Two-dimensional Gas Chromatography-mass Spectrometry Research Articles

Comprehensive analysis of spatial heterogeneity reveals the important role of the upper-layer fermented grains in the fermentation and flavor formation of Qingxiangxing baijiu

Different spatial positions lead to inconsistent fermentation effects and flavors, however the spatial heterogeneity of Qingxiangxing (QXX) Baijiu remains unknown. We investigated the microbes, flavors, and physicochemical properties of different layers in fermented grains of QXX Baijiu using Illumina HiSeq sequencing, two-dimensional gas chromatography–mass spectrometry (GC × GC–MS) and ultra-high performance liquid chromatography-mass (UHPLC-MS). A total of 79 volatiles, 1596 metabolites, 50 bacterial genera, and 52 fungal genera were identified. The contents distribution followed the order: upper layer > bottom layer > middle layer. Organic acids and derivatives were the main differential metabolites across the three layers. Starch, pH, and reducing sugar levels increased from the upper to bottom layer. Saccharomyces and Lactobacillus were dominant microbes. Pediococcus, the biomarker of upper layer, showed positively correlations with formic acid, ethyl lactate, acetic acid, ethyl linoleate, and ethyl oleate. These findings deepen our understanding of the fermentation and flavor formation mechanism of QXX Baijiu.

Comprehensive Two-Dimensional Gas Chromatography-Mass Spectrometry as a Tool for the Untargeted Study of Hop and Their Metabolites.

Since hop secondary metabolites have a direct correlation with the quality of beer and other hop-based beverages, and the volatile fraction of hop has a complex composition, requiring effective separation, here we explore the application of headspace solid-phase microextraction as a sample preparation method, coupled with comprehensive two-dimensional gas chromatography-mass spectrometry (GC×GC-MS) analysis. The methodology involved the use of a DVB/PDMS fibre with 500 mg of hop cone powder, extracted for 40 min at 50 °C, for both GC-MS and GC×GC-MS. The varieties Azacca, Cascade, Enigma, Loral, and Zappa were studied comprehensively. The results demonstrate that GC×GC-MS increases the number of peaks by over 300% compared to classical GC-MS. Overall, 137 compounds were identified or tentatively identified and categorised into 10 classes, representing between 87.6% and 96.9% of the total peak area. The composition revealed the highest concentration of sesquiterpene hydrocarbons for Enigma, whilst Zappa showed a relatively significant concentration of monoterpene hydrocarbons. Principal component analysis for all compounds and classes, along with hierarchical cluster analysis, indicated similarities between Zappa and Cascade, and Azacca and Loral. In conclusion, this method presents an optimistic advancement in hop metabolite studies with a simple and established sample preparation procedure in combination with an effective separation technique.

Correlation between microbial communities and volatile flavor compounds in the fermentation of Semen Sojae Praeparatum

SSP (Sojae Semen Praeparatum, SSP), a traditional medicinal and edible product, undergoes natural fermentation resulting in a unique flavor. However, the complexity of the natural fermentation system results in inconsistent quality. This study utilized E-nose, headspace solid-phase microextraction combined with full two-dimensional gas chromatography-mass spectrometry, and high-throughput sequencing techniques to reveal the correlation between key volatile flavor compounds and dominant microbial communities during SSP fermentation. The results showed that total organic acids increased from 50.61 mg/g to 72.29 mg/g during SSP fermentation, and levels of umami and sweet amino acids significantly increased. Alcohols, esters, and acids were the main flavor compounds during SSP fermentation, with 52 being identified as key volatile flavor compounds. In the microbial community, bacterial communities dominated by Proteobacteria, Cyanobacteria, and Firmicutes exhibited dynamic solid changes, while fungal communities dominated by Ascomycota, Basidiomycota, unclassified_Fungi, and Mortierellomycota showed relatively stable abundance. Spearman correlation analysis showed that 9 dominant microbial genera were significantly correlated with 27 key volatile flavor compounds, among which Cladosporium, Leuconostoc, Weissella, and Lactiplantibacillus may be the core functional microbial community for SSP characteristic flavors. This study provided theoretical references for the targeted control of SSP quality and the screening of starter fermentation cultures.

