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The clinical diagnosis of dermatophytosis and identification of dermatophytes face challenges due to reliance on culture-based methods. Rapid, cost-effective detection techniques for volatile organic compounds (VOCs) have been developed for other microorganisms, but their application to dermatophytes is limited. This study explores using VOCs as diagnostic markers for dermatophytes. We compared VOC profiles across different dermatophyte taxa using solid-phase microextraction (SPME) and advanced analytical methods: gas chromatography-mass spectrometry (GC-MS) and comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry (GC×GC-TOFMS). We analyzed 47 dermatophyte strains from 15 taxa grown on sheep wool, including clinically significant species. Additionally, we examined phylogenetic relationships among the strains to correlate genetic relatedness with metabolite production. Our results showed that GC×GC-TOFMS offered superior resolution but similar differentiation of VOC profiles compared to GC-MS. VOC spectra allowed reliable distinction of taxonomic units at the species level and below, however, these distinctions showed only a slight correlation with phylogenetic data. We identified pan-dermatophyte and species- or strain-specific VOC profiles, indicating their potential for rapid, non-invasive detection of dermatophyte infections, including epidemic strains. These patterns could enable future taxa-specific identification. Our study highlights the potential of VOCs as tools for dermatophyte taxonomy and diagnosis., Competing Interests: Declarations. Conflict of interest: We declare no conflict of interest., (© 2025. The Author(s).)

Despite the efficacy of strong emission control plans that have been implemented the last few decades, polychlorinated dibenzo- p -dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs) may still be released from anthropogenic sources such as sinter plants, and municipal and hazardous waste incinerators. Monitoring for PCDDs and PCDFs in gaseous emissions from such facilities is important due to the acute toxicity of these compounds even at trace levels. Currently, most of these samples from the African continent are being analysed abroad at high cost, with the direct consequence that the number of measurements are kept to a minimum. In this context, we developed a more affordable analytical approach for the measurement of PCDD/Fs sampled onto Amberlite XAD-2 sorbent, which relies on a novel extraction, clean-up, and analysis method with the aim of reducing both the cost and the complexity of standard methods while maintaining high quality results. A simple, sequential, 3 hour end-over-end tumbling extraction procedure was developed employing acetone :  n -hexane (1 : 9) as extraction solvent. This was combined with a dimethyl sulfoxide (DMSO) clean-up to remove aliphatic interferences, prior to direct analysis by gas chromatography triple quadrupole mass spectrometry. The Unites States Environmental Protection Agency Method 23, in contrast, requires a 16 hour Soxhlet extraction with toluene and multiple column chromatography steps. The end-over-end tumbling extraction yielded an average recovery of 79% for PCDD/Fs usually monitored in gaseous samples, whilst an average recovery of 89% was achieved for the DMSO clean-up procedure. In addition, an overall average recovery of 78% and a Z -score of -1.1 was obtained using the developed method for the proficiency testing of a solid reference material, proving the method is fit for purpose. It was then successfully applied to the analysis of air emissions from a medical waste incinerator, which further showed that the alternative approach may deliver quality, fast, and cost-effective analysis of gaseous PCDD/Fs sampled onto Amberlite XAD-2 sorbent in a developing country context.

Per- and polyfluoroalkyl substances (PFAS) are a group of chemicals that have been widely used by various industries, including the food contact material industry. These substances are favoured for their ability to repel oil and resist moisture. However, exposure to PFAS has been linked to several health problems, including effects on the immune system. According to the European Food Safety Authority (EFSA), food contact materials (FCM) are likely to contribute to human exposure to PFAS. Therefore, this study investigated the exposure to PFAS from FCM. One hundred and ten FCM made of paper and board (e.g. straws, cups, bowls, boxes etc.), sugar cane or wheat pulp-based FCM, called paper analogues (e.g., cup, bowls, plates, hamburger boxes etc.) were carefully selected on the Belgian market and investigated using liquid chromatography coupled with high-resolution mass spectrometery. Out of the 25 PFAS targeted, 11 were detected in the samples, mainly perfluoroalkyl carboxylic acids (PFBA, PFPeA, PFHxA, PFHpA, PFOA, PFNA, PFDA, PFUnDA, PFDoDA, PFTrDA) and PFOS. It was found that all of the paper analogue samples contained PFAS, while 43% of the paper and board samples showed the presence of these chemicals. Except for one sample, most detections suggest contamination rather than intentional use. Finally, a risk assessment was conducted, which revealed potential risks for consumers related to a coffee cup made of paper and board and a food tray made of sugar cane., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

