstrated the effectiveness of the SPME–GC–MS based metabolomics approach to study such a complex biological system.     

Qualitative drug analysis of hair extracts by comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry

A technique using comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry (GC × GC/TOFMS) is applied to a qualitative analysis of three sample extracts from hair suspected of containing various drug compounds. The samples were also subjected to a quantitative target analysis for codeine, morphine, 6-monoacetylmorphine (6-MAM), amphetamine, methamphetamine, methylenedioxyamphetamine (MDA), methylenedioxymethylamphetamine (MDMA), methadone, and benzylpiperazine (BZP) by liquid chromatography-tandem mass spectrometry (LC-MS/MS). GC × GC/TOFMS provided a non-specific procedure that identified various drugs, metabolites, and impurities not included in the target analysis. They included cocaine, diazepam, and methaqualone (quaalude). Comprehensive GC × GC separation was achieved using twin-stage cryo-modulation to focus eluant from a DB-5ms (5% phenyl) to a BPX50 (50% phenyl) GC column. The TOF mass spectrometer provided unit mass resolution in the mass range m/z 5–1000 and rapid spectral acquisition (≤500 spectra/s). Clean mass spectra of the individual components were obtained using mass spectral deconvolution software. The ‘unknown’ components were identified by comparison with mass spectra stored in a library database.     

An evaluation of microwave-assisted derivatization procedures using hyphenated mass spectrometric techniques

The potential of microwave-assisted derivatization techniques in systematic toxicological analysis using gas chromatography coupled with mass spectrometry (GC–MS) was evaluated. Special emphasis was placed on the use of dedicated microwave reactors incorporating online temperature and pressure control. The use of such equipment allowed a detailed analysis of several microwave-assisted derivatization protocols comparing the efficiency of microwave and conventional heating methods utilizing a combination of GC–MS and liquid chromatography coupled with mass detection (LC–MS and LC–MS/MS) techniques. These studies revealed that for standard derivatization protocols such as acetylation (exemplified for codeine and morphine), pentafluoropropionylation (for 6-monoacetylmorphine) and trimethylsilylation (for Δ⁹-tetrahydrocannabinol) a reaction time of 5 min at 100 °C in a microwave reactor was sufficient to allow for an effective derivatization. Control experiments using standard operating procedures (30 min at 60 °C conventional heating) indicated that the faster derivatization under microwave irradiation is a consequence of the higher reaction temperatures that can rapidly be attained in a sealed vessel and the more efficient heat transfer to the reaction mixture applying direct in core microwave dielectric heating. The results suggest that microwave derivatization procedures can significantly reduce the overall analysis time and increase sample throughput for GC–MS-based analytical methods.     

Optimisation of a headspace-solid-phase micro-extraction method for simultaneous determination of organometallic compounds of mercury,lead and tin in water by gas chromatography–tandem mass spectrometry

In this work, a headspace-solid-phase micro-extraction (HS-SPME) combined with gas chromatography–mass spectrometry (GC–MS) method for multielemental speciation of organometallic compounds of mercury, lead and tin in water samples was upgraded by the introduction of tandem mass spectrometry (MS/MS) as detection technique. The analytical method is based on the ethylation with NaBEt₄ and simultaneous headspace-solid-phase micro-extraction of the derivative compounds followed by GC–MS/MS analysis. The main experimental parameters influencing the extraction efficiency such as derivatisation time, extraction time and extraction temperature were optimized. The overall optimum extraction conditions were the following: a 50 μm/30 μm divinyl-benzene/carboxen/polydimethylsiloxane (DVB/CAR/PDMS) SPME fibre, 150 min derivatisation time, 15 min extraction time, sample agitation at 250 rpm and 40 °C extraction temperature. The analytical characteristics of the HS-SPME method combined with GC–MS and GC–MS/MS were evaluated. The combination of both techniques HS-SPME and GC–MS/MS allowed to attain lower limits of detection (4–33 ng l⁻¹) than those obtained by HS-SPME–GC–MS (17–45 ng l⁻¹). The proposed method presented good linear regression coefficients (r² > 0.9970) and repeatability (4.8–21.0%) for all the compounds under study. The accuracy of the method measured as the average percentage recovery of the compounds in spiked river water and seawater samples was higher than 80% for all the compounds studied, except for monobutyltin in the river water sample. A study of the uncertainty associated with the analytical results was also carried out.     