A novel headspace solid-phase microextraction arrow method employing comprehensive two-dimensional gas chromatography–mass spectrometry combined with chemometric tools for the investigation of wine aging

BackgroundOmics is used as an analytical tool to investigate wine authenticity issues. Aging authentication ensures that the wine has undergone the necessary maturation and developed its desired organoleptic characteristics. Considering that aged wines constitute valuable commodities, the development of advanced omics techniques that guarantee aging authenticity and prevent fraud is essential. ResultsΑ solid phase microextraction Arrow method combined with comprehensive two-dimensional gas chromatography-mass spectrometry was developed to identify volatiles in red wines and investigate how aging affects their volatile fingerprint. The method was optimized by examining the critical parameters that affect the solid phase microextraction Arrow extraction (stirring rate, extraction time) process. Under optimized conditions, extraction took place within 45 min under stirring at 1000 rpm. In all, 24 monovarietal red wine samples belonging to the Xinomavro variety from Naoussa (Imathia regional unit of Macedonia, Greece) produced during four different vintage years (1998, 2005, 2008 and 2015) were analyzed. Overall, 237 volatile compounds were tentatively identified and were treated with chemometric tools. Four major groups, one for each vintage year were revealed using the Hierarchical Clustering Analysis. The first two Principal Components of Principal Component Analysis explained 86.1% of the total variance, showing appropriate grouping of the wine samples produced in the same crop year. A two-way orthogonal partial least square – discriminant analysis model was developed and successfully classified all the samples to the proper class according to the vintage age, establishing 17 volatile markers as the most important features responsible for the classification, with an explained total variance of 88.5%. The developed prediction model was validated and the analyzed samples were classified with 100% accuracy according to the vintage age, based on their volatile fingerprint. SignificanceThe developed methodology in combination with chemometric techniques allows to trace back and confirm the vintage year, and is proposed as a novel authenticity tool which opens completely new and hitherto unexplored possibilities for wine authenticity testing and confirmation.

Chemometrics combined with comprehensive two-dimensional gas chromatography-mass spectrometry for the identification of Baijiu vintage

The identification of baijiu vintage is crucial for quality assessment and economic value determination. However, its complex composition and multifaceted influences pose significant technical challenges, necessitating research into its aging mechanisms and the development of related identification methods. This study utilized Chemometrics in conjunction with GC × GC-TOFMS for Baijiu Vintage identification. Data compression achieved a reduction of over 1000-fold without compromising key information, enabling analysis on many samples and get their changing regular in a big matrix by MCR. Subsequently, MCR-ALS facilitated the extraction of physical and chemical meaningful information related to baijiu vintage. Key MCR principal components suitable for qualitative and quantitative assessments were selected using CARS-PLS. The regression model demonstrated errors of less than one year. Furthermore, a PLS-DA model provided 30 MCR principal components as potential markers. The research results provide technical support for baijiu vintage identification and lay the groundwork for studying the changing patterns of flavor compounds in baijiu.

Timing of leaf removal modulates tannin composition and the level of anthocyanins and methoxypyrazines in Pinot noir grapes and wines

This study aimed to investigate the impact of leaf removal on concentrations of anthocyanin, tannin, and methoxypyrazines (MPs) in Pinot noir grapes and wines. Leaf removal after 7 days (LR7), 30 days (LR30), and 60 days (LR60) of flowering were compared with no leaf removal control (LRC). Grapes and resultant wines were analysed for tannin and aroma composition using liquid chromatography and two-dimensional gas chromatography–mass spectrometry. All leaf removal treatments increased anthocyanin concentration in grapes and reduced MP levels in grape stems compared to LRC, indicating the effectiveness of both early and late leaf removal. Leaf removal after 7 days and 30 days were more effective in enhancing colour density, polymeric pigments, and tannin concentration in wines. Higher grape skin tannin and anthocyanin concentrations, along with lower seed tannin concentration in berries, correlated with higher tannin concentrations in wines. LR7 showed significantly higher skin-originated tannin proportion than LRC, suggesting a useful tool to manage tannin extraction. Aroma composition of resultant wines was influenced by leaf removal, although these differences were not evident in the sensory evaluation.