This study aims to characterize a complete volatile organic compound profile of pork neck fat for boar taint prediction. The objectives are to identify specific compounds related to boar taint and to develop a classification model. In addition to the well-known androstenone, skatole and indole, 10 other features were found to be discriminant according to untargeted volatolomic analyses were conducted on 129 samples using HS-SPME-GC×GC-TOFMS. To select the odor-positive samples among the 129 analyzed, the selection was made by combining human nose evaluations with the skatole and androstenone concentrations determined using UHPLC-MS/MS. A comparison of the data of the two populations was performed and a statistical model analysis was built on 70 samples out of the total of 129 samples fully positive or fully negative through these two orthogonal methods for tainted prediction. Then, the model was applied to the 59 remaining samples. Finally, 7 samples were classified as tainted., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Since the ban on single-use plastic articles in Europe, the food contact material (FCM) industry has been forced to move to more sustainable alternatives. Paper and board FCM are convenient alternatives but must be safe for consumers. This study aims to investigate potential migrations of various substances (e.g., plasticizers, photoinitiators, primary aromatic amines, mineral oil, and bisphenols) from straws and takeaway articles made of paper and board. Twenty straws and fifty-eight takeaway articles were carefully selected and investigated using liquid and gas chromatography coupled with tandem mass spectrometry or flame ionization detector. Fourteen substances of all the targeted categories were found in takeaway articles, including seven plasticizers, two photoinitiators, one primary aromatic amine, two bisphenols, and the saturated and aromatic fraction of mineral oil (MOSH and MOAH, respectively). In straws, fewer substances were detected, i.e., six substances, including three plasticizers, one photoinitiator, MOSH, and MOAH. At least one of the target substances was detected in 88% of the samples, demonstrating the importance of further evaluation of these materials. Finally, the associated risks were assessed, highlighting the potential risks for several types of articles regarding bisphenol A, one primary aromatic amine (3.3-DMB), and MOSH and MOAH., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Di Mario, Bauwens, Peltier, Goscinny, Focant, Purcaro and Van Hoeck.)

In recent years, comprehensive two-dimensional gas chromatography (GC × GC) has been gradually gaining prominence as a preferred method for the analysis of complex samples due to its higher peak capacity and resolution power compared to conventional gas chromatography (GC). Nonetheless, to fully benefit from the capabilities of GC × GC, a holistic approach to method development and data processing is essential for a successful and informative analysis. Method development enables the fine-tuning of the chromatographic separation, resulting in high-quality data. While generating such data is pivotal, it does not necessarily guarantee that meaningful information will be extracted from it. To this end, the first part of this manuscript reviews the importance of theoretical modeling in achieving good optimization of the separation conditions, ultimately improving the quality of the chromatographic separation. Multiple theoretical modeling approaches are discussed, with a special focus on thermodynamic-based modeling. The second part of this review highlights the importance of establishing robust data processing workflows, with a special emphasis on the use of advanced data processing tools such as, Machine Learning (ML) algorithms. Three widely used ML algorithms are discussed: Random Forest (RF), Support Vector Machine (SVM), and Partial Least Square-Discriminate Analysis (PLS-DA), highlighting their role in discovery-based analysis., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Introduction: Modern comprehensive instrumentations provide an unprecedented coverage of complex matrices in the form of high-dimensional, information rich data sets., Objectives: In addition to the usual biomarker research that focuses on the detection of the studied condition, we aimed to define a proper strategy to conduct a correlation analysis on an untargeted colorectal cancer case study with a data set of 102 variables corresponding to metabolites obtained from serum samples analyzed with comprehensive two-dimensional gas chromatography coupled to high-resolution time-of-flight mass spectrometry (GC × GC-HRTOF-MS). Indeed, the strength of association existing between the metabolites contains potentially valuable information about the molecular mechanisms involved and the underlying metabolic network associated to a global perturbation, at no additional analytical effort., Methods: Following Anscombe's quartet, we took particular attention to four main aspects. First, the presence of non-linear relationships through the comparison of parametric and non-parametric correlation coefficients: Pearson's r, Spearman's rho, Kendall's tau and Goodman-Kruskal's gamma. Second, the visual control of the detected associations through scatterplots and their associated regressions and angles. Third, the effect and handling of atypical samples and values. Fourth, the role of the precision of the data on the attribution of the ranks through the presence of ties., Results: Kendall's tau was found the method of choice for the data set at hand. Its application highlighted 17 correlations significantly altered in the active state of colorectal cancer (CRC) in comparison to matched healthy controls (HC), from which 10 were specific to this state in comparison to the remission one (R-CRC) investigated on distinct patients. 15 metabolites involved in the correlations of interest, on the 25 unique ones obtained, were annotated (Metabolomics Standards Initiative level 2)., Conclusions: The metabolites highlighted could be used to better understand the pathology. The systematic investigation of the methodological aspects that we expose allows to implement correlation analysis to various fields and many specific cases., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