Development of solid-phase microextraction to study dissolved organic matter—Polycyclic aromatic hydrocarbon interactions in aquatic environment

Solid-phase microextraction coupled with gas chromatography and mass spectrometry (SPME–GC–MS) was developed for the study of interactions between polycyclic aromatic hydrocarbons (PAHs) and dissolved organic matter (DOM). After the determination of the best conditions of extraction, the tool was applied to spiked water to calculate the dissolved organic carbon water distribution coefficient (K_DOC) in presence of different mixtures of PAHs and Aldrich humic acid. The use of deuterated naphthalene as internal standard for freely dissolved PAH quantification was shown to provide more accuracy than regular external calibration. For the first time, K_DOC values of 18 PAHs were calculated using data from SPME–GC–MS and fluorescence quenching; they were in agreement with the results of previous studies. Competition between PAHs, deuterated PAHs and DOM was demonstrated, pointing out the non-linearity of PAH–DOM interactions and the stronger interactions of light molecular weight PAHs (higher K_DOC values) in absence of high molecular weight PAHs.     

Selectable one-dimensional or two-dimensional gas chromatography–mass spectrometry with simultaneous olfactometry or element-specific detection

A novel selectable one-dimensional (¹D) or two-dimensional (²D) gas chromatography–mass spectrometry (selectable ¹D/²D GC–MS) system with selective detection was developed by using capillary flow technology and low thermal mass GC (LTM-GC). The main advantages of this system are the simple and fast selection of ¹D GC–MS or ²D GC–MS operation without any instrumental set-up change (e.g.²D GC–MS can be run just after ¹D GC–MS run), and simultaneous mass spectrometric and olfactometry or element-specific detection for both ¹D and ²D separation to assure selection of a heart-cut region and correct identification of compounds of interest. The feasibility and benefit of the proposed system with selective detection, e.g. olfactometry, nitrogen phosphorus detection (NPD), and pulsed flame photometric detection (PFPD), was demonstrated with an identification of trace amounts of aroma components in beverages (beer and coffee). Using stir bar sorptive extraction (SBSE) and selectable ¹D/²D GC–Olfactometry/MS on a beer sample, β-damascenone could be determined at 1.9 ng mL⁻¹ (RSD 3.1%, n = 6) as a potent aroma compound. In a coffee sample, two odor active compounds were clearly resolved from a 4.2 s heart-cut and were assigned probable identifications as 4,5-dimethyl thiazole and dimethyl trisulfide based on a NIST library search, dual linear retention indices (dual LRI) and elemental information obtained by SBSE in combination with selectable ¹D/²D GC–NPD/PFPD/MS.     

Automated thermochemolysis reactor for detection of Bacillus anthracis endospores by gas chromatography–mass spectrometry

An automated sample preparation system was developed and tested for the rapid detection of Bacillus anthracis endospores by gas chromatography–mass spectrometry (GC–MS) for eventual use in the field. This reactor is capable of automatically processing suspected bio-threat agents to release and derivatize unique chemical biomarkers by thermochemolysis (TCM). The system automatically controls the movement of sample vials from one position to another, crimping of septum caps onto the vials, precise delivery of reagents, and TCM reaction times and temperatures. The specific operations of introduction of sample vials, solid phase microextraction (SPME) sampling, injection into the GC–MS system, and ejection of used vials from the system were performed manually in this study, although they can be integrated into the automated system. Manual SPME sampling is performed by following visual and audible signal prompts for inserting the fiber into and retracting it from the sampling port. A rotating carousel design allows for simultaneous sample collection, reaction, biomarker extraction and analysis of sequential samples. Dipicolinic acid methyl ester (DPAME), 3-methyl-2-butenoic acid methyl ester (a fragment of anthrose) and two methylated sugars were used to compare the performance of the autoreactor with manual TCM. Statistical algorithms were used to construct reliable bacterial endospore signatures, and 24 out of 25 (96%) endospore-forming Bacillus species were correctly identified in a statistically designed test.     