Identification of coronavirus disease marker compounds in sweat with comprehensive two dimensional gas chromatography using multiloop splitter-based non-cryogenic artificial trapping modulation system

This study applied comprehensive two-dimensional gas chromatography-mass spectrometry (GC × GCMS–) for analysis of volatile compounds in headspaces of axillary swab samples of RT-PCR or antigen test kit proven COVID-19 positive and negative volunteers in Bangkok, Thailand. The separation was performed using a conventional Deans switch (DS) based heartcut system with an additional splitter system located between the first (1D) column (30 m) and the DS. The splitter consisted of deactivated fused silica (DFS) columns connected into three loops with the progressively doubled perimeters of the downstream loops. An artificial GC × GC result was obtained by applying a periodic heartcut (H/C) event within every artificial modulation period (PAM) of 1.14 min, selectively transferring the analytes onto the second (2D) column (30 m). Chemometric analysis including feature selection was used to identify significantly altered metabolites between the positive and negative groups. Fourteen significant metabolites were tentatively identified, including p-cymene, linalool, and 2,6,11-trimethyldodecane. The marker peak area thresholds were optimized by generating receiver operating characteristic (ROC) curves showing accuracy, sensitivity and selectivity within the ranges of 94–98%, 93–97% and 94–100%, respectively. Based on these results, we hypothesize that SARS-CoV-2 infection disrupts the metabolism of volatile metabolites in sweat, or impacts the microbiome, changing the volatile profile of sweat in infected patients.

Determination of volatile compounds in different parts of grass carp using GC✕GC-MS combined with chemometrics

The flavor of freshwater fish, which is a highly complex mixture of volatile molecules in varying concentrations, has a nasty and earthy odor. Many compounds of freshwater fish cannot be differentiated due to insufficient separation in traditional one-dimensional gas chromatography-mass spectrometry (GC-MS). This study employed an improved method to detect volatile compounds in different parts of grass carp, including the dorsal meat, skin, intestines, belly, fins, and gills. Comprehensive two-dimensional gas chromatography-mass spectrometry (GC✕GC-MS) with high resolution power was utilized to fully separate the volatile compounds. Additionally, an in-house written script based on Matlab and chemometrics was used to conduct large scale and untargeted studies on volatile compounds. The results demonstrated the superior capability of GC✕GC-MS in identifying a greater number of volatile compounds. The in-house written script was used to automatically compare the same compounds from different samples. Through OPLS-DA analysis, 51 key volatile compound candidates, including dihydrojasmone, cryptomeridiol, (Z,Z)-3,6-nonadienal, 3,5-octadien-2-one, and others, were identified as the most-influential variables in differentiating different parts of grass carp. PCA analysis revealed that the 51 key volatile compound candidates still retained information about the origin of different parts, despite their low concentration. Furthermore, expect that most of these compounds have been found in fish or fish-related products, some may originate from plants, insecticides, or pollution.

Region of interest selection for GC×GC–MS data using a pseudo fisher ratio moving window with connected components segmentation

Comprehensive two-dimensional gas chromatography mass spectrometry (GC×GC–MS) data present several challenges for analysis largely because chemical factors drift along the chromatographic modes across different chromatographic runs, and there is frequently a lack of reliable molecular ion measurements with which to align data across multiple samples. Tensor decomposition techniques such as Parallel Factor Analysis (PARAFAC2/PARAFAC2×N) allow analysts to deconvolve closely eluting signals for quantitative and qualitative purposes. These techniques make relatively few assumptions about chromatographic peak shapes or the relative abundance of noise and allow for highly accurate representations of the underlying chemical phenomena using well-characterized and scrutinized principles of chemometrics. However, expert intervention and supervision is required to select appropriate Regions of Interest (ROI) and numbers of chemical components present in each ROI. We previously reported an automated ROI selection algorithm for GC–MS data in Giebelhaus et al. where we observed the ratio of the first and second eigenvalues within a moving window across the entire chromatogram. Here, we present an extension of this work to automatically detect ROIs in GC×GC–MS chromatograms, while making no assumptions about peak shape. First, we calculate the probabilities of each acquisition being in a ROI, then apply connected components segmentation to discretize the regions of interest. For sparse chromatograms we found the algorithm detected spurious peaks. To address this, we implemented an iterative ROI selection process where we autoscaled the moving window to the standard deviation of the noise from the previous iteration. Using three user-defined parameters, we generated informative ROIs on a wide range of GC×GC-TOFMS chromatograms.