In this study, we introduce a new nontargeted tile-based supervised analysis method that combines the four-grid tiling scheme previously established for the Fisher ratio (F-ratio) analysis (FRA) with the estimation of tile hit importance using the machine learning (ML) algorithm Random Forest (RF). This approach is termed tile-based RF analysis. As opposed to the standard tile-based F-ratio analysis, the RF approach can be extended to the analysis of unbalanced data sets, i.e., different numbers of samples per class. Tile-based RF computes out-of-bag (oob) tile hit importance estimates for every summed chromatographic signal within each tile on a per-mass channel basis ( m / z ). These estimates are then used to rank tile hits in a descending order of importance. In the present investigation, the RF approach was applied for a two-class comparison of stool samples collected from omnivore (O) subjects and stored using two different storage conditions: liquid (Liq) and lyophilized (Lyo). Two final hit lists were generated using balanced (8 vs Eight comparison) and unbalanced (8 vs Nine comparison) data sets and compared to the hit list generated by the standard F-ratio analysis. Similar class-distinguishing analytes ( p < 0.01) were discovered by both methods. However, while the FRA discovered a more comprehensive hit list (65 hits), the RF approach strictly discovered hits (31 hits for the balanced data set comparison and 29 hits for the unbalanced data set comparison) with concentration ratios, [OLiq]/[OLyo], greater than 2 (or less than 0.5). This difference is attributed to the more stringent feature selection process used by the RF algorithm. Moreover, our findings suggest that the RF approach is a promising method for identifying class-distinguishing analytes in settings characterized by both high between-class variance and high within-class variance, making it an advantageous method in the study of complex biological matrices.

Colorectal cancer (CRC) ranks as the third most frequently diagnosed cancer and the second leading cause of cancer-related deaths. The current endoscopic-based or stool-based diagnostic techniques are either highly invasive or lack sufficient sensitivity. Thus, there is a need for less invasive and more sensitive screening approaches. We, therefore, conducted a study on 64 human serum samples representing three different groups (adenocarcinoma, adenoma, and control) using cutting-edge GC×GC-LR/HR-TOFMS (comprehensive two-dimensional gas chromatography coupled with low/high-resolution time-of-flight mass spectrometry). We analyzed samples with two different specifically tailored sample preparation approaches for lipidomics (fatty acids) (25 μL serum) and metabolomics (50 μL serum). In-depth chemometric screening with supervised and unsupervised approaches and metabolic pathway analysis were applied to both datasets. A lipidomics study revealed that specific PUFA (ω-3) molecules are inversely associated with increased odds of CRC, while some PUFA (ω-6) analytes show a positive correlation. The metabolomics approach revealed downregulation of amino acids (alanine, glutamate, methionine, threonine, tyrosine, and valine) and myo-inositol in CRC, while 3-hydroxybutyrate levels were increased. This unique study provides comprehensive insight into molecular-level changes associated with CRC and allows for a comparison of the efficiency of two different analytical approaches for CRC screening using same serum samples and single instrumentation.

According to the annual production of plastics worldwide, in 2020 about 370 million tons of plastic were produced in the world. Chemical recycling, particularly pyrolysis of plastic wastes, could be a valuable solution to resolve these problems and provide an alternative pathway to produce "recycled" chemical products for the petrochemical industry. Nevertheless, the pyrolysis oils need a detailed characterization before the upgrading test to re-use them to generate new recycled products. Multidimensional gas chromatography coupled with both low- and high-resolution time-of-flight mass spectrometers was employed for a detailed investigation among and within different chemical classes present in bio-plastic oil. The presence of several isomeric species as well as homologs series did not allow a reliable molecular identification, except for a few compounds that showed both MS similarity >800/1000 and retention index within ±20. Indeed, the identification of several isomeric species was assessed by high-resolution mass spectrometry equipped with photoionization interface. This soft ionization mode was an additional filter in the identification step allowing unambiguous identification of analytes not identified by the standard electron ionization mode at 70 eV. The injection method was also optimized using a central composite design to successfully introduce a wide range of carbon number compounds without discrimination of low/high boiling points., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

In this contribution, we describe a novel modeling approach to predicting retention times ( t r ) in comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (GC × GC-ToF-MS) with a particular emphasis on the second-dimension ( 2 D) retention time predictions ( 2 t r ). This approach is referred to as a "top-down" approach in that it breaks down the complete GC × GC separation into two independent one-dimensional gas chromatography separations (1D-GC). In this regard, both dimensions, that is, first dimension ( 1 D) and second dimension ( 2 D) are treated separately, and the cryogenic modulator is simply considered as a second consecutive injection device. Separate 1D-GC t r predictions are performed on both dimensions using the same flow rate as the one deployed in the conventional GC × GC system. The separate t r predictions are then combined to account for the two-dimensional separation. This model was applied to 24 analytes from 2 standard mixtures (Grob Test Mix and Fragrance Materials Test Mix) and assessed across 9 GC × GC chromatographic conditions. The experimental and predicted chromatographic retention space occupations were assessed by using the convex hull approach defined by the Delaunay triangulation. The predicted percentage of space occupation corresponded favorably with the experimental values. Furthermore, the top-down approach enabled an accurate prediction of the 2 t r of all investigated analytes, providing an average 2 t r modeling error of 0.26 ± 0.01 s.