Extraction of climatic signals from fossil organic compounds in marine sediments up to 11.7 Ma old (IODP-U1318)

This study focuses on the extraction of climate signals and processes using a combined approach which includes the analysis of a high number of lipid molecules in marine sediments, and the chemometric analysis of the acquired data. Neutral and acidic fractions of marine sediments from site IODP-U1318 (south-west of the UK, Porcupine Seabight) were quantified by GC–MS. The alkenone unsaturation index, U^k′₃₇, was estimated from the composition of C₃₇ alkenones and it was then used for the estimation of sea surface temperatures (SST) for reference. Principal component analysis (PCA), explained 77.45% of the total data variance, and differentiated neutral fraction GC–MS total ion current (TIC) profiles according to SST values of the different sediment sections. GC–MS TIC chromatograms were correlated to sea surface temperatures (SST) by partial least squares regression (PLSR). The compounds more robustly in line with SST values at each sediment section explained 93% of the SST variance and they were identified using the variable importance in projection (VIP) scores method. The proposed approach enables an objective identification of organic compounds sensitive to SST variability throughout complete chromatographic profiles. As a result of this multivariate unbiased approach, lipid composition of sediments was differentiated between compounds of marine (long chain n-alkanes, long chain n-alkan-1-ols) and terrestrial (short chain n-alkan1-ols, alkenols, cholesterol, squalene) origin, whose concentrations were directly and inversely correlated to SST, respectively.     

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.     

Mass fragmentation study of the trimethylsilyl derivatives of arctiin,matairesinoside, arctigenin,phylligenin, matairesinol,pinoresinol and methylarctigenin: Their gas and liquid chromatographic analysis in plant extracts

The mass fragmentation patterns and the characteristic behavior of the trimethylsilyl (TMS) derivatives of the dibenzylbutyrolactone-type (arctiin, arctigenin, methylarctigenin, matairesinoside, matairesinol) and those of the diphenylperhydrofurotetrahydrofurane-type (phylligenin, pinoresinol) lignans, obtained by gas chromatography–mass spectrometry (GC–MS), were presented. It was shown that upon acidic hydrolysis the dibenzylbutyrolactone-type lignans are stable while the diphenylperhydrofurotetrahydrofurane-type ones decompose. As a novelty to the field we confirmed that the fragment species of the derivatized lignan glycosides, in the presence of excess hexamethyldisilazane, leaded to their in situ derivatization. Quantification of the selective fragment ions of the TMS derivatives by GC–MS, in respect of the ions found one by one, and concerning the selective fragment ions {SFI(s)} in total, provided acceptable reproducibilities, suitable for quantitation purposes: varying between 1.20% and 6.6% relative standard deviation percentages (RSD%). For characterization of the behavior of various type of lignans, analyses were performed with the untreated and with the trifluoroacetic acid hydrolyzed plant extracts, from the same sample, in parallel, both by GC–MS and by high performance liquid chromatography–mass spectrometry, working in the positive electron ionization mode (HPLC–ESPI-MS). The analysis of lignans in fruit and leaf extracts (obtained from the Arctium, Centaurea and Forsythia plants) was confirmed both by GC–MS and by HPLC–ESPI-MS. Our multicomponent system (including the identification and quantification of sugars, sugar alcohols, and several members of various homologous series of acids, anthraquinones and flavonoids) has been extended to the analysis of lignan glycosides and to the free lignans. Reproducibilities in the quantitation of lignans in plant matrices, as averages on GC and HPLC basis, varied between 0.9% and 11% (RSD). The distribution of the lignan constituents was presented for 5 Arctium, for 8 Centaurea and for 4 Forsythia plant extracts: the total of lignan contents varied between 0.42 and 87.9 mg/g, respectively.     

Metabolomic profiling of human urine in hepatocellular carcinoma patients using gas chromatography/mass spectrometry

With the technique of metabolomics, gas chromatography/mass spectrometry (GC/MS), urine or serum metabolites can be assayed to explore disease biomarkers. In this work, we present a metabolomic method to investigate the urinary metabolic difference between hepatocellular carcinoma (HCC, n = 20) male patients and normal male subjects (n = 20). The urinary endogenous metabolome was assayed using chemical derivatization followed by GC/MS. After GC/MS analysis, 103 metabolites were detected, of which 66 were annotated as known compounds. By a two sample t-test statistics with p < 0.05, 18 metabolites were shown to be significantly different between the HCC and control groups. A diagnostic model was constructed with a combination of 18 marker metabolites or together with alphafetoprotein, using principal component analysis and receiver-operator characteristic curves. The multivariate statistics of the diagnostic model yielded a separation between the two groups with an area under the curve value of 0.9275. This non-invasive technique of identifying HCC biomarkers from urine may have clinical utility.