Complex origins of naphthenic oils in the Junggar Basin, China: Biodegradation vs. non-biodegradation

Naphthenic crude oils are scarce resources of great value. Their origins are generally considered to be related to biodegradation, which consumes paraffins and enriches naphthenes. However, other possible controls on the origins of the naphthenic oils remain insufficiently clear. To fill the knowledge gap, we conducted a case study in the Junggar Basin by using comprehensive two-dimensional gas chromatography–mass spectrometry for semi-quantitative analysis of naphthenes in combination with relevant organic geochemical data, and address its global implications by synthesizing the typical naphthenic oils discovered worldwide. It was found that the occurrence of naphthenic crude oils in the basin was not caused by biodegradation alone, while sedimentary paleoenvironments and source-rock biological inputs (i.e., indicative of organofacies) are important controlling factors. Naphthenic crude oils are mainly derived from dolomitic source rocks of the Permian Fengcheng Formation in the Mahu Sag of the northwestern basin, where the average naphthene content is 43.8 %, with an average naphthene/paraffin (N/P) ratio of 1.24. Source rocks were deposited in a reducing, hypersaline and stratified alkaline lake (0.75 < pristane/phytane (Pr/Ph) < 1.46, gammacerane/C30αβ hopane > 0.23), with source-rock biological inputs being dominated by halophilic algae (steranes/hopanes > 1, C28/C27-29-steranes > 40 %). In contrast, crude oils in the Jimusaer Sag of the southeastern basin are paraffinic–naphthenic with an average naphthene content of 24.8 % and an average N/P ratio of 0.75. Source rocks here were deposited in an anoxic–oxic lake of low salinity (1.05 < Pr/Ph < 1.59, 0.15 < gammacerane/C30αβH < 0.18), and organic matter consists of mixed bacteria, algae, and terrigenous higher plants (steranes/hopanes < 1, C28/C27-29-steranes < 40 %). Thermal maturity and biodegradation also control the composition of naphthenic oils. High thermal maturity promotes cracking of naphthenic groups, whereas moderate biodegradation (rank PM < 6) promotes naphthenic groups by preferentially catabolizing paraffins. Our results suggest that halophilic algae in strongly-reducing alkaline lakes provide important material for the generation of naphthenic oils in the Mahu Sag and the occurrence of naphthenic crude oils is not controlled solely by biodegradation; influencing factors are complex and vary between regions without universality. This may be the reason for their limited and sparse distribution worldwide.

Development of Tannins and Methoxypyrazines in Grape Skins, Seeds, and Stems of Two Pinot Noir Clones during Ripening.

Two Pinot noir clones (AM10/5 and UCD5) were analyzed for tannin and methoxypyrazines (MPs) in different grape tissues during berry development using liquid chromatography and two-dimensional gas chromatography-mass spectrometry. On a per berry basis, skin tannins reached the maximum level about 2-3 weeks after véraison, seed tannins at around véraison, and stem tannins 4 weeks before véraison. Clone AM10/5 showed significantly higher levels of seed and stem tannins on a per berry basis at harvest. Tannin concentration and composition varied among the different tissues. On a per berry basis, stem tannin levels were comparable to skin tannins but were 3 to 4 times lower than seed tannins, while stem tannins had an intermediate galloylation (5-7%) between seed tannins (12-18%) and skin tannins (2%) and lower prodelphinidin (4-7%) than skin tannins (31-36%). The mean degree of polymerization of stem tannins was similar to seed tannins but lower than skin tannins. MPs, including 3-isopropyl-2-methoxypyrazine (IPMP), 3-s-isobutyl-2-methoxypyrazine (SBMP), and 3-isobutyl-2-methoxypyrazine (IBMP), showed significantly higher concentrations than their sensory thresholds in grape stems but not in skins. The MPs development in stems showed an increasing trend toward véraison and then a decreasing trend toward harvest. Compared to AM 10/5, UCD5 stems showed a higher level of MPs, especially significantly higher concentrations of IPMP and IBMP at harvest. The extraction of MPs from grape stems could contribute negative green and vegetative characters to Pinot noir wines.