Mass spectrometry (MS)-based techniques, including liquid chromatography coupling, shotgun lipidomics, MS imaging, and ion mobility, are widely used to analyze lipids. However, with enhanced separation capacity and an optimized chemical derivatization approach, comprehensive two-dimensional gas chromatography (GC×GC) can be a powerful tool to investigate some groups of small lipids in the framework of lipidomics. This study describes the optimization of a dedicated two-stage derivatization and extraction process to analyze different saturated and unsaturated fatty acids in plasma by two-dimensional gas chromatography-time-of-flight mass spectrometry (GC×GC-TOFMS) using a full factorial design. The optimized condition has a composite desirability of 0.9159. This optimized sample preparation and chromatographic condition were implemented to differentiate between positive (BT) and negative (UT) boar-tainted pigs based on fatty acid profiling in pig serum using GC×GC-TOFMS. A chemometric screening, including unsupervised (PCA, HCA) and supervised analysis (PLS-DA), as well as univariate analysis (volcano plot), was performed. The results suggested that the concentration of PUFA ω-6 and cholesterol derivatives were significantly increased in BT pigs, whereas SFA and PUFA ω-3 concentrations were increased in UT pigs. The metabolic pathway and quantitative enrichment analysis suggest the significant involvement of linolenic acid metabolism.

The high potential of exhaled breath for disease diagnosis has been highlighted in numerous studies. However, exhaled breath analysis is suffering from a lack of standardized sampling and analysis procedures, impacting the robustness of inter-laboratory results, and thus hampering proper external validation. The aim of this work was to verify compliance and validate the performance of two different comprehensive two-dimensional gas chromatography coupled to mass spectrometry platforms in different laboratories by monitoring probe metabolites in exhaled breath following the Peppermint Initiative guidelines. An initial assessment of the exhaled breath sampling conditions was performed, selecting the most suitable sampling bag material and volume. Then, a single sampling was performed using Tedlar bags, followed by the trapping of the volatile organic compounds into thermal desorption tubes for the subsequent analysis using two different analytical platforms. The thermal desorption tubes were first analyzed by a (cryogenically modulated) comprehensive two-dimensional gas chromatography system coupled to high-resolution time-of-flight mass spectrometry. The desorption was performed in split mode and the split part was recollected in the same tube and further analyzed by a different (flow modulated) comprehensive two-dimensional gas chromatography system with a parallel detection, specifically using a quadrupole mass spectrometer and a vacuum ultraviolet detector. Both the comprehensive two-dimensional gas chromatography platforms enabled the longitudinal tracking of the peppermint oil metabolites in exhaled breath. The increased sensitivity of comprehensive two-dimensional gas chromatography enabled to successfully monitor over a 6.5 h period a total of 10 target compounds, namely α-pinene, camphene, β-pinene, limonene, cymene, eucalyptol, menthofuran, menthone, isomenthone, and neomenthol., (© 2022 The Authors. Journal of Separation Science published by Wiley-VCH GmbH.)

Coffee, one of the most popular beverages in the world, attracts consumers by its rich aroma and the stimulating effect of caffeine. Increasing consumers prefer decaffeinated coffee to regular coffee due to health concerns. There are some main decaffeination methods commonly used by commercial coffee producers for decades. However, a certain amount of the aroma precursors can be removed together with caffeine, which could cause a thin taste of decaffeinated coffee. To understand the difference between regular and decaffeinated coffee from the volatile composition point of view, headspace solid-phase microextraction two-dimensional gas chromatography time-of-flight mass spectrometry (HS-SPME-GC×GC-TOFMS) was employed to examine the headspace volatiles of eight pairs of regular and decaffeinated coffees in this study. Using the key aroma-related volatiles, decaffeinated coffee was significantly separated from regular coffee by principal component analysis (PCA). Using feature-selection tools (univariate analysis: t -test and multivariate analysis: partial least squares-discriminant analysis (PLS-DA)), a group of pyrazines was observed to be significantly different between regular coffee and decaffeinated coffee. Pyrazines were more enriched in the regular coffee, which was due to the reduction of sucrose during the decaffeination process. The reduction of pyrazines led to a lack of nutty, roasted, chocolate, earthy, and musty aroma in the decaffeinated coffee. For the non-targeted analysis, the random forest (RF) classification algorithm was used to select the most important features that could enable a distinct classification between the two coffee types. In total, 20 discriminatory features were identified. The results suggested that pyrazine-derived compounds were a strong marker for the regular coffee group whereas furan-derived compounds were a strong marker for the decaffeinated coffee samples.

European Biota Quality Standards (EQS biota ), for compounds with low water solubility and high biomagnification, were created to sustain water quality and protect top predators and humans from secondary poisoning. In reality, for multiple compounds, an exceedance of these standards is often reported in literature without a decrease in ecological water quality determined by biotic indices. In the present study, threshold concentrations were defined in biota (from 44 sampling locations throughout Flanders (Belgium)), above which a good ecological water quality, assessed by the Multimetric Macroinvertebrate Index Flanders (MMIF), was never reached. Threshold values were compared to current EQS biota . Accumulated perfluoroctane sulfonate (PFOS), mercury (Hg), hexabromocyclododecane (HBCD), polybrominated diphenyl ethers (PBDEs), dioxins and polychlorinated biphenyls (PCBs) concentrations were measured in muscle tissue of European yellow eel (Anguilla anguilla) and perch (Perca fluviatilis). Fluoranthene and benzo(a)pyrene were also analyzed in translocated mussels (Dreissena bugensis, D. polymorpha and Corbicula fluminea). Threshold values could only be calculated using a 90th quantile regression model for PFOS (in perch; 12 µg/kg ww), PCBs (in eel; 328 µg/kg ww) and benzo(a)pyrene (in mussels: 4.35 µg/kg ww). The lack of a significant regression model for the other compounds indicated an effective threshold value higher than the concentrations measured in the present study. Alternatively, the 95th percentile of concentrations measured in locations with a good ecological quality (MMIF≥0.7), was calculated for all compounds as an additional threshold value. Finally, fish concentrations were standardized for 5% lipid content (or 26% dry weight content for PFOS and Hg). Threshold values for PFOS and benzo(a)pyrene and the 95th percentiles for dioxins and fluoranthene were comparable to the existing standards. For all other compounds, the 95th percentile was higher than the current EQS biota , while for HBCD, it was lower. These results strongly advise revising and fine-tuning the current EQS biota , especially for ∑PBDE and HBCD., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

The production of renewable fuels as biodiesel and bio-jet fuel is usually originated by the transformation and processing of oleaginous feedstocks, mainly composed of triacylglycerols. Currently, a significant part of the triacylglycerol production relies on grassy oil crops or other woody oil plants, representing more than 120 million metric tons every year. Considering that the worldwide triacylglycerol demand is expected to rise in the future, alternative routes are necessary to ensure a sustainable biodiesel industry and limit diesel price volatility. In this context, the use of animal fats could be an interesting alternative for biodiesel production as the production of animal byproducts represents nearly 17 million tons per year in the European Union only (2020). Animal fats, however, contain large amounts of no-esterified fatty acids and other oxygen compounds, reducing the yield of biodiesel. Therefore, a specific pretreatment is needed before the trans-esterification process. The setup of such appropriate pretreatments requires detailed upstream characterization of the minor components present in the feedstock. For this purpose, the minor component profile of animal fat was investigated by comprehensive two-dimensional gas chromatography coupled with high-resolution time-of-flight mass spectrometry. This was preceded by an innovative sample fractionation and focalization of these minor components by a preparative liquid chromatographic column method. The overall method permitted to extract different levels of information from the two-dimensional chromatograms, leading to a tentative identification of more than 150 compounds, mainly oxygenated, belonging to different chemical classes., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Many aquatic ecosystems are under persistent stress due to influxes of anthropogenic chemical pollutants. High concentrations can harm entire ecosystems and be toxic to humans. However, in case of highly hydrophobic compounds, their low water solubility precludes direct measurement in water, and thus alternative monitoring strategies are needed. In the present study, we investigated the extent to which bioaccumulated concentrations of persistent compounds can be predicted by concentrations in environmental compartments (water and sediment). Due to their high biomagnification potential, Hg and PFOS were included in this analysis as well. At 44 field locations in Flanders (Belgium), we monitored the concentrations of 11 priority compounds and their derivatives, included in the Water Framework Directive, in both sediment and water (where feasible) and biota (European perch, European eel and freshwater mussels). Besides, some sediment (i.e. total organic carbon (TOC) and clay content) and water characteristics were measured (i.e. pH, oxygen level, conductivity, nitrate, nitrite and dissolved organic carbon (DOC)). Measurements of HCB, HCBD, cis-heptachlorepoxide, HBCD and PFOS in sediment and ∑PCB in water showed a lower detection frequency than in fish samples. While PCB profiles were comparable between all matrices, for PBDE clear differences were detected between sediment and fish profiles, with BDE99 contributing the most for sediment (34%) and BDE47 for fish (≥44%), followed by BDE99 for perch (28%) and BDE100 for eel (25%). Water concentrations for PFOS and benzo(a)pyrene were predictive of respective bioaccumulated concentrations. HCB, ∑PCB and ∑PBDE, concentrations in fish were dependent on sediment concentrations and negatively related to organic compound levels (p < 0.05). Furthermore, pH and nitrite were negatively associated with accumulated concentrations in eel for HCB and PFOS, respectively (p < 0.05). Strong relationships between bioaccumulation and sediment and/or water concentrations strengthened the basis for surrogate monitoring methods. Finally, the extrapolation potential of Hg, ∑PBDE, PFOS, HBCD and ∑PCB between both fish species offered new opportunities in extrapolating different European monitoring frameworks., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.)