Variation of wine preference amongst consumers is influenced by the composition of salivary proteins

The preferences of consumers for different flavours and aromas in wine are varied and may be explained by inherent factors such as cultural background, wine education and personal taste of the wine consumer. Wine flavour, as perceived in the mouth, includes aroma compounds released through the retronasal pathway, which are shaped by interactions with saliva. Saliva and wine interactions could provide an explanation as to why wine tasters express different preferences for wine. To test this hypothesis, 13 Western and 13 Chinese experienced wine tasters were recruited. Sensory evaluation was performed in formal surroundings to acquire free description-based and perceived sensory intensity data using the Pivot® Profile and continuous scale assessment, respectively. Participants’ saliva samples were collected before the sensory evaluation and spiked into a wine sample to investigate the impact on the wine’s volatile release using comprehensive two-dimensional gas chromatography–mass spectrometry (GC × GC–MS). Saliva samples were subjected to enzyme activity assays and protein composition profiling by Tandem Mass Tag (TMT) quantitative proteomics. The wine tasters showed differences in wine flavour perception, which was supported by the difference in wine volatile release resulting from the addition of saliva. The two groups of participants did not have significant differences in total salivary protein concentrations or the amounts of esterase and α-amylase. However, statistically significant variations in the concentrations of specific proteins (proline-rich proteins (PRPs) and lipocalin-1 (LCN-1); p < 0.01) were found between the two groups. Significant correlations between perceived intensities of wine attributes and concentrations of PRPs and LCN-1 were observed. These results indicate that the composition of proteins in saliva is a factor that influences wine perception and preference. Our results provide a biochemical basis for understanding preference for food based on interactions between aroma compounds and salivary proteins and could be used to suggest foods or beverages to particular cultural groups.

Partial substitution of wheat flour with soybean and gluten powder: impact on flavor characteristics of Pixian Douban-Meju and its quality.

In this study, different proportions of soybean flour and gluten flour were used as partial replacements for wheat flour for the fermentation of Pixian Douban-Meju (PXDB). The aim was to study the effects of soybean flour/gluten flour on the quality improvement of PXDB. In comparison with the control group (CT) (0% substitution of wheat flour), substitution of wheat flower with 12.5% soybean flour (the H2 group), 7.5% gluten flour (G2), and 10% gluten flour (G3) improved the amino acid nitrogen content by 3.8%, 5.6%, and 9.4% respectively. The mixtures of wheat flour and gluten flour (G2 or G3) increased the organic acid and free amino acid content. The results of two-dimensional gas chromatography mass spectrometry (GC × GC-MS) showed that the amount of key aroma substances increased about sixfold in comparison with the CT group (194.61 g.kg-1 ), achieving 1283.67, 1113.883, and 1160.19 g.kg-1 in the H2, G2, and G3 groups, respectively. There were also more aldehydes and pyrazines in all the substitution groups. Quantitative descriptive analysis indicated that the G3 sample presented the best organoleptic quality with a reddish-brown color and a more mellow aroma than the control sample. In conclusion, the fermentation of G3 resulted in higher quality PXDB-meju, showing that partial substitution of wheat flour with gluten improved the quality of PXDB. © 2023 Society of Chemical Industry.

Quantification of odorous and potentially harmful substances in acrylic paint

Within this study sixteen odour active substances (1-butanol, butyl acetate, 3-methyl-4-heptanone, butyl acrylate, styrene, ethylbenzene, propylbenzene, cumene, sec-butylbenzene, benzaldehyde, 2-ethylhexyl acrylate, naphthalene, 1-methylnaphthalene, 2-methylnaphthalene, 1,2-dimethylnaphthalene, 1,7-dimethylnaphthalene), that have previously been identified in acryl paints were quantified in ten black acrylic paint samples using GC-GC-MS (heart-cut two-dimensional gas chromatography-mass spectrometry) after prior extraction and purification via solvent assisted flavour evaporation. In this case, the preceding analysis of the most abundant odour active volatiles via GC-O (gas chromatography-olfactometry) provided indications on which smell properties might be linked with elevated and concerning levels of possibly harmful substances. Based on that work, four samples raised attention due to their mainly repelling or unpleasant odour with mainly aromatic, solvent-like, mothball-like or geranium-like smell impressions. The remaining samples either showed fruity/fermented, fruity/apple juice-like, mushroom-like or cocoa-like/earthy odour qualities. The repelling and unpleasant odour was generally linked to naphthalene or benzene derivatives that are of concern with regard to being potential carcinogens. With concentrations ranging as high as from 3.75 mg/kg to 143.41 mg/kg, n-butanol was found to be the odour active substance with the highest concentrations in all but one paint sample. The results showed that all paints contain different and specific patterns of the analysed odour active substances and volatiles. Whereas only two samples revealed no elevated concentration of any of the quantified substances, two samples (A9 and A10) showed elevated levels for all or nearly all substances. The concentrations for single substances were generally lower than the recommended exposure limit and therefore unlikely to cause any adverse effects with regards to toxicity and irritation as single constituents. However, as a group of substances these might exert adverse health effects due to combined or synergistic effects. Based on these observations, the occurrence of combinations of potentially carcinogenic substances in products which are occupationally used on a daily basis or are in direct skin contact should thus be regarded with care in the future.