Catalyzed light olefin oligomerization is widely used in petrochemical industries to produce fuels and chemicals. Light olefins such as propene and butenes are commonly selected as feedstocks. Solid phosphoric acid (SPA) and zeolite are representative acidic catalysts. Both the feedstocks and catalysts have an impact on the product composition. In this study, state-of-the-art instrumentation two-dimensional gas chromatography (GC × GC) coupled photoionization-time of flight mass spectrometry was employed to investigate the composition of dodecene products produced from olefin oligomerization. Information such as the olefin congener distribution, dodecene structural subgroup distribution, and individual dodecene isomers was obtained and utilized in the statistical analyses. By using specific data sets of the product composition, the distinguishment between SPA and zeolite catalysts as well as among the feedstocks was achieved by applying the unsupervised screening approaches (principal component analysis and hierarchical clustering analysis). The potential indicators of catalysts and feedstocks were selected by the feature selection methods (univariate analysis: analysis of variance and multivariate analysis: partial least squares-discriminant analysis)., Competing Interests: The authors declare no competing financial interest., (© 2021 The Authors. Published by American Chemical Society.)

In the host, pathogenic microorganisms have developed stress responses to cope with constantly changing environments. Stress responses are directly related to changes in several metabolomic pathways, which could hamper microorganisms' unequivocal identification. We evaluated the effect of various in vitro stress conditions (acidic, basic, oxidative, ethanolic, and saline conditions) on the metabolism of Staphylococcus aureus, Bacillus cereus, and Pseudomonas aeruginosa, which are common lung pathogens. The metabolite profiles of the bacteria were analyzed using liquid chromatography coupled to triple quadrupole and quadrupole time-of-flight mass spectrometry. The advantages of targeted and untargeted analysis combined with univariate and multivariate statistical analysis (principal component analysis, hierarchical cluster analysis, partial least square discriminant analysis, random forest) were combined to unequivocally identify bacterial species. In normal in vitro conditions, the targeted methodology, based on the analysis of primary metabolites, enabled the rapid and efficient discrimination of the three bacteria. In changing in vitro conditions and specifically in presence of the various stressors, the untargeted methodology proved to be more valuable for the global and accurate differentiation of the three bacteria, also considering the type of stress environment within each species. In addition, species-specific metabolites (i.e., fatty acids, polysaccharides, peptides, and nucleotide bases derivatives) were putatively identified. Good intra-day repeatability and inter-day repeatability (< 10% RSD and < 15% RSD, respectively) were obtained for the targeted and the untargeted methods. This untargeted approach highlights its importance in unusual (and less known) bacterial growth environments, being a powerful tool for infectious disease diagnosis, where the accurate classification of microorganisms is sought., (© 2021. Springer-Verlag GmbH Germany, part of Springer Nature.)

This contribution evaluates the performance of two predictive approaches in calculating temperature-programmed gas chromatographic retention times under vacuum outlet conditions. In the first approach, the predictions are performed according to a thermodynamic-based model, while in the second approach the predictions are conducted by using the temperature-programmed retention time equation. These modeling approaches were evaluated on 47 test compounds belonging to different chemical classes, under different experimental conditions, namely, two modes of gas flow regulation (i.e., constant inlet pressure and constant flow rate), and different temperature programs (i.e., 7 °C/min, 5 °C/min, and 3 °C/min). Both modeling approaches gave satisfactory results and were able to accurately predict the elution profiles of the studied test compounds. The thermodynamic-based model provided more satisfying results under constant flow rate mode, with average modeling errors of 0.43%, 0.33%, and 0.15% across all the studied temperature programs. Nevertheless, under constant inlet pressure mode, lower modeling errors were achieved when using the temperature-programmed retention time equation, with average modeling errors of 0.18%, 0.18%, and 0.31% across the used temperature programs., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Systemic sclerosis is a rare autoimmune disease associated with rapidly evolving interstitial lung disease, responsible for the disease severity and mortality. Specific biomarkers enabling the early diagnosis and prognosis associated with the disease progression are highly needed. Volatile organic compounds in exhaled breath are widely available and non-invasive and have the potential to reflect metabolic processes occurring within the body. Comprehensive two-dimensional gas chromatography coupled to high-resolution mass spectrometry was used to investigate the potential of exhaled breath to diagnose systemic sclerosis. The exhaled breath of 32 patients and 30 healthy subjects was analyzed. The high resolving power of this approach enabled the detection of 356 compounds in the breath of systemic sclerosis patients, which was characterized by an increase of mainly terpenoids and hydrocarbons. In addition, the use of 4 complementary statistical approaches (two-tailed equal variance t-test, fold change, partial least squares discriminant analysis, and random forest) resulted in the identification of 16 compounds that can be used to discriminate systemic sclerosis patients from healthy subjects. Receiver operating curves were generated that provided an accuracy of 90%, a sensitivity of 92%, and a specificity of 89%. The chemical identification of eight compounds predictive of systemic sclerosis was validated using commercially available standards. The analytical variations together with the volatile composition of room air were carefully monitored during the timeframe of the study to ensure the robustness of the technique. This study represents the first reported evaluation of exhaled breath analysis for systemic sclerosis diagnosis and provides surrogate markers for such disease.

Commercial dodecenes are a complex chemical mixture with a majority of C 12 olefins and minority of C 8-18 olefins. Structurally, dodecene products may consist of straight-chain alkenes, branched alkenes, as well as cyclic hydrocarbons. Due to the difference of feeds and catalysts used in the oligomerization reaction, the composition of the dodecenes is complex and their properties are very different. Knowing the complex composition of dodecenes can help tune the production process and select the appropriate products according to their end use. To reveal the complex profile of dodecenes, an analytical method using two-dimensional gas chromatography (GC×GC) coupled photoionization (PI) - time of flight mass spectrometry (TOFMS) was developed in this study. A conventional (nonpolar × polar) column combination (non-polar column as 1 st dimension and mid-polar column as 2 nd dimension) was selected. The analytical condition of GC was optimized using fractional factorial experimental design (DoE). Olefin congener grouping by carbon chain length and double bond equivalent (DBE) was achieved based on the detection of molecular ions by PI-TOFMS. Grouping of dodecenes by linear, mono-branched, di- and tri-branched subgroups was achieved based on branching index (BI) under the assumption of no retention time (RT) overlap among subgroups. Certain dodecene isomers were identified by retention index (RI) and further confirmed by PI mass spectra. The information altogether provided a multimodal characterization possibility to be used with statistical tools. Principal component analysis (PCA) and hierarchical clustering analysis (HCA) of seventeen dodecene samples explained the composition variance between catalysts solid phosphoric acid and zeolite, as well as between feeds with C 4 and without C 4 ., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

In this review, we report on the latest (2020-Early 2021) instrumental advances and applications of comprehensive two-dimensional gas chromatography (GC×GC), including its hyphenation with novel upstream or downstream processes (sample preparation approaches or detection technologies). We also discuss software and analysis workflow developments necessary to elaborate the dense chemical information obtained. Thirty years after its inception, the use of GC×GC, as the main analytical tool or as a complementary platform, is undoubtedly shifting toward more applied challenges in a vast breadth of applications. Therefore, we consider the major fields (energy, fuel, foodstuff, plant, biological, and environmental) in which GC×GC has been successfully used, discussing some of the recent innovative research works., Competing Interests: The authors declare no competing financial interest., (© 2021 The Authors. Analytical Science Advances published by Wiley‐VCH GmbH.)

The increased attraction of biological volatile compounds has opened the route to a wide variety of sampling techniques, amongst which trap tubes packed with adsorbent materials are commonly used. Many types of adsorbent materials are available and the choice of the adsorbent can impact the obtained results in untargeted analysis. Therefore, a proper combination of the adsorbent material and the sample is necessary to increase the robustness and reproducibility of biological studies. In this study, the sampling performance of thermal desorption tubes with six common adsorbent material combinations, i.e., Tenax® TA, Tenax® TA/Carbopack™ B, Tenax® TA/Sulficarb, Tenax® TA/Carbograph™ 5TD, Tenax® TA/Carbograph™ 1TD/Carboxen® 1003, and Carboxen® 1016/Carbograph™ 5TD, was evaluated in two different setups: in vitro and in vivo sampling. The in vitro setup consisted of the headspace dynamic extraction of spiked serum, and a mixture of 19 standards was evaluated in terms of response and reproducibility. The in vivo setup consisted into two parts: the first one was based the evaluation of the standard mixture, which was flash-vaporised into Tedlar® bags containing exhaled breath; the second part was based on the longitudinal monitoring of breath metabolites originating from a beverage intake (i.e., brewed coffee), over a 90 min time period. The tubes were all desorbed and analysed in a comprehensive two-dimensional gas chromatography system coupled to a high-resolution time-of-flight mass spectrometer (GC × GC-HR ToF MS). In both sampling setups, the widest analytes coverage and the overall best extraction yield on the selected compounds were obtained using Tenax® TA, followed by Tenax® TA/Carbopack™ B. Tenax® TA provided the highest sampling reproducibility with 12 %RSD, 10 %RSD and <5 %RSD of the response during the experiments using the in vitro setup, the in vivo setup, and during the longitudinal tracking, respectively., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Comprehensive two-dimensional gas chromatography (GC × GC) is amongst the most powerful separation technologies currently existing. Since its advent in early 1990, it has become an established method which is readily available. However, one of its most challenging aspects, especially in hyphenation with mass spectrometry is the high amount of chemical information it provides for each measurement. The GC × GC community agrees that there, the highest demand for action is found. In response, the number of software packages allowing for in-depth data processing of GC × GC data has risen over the last couple of years. These packages provide sophisticated tools and algorithms allowing for more streamlined data evaluation. However, these tools/algorithms and their respective specific functionalities differ drastically within the available software packages and might result in various levels of findings if not appropriately implemented by the end users. This study focuses on two main objectives. First, to propose a data analysis framework and second to propose an open-source dataset for benchmarking software options and their specificities. Thus, allowing for an unanimous and comprehensive evaluation of GC × GC software. Thereby, the benchmark data includes a set of standard compound measurements and a set of chocolate aroma profiles. On this foundation, eight readily available GC × GC software packages were anonymously investigated for fundamental and advanced functionalities such as retention and detection device derived parameters, revealing differences in the determination of e.g. retention times and mass spectra., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020. Published by Elsevier B.V.)