Insight into the comparison of key aroma-active compounds between camellia oils from different processing technology

Currently, the difference between key odorants of camellia oils from different processing technology (i.e., extra virgin camellia oil (EVCO), virgin camellia oil (VCO), fragrant camellia oil (FCO)) is unclear. In this study, a total of 91 odorants were identified by comprehensive two-dimensional gas chromatography and quadrupole mass spectrometry (GC × GC-qMS). The headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) provided fingerprint information for 57 odorants distinguished between EVCO, VCO, and FCO. Moreover, 76 odorants were shown flavor dilution (FD) factors range from 1 to 729, and fruity esters (ethyl 2-hydroxypropanoate, ethyl decanoate, and ethyl phenylacetate) with FD factors ≥ 27 and odor activity values ≥ 1 are the unique odorants in EVCO. (E, E)-2,4-Heptadienal, (E, E)-2,4-nonadienal, and d-limonene are the aroma-active compounds in VCO. While furfural and 3-ethyl-2,5-dimethylpyrazine with FD factors ≥ 243 are the major contributors to roasted and nutty odor in FCO. This work provides aroma markers for quality assessment of camellia oils.

Error rate and similarity determination of latent fingerprint chemistry via 1D GC and GC × GC–MS

In response to the National Academy of Science’s report on Strengthening Forensic Science, many researchers have investigated ways of improving and supplementing pattern-based visual methods for latent fingerprint (LF) analysis. Gas chromatography (GC) has been used to study the initial and aged chemistry of latent fingerprints, along with attempting to statistically asses same source association with donor characteristics. Since LFs are composed of a complex mixture of oil, sweat, and other components, sections within the chromatographic profile that have poor resolution could benefit from better separation of components, thus yielding more associations to the correct source. This study investigates the potential of increased source association using comprehensive two-dimensional (GC × GC) and one-dimensional (1D) gas chromatography-mass spectrometry (GC–MS). Three LFs from a sample of thirteen volunteers were collected, derivatized with boron trifluoride–methanol (BF3-MeOH), and analyzed via 1D GC and GC × GC–MS. The statistical strength of source association was performed by evaluating the log likelihood ratios (LLRs) obtained from the intra- and inter-personal pairwise Pearson correlation comparisons (PCCs) and using the normal and kernel density comparison R functions. The 1D GC method provided stronger same-source association due to high intra-personal PCC values; however, lower inter-personal PCCs were acquired from GC × GC. Higher area under the curves (AUCs) and LLR calibration were computed for the 1D GC PCCs. Conversely, poor statistical calibration and discriminating power were obtained for both 1D GC and GC × GC methods when assessing the LLRs despite having high AUCs.

Analysis, distribution and evolution of individual carboxylic acids in crude oil during biodegradation

Carboxylic acids (CAs) are important molecular markers in the study of petroleum biodegradation. This work presents a vortex-assisted liquid–liquid microextraction (VALLME) method, followed by comprehensive two-dimensional gas chromatography-mass spectrometry (GC × GC–MS) analysis for the profiling of CAs in complex oils. The designed extractant containing CAs in VALLME can be silylated immediately and injected into GC × GC–MS without any post-treatment. More than 400 individual CAs, including alkanoic acids, cyclic aliphatic acids and aromatic acids, were putatively or positively identified. With good reproducibility and high sensitivity, VALLME combined with GC × GC–MS was applied to investigate the distribution and evolution of individual CAs in crude oil during laboratory biodegradation. It was found that acyclic acids and monocyclic aliphatic/aromatic acids could be detected at all stages of oil biodegradation, while polycyclic aliphatic/aromatic acids could only be identified in oils at a relatively higher degree of biodegradation. In addition, the contents of each type of CA changed regularly during biodegradation. Targeted analysis on the distributions of individual acyclic acids showed that the abundance ratio of short chain to long chain n-alkanoic acids kept increasing during biodegradation, which might reflect the multiple origins of short chain n-alkanoic acids. Moreover, based on the distributions of pristanic/phytanic acid and pristane/phytane in oils with different biodegradation degrees, pristanic and phytanic acid seemed to be more susceptible to degradation compared to their hydrocarbon analogues, and pristane might be more susceptible to degradation in comparison to phytane.

A green and sustainable method for Capsicum volatilome investigation by means of headspace solid-phase microextraction combined with flow-modulated two-dimensional gas chromatography-mass spectrometry using hydrogen as carrier gas

A green and sustainable method for Capsicum volatilome investigation by means of headspace solid-phase microextraction combined with flow-modulated two-dimensional gas chromatography-mass spectrometry using hydrogen as carrier gas

Acute effects of moderate vs. vigorous endurance exercise on urinary metabolites in healthy, young, physically active men-A multi-platform metabolomics approach.

Introduction: Endurance exercise alters whole-body as well as skeletal muscle metabolism and physiology, leading to improvements in performance and health. However, biological mechanisms underlying the body's adaptations to different endurance exercise protocols are not entirely understood. Methods: We applied a multi-platform metabolomics approach to identify urinary metabolites and associated metabolic pathways that distinguish the acute metabolic response to two endurance exercise interventions at distinct intensities. In our randomized crossover study, 16 healthy, young, and physically active men performed 30min of continuous moderate exercise (CME) and continuous vigorous exercise (CVE). Urine was collected during three post-exercise sampling phases (U01/U02/U03: until 45/105/195min post-exercise), providing detailed temporal information on the response of the urinary metabolome to CME and CVE. Also, fasting spot urine samples were collected pre-exercise (U00) and on the following day (U04). While untargeted two-dimensional gas chromatography-mass spectrometry (GC×GC-MS) led to the detection of 608 spectral features, 44 metabolites were identified and quantified by targeted nuclear magnetic resonance (NMR) spectroscopy or liquid chromatography-mass spectrometry (LC-MS). Results: 104 urinary metabolites showed at least one significant difference for selected comparisons of sampling time points within or between exercise trials as well as a relevant median fold change >1.5 or <0. (NMR, LC-MS) or >2.0 or <0.5 (GC×GC-MS), being classified as either exercise-responsive or intensity-dependent. Our findings indicate that CVE induced more profound alterations in the urinary metabolome than CME, especially at U01, returning to baseline within 24h after U00. Most differences between exercise trials are likely to reflect higher energy requirements during CVE, as demonstrated by greater shifts in metabolites related to glycolysis (e.g., lactate, pyruvate), tricarboxylic acid cycle (e.g., cis-aconitate, malate), purine nucleotide breakdown (e.g., hypoxanthine), and amino acid mobilization (e.g., alanine) or degradation (e.g., 4-hydroxyphenylacetate). Discussion: To conclude, this study provided first evidence of specific urinary metabolites as potential metabolic markers of endurance exercise intensity. Future studies are needed to validate our results and to examine whether acute metabolite changes in urine might also be partly reflective of mechanisms underlying the health- or performance-enhancing effects of endurance exercise, particularly if performed at high intensities.

Solid-phase microextraction Arrow combined with comprehensive two-dimensional gas chromatography-mass spectrometry for the elucidation of the volatile composition of honey samples.

In this work, a solid-phase microextraction (SPME) Arrow method combined with comprehensive two-dimensional gas chromatography-mass spectrometry (GC × GC-MS) was developed for the elucidation of the volatile composition of honey samples. The sample preparation protocol was optimized to ensure high extraction efficiency of the volatile organic compounds (VOCs) which are directly associated with the organoleptic properties of honey and its acceptance by the consumers. Following its optimization, SPME Arrow was compared to conventional SPME in terms of sensitivity, precision, and number of extracted VOCs. The utilization of SPME Arrow fibers enabled the determination of 203, 147, and 149 compounds in honeydew honey, flower honey, and pine honey, respectively, while a significantly lower number of compounds (124, 94, and 111 for honeydew honey, flower honey, and pine honey, respectively) was determined using conventional SPME. At the same time, the utilization of SPME Arrow resulted in enhanced sensitivity and precision. All things considered, SPME Arrow and GC × GC-MS can be considered as highly suitable for the elucidation of the volatile composition of complex food samples resulting in high sensitivity and separation efficiency.