In this review, we consider and discuss the affinity and complementarity between a generic sample preparation technique and the comprehensive two-dimensional gas chromatography process. From the initial technical development focus (e.g., on the GC×GC and solid-phase microextraction techniques), the trend is inevitably shifting toward more applied challenges, and therefore, the preparation of the sample should be carefully considered in any GC×GC separation for an overreaching research. We highlight recent biomedical, food, and plant applications (2016-July 2020), and specifically those in which the combination of tailored sample preparation methods and GC×GC-MS has proven to be beneficial in the challenging aspects of non-targeted analysis. Specifically on the sample preparation, we report on gas-phase, solid-phase, and liquid-phase extractions, and derivatization procedures that have been used to extract and prepare volatile and semi-volatile metabolites for the successive GC×GC analysis. Moreover, we also present a milestone section reporting the early works that pioneered the combination of sample preparation techniques with GC×GC for non-targeted analysis., (© 2020 Wiley-VCH GmbH.)

A wide variety of biomass, from triglycerides to lignocellulosic-based feedstock, are among promising candidates to possibly fulfill requirements as a substitute for crude oils as primary sources of chemical energy feedstock. During the feedstock processing carried out to increase the H:C ratio of the products, heteroatom-containing compounds can promote corrosion, thus limiting and/or deactivating catalytic processes needed to transform the biomass into fuel. The use of advanced gas chromatography techniques, in particular multi-dimensional gas chromatography, both heart-cutting and comprehensive coupled to mass spectrometry, has been widely exploited in the field of petroleomics over the past 30 years and has also been successfully applied to the characterization of volatile and semi-volatile compounds during the processing of biomass feedstock. This review intends to describe advanced gas chromatography-mass spectrometry-based techniques, mainly focusing in the period 2011-early 2020. Particular emphasis has been devoted to the multi-dimensional gas chromatography-mass spectrometry techniques, for the isolation and characterization of the oxygen-containing compounds in biomass feedstock. Within this context, the most recent advances to sample preparation, derivatization, as well as gas chromatography instrumentation, mass spectrometry ionization, identification, and data handling in the biomass industry, are described., (© 2020 Wiley-VCH GmbH.)

Chronic inflammatory lung diseases impact more than 300 million of people worldwide. Because they are not curable, these diseases have a high impact on both the quality of life of patients and the healthcare budget. The stability of patient condition relies mostly on constant treatment adaptation and lung function monitoring. However, due to the variety of inflammation phenotypes, almost one third of the patients receive an ineffective treatment. To improve phenotyping, we evaluated the complementarity of two techniques for exhaled breath analysis: full resolving comprehensive two-dimensional gas chromatography coupled to high-resolution time-of-flight mass spectrometry (GC × GC-HRTOFMS) and rapid screening selected ion flow tube MS (SIFT-MS). GC × GC-HRTOFMS has a high resolving power and offers a full overview of sample composition, providing deep insights on the ongoing biology. SIFT-MS is usually used for targeted analyses, allowing rapid classification of samples in defined groups. In this study, we used SIFT-MS in a possible untargeted full-scan mode, where it provides pattern-based classification capacity. We analyzed the exhaled breath of 50 asthmatic patients. Both techniques provided good classification accuracy (around 75%), similar to the efficiency of other clinical tools routinely used for asthma phenotyping. Moreover, our study provides useful information regarding the complementarity of the two techniques.

Introduction: Colorectal cancer is one of the most diagnosed cancers, leading to numerous deaths. In addition to existing screening methods, metabolic profiling could help both to diagnose and to understand the various states of the disease., Objectives: Find specific candidate biomarkers (CB) in serum of patients with colorectal cancer (CRC), in comparison to the situation after remission (R-CRC), evaluated on distinct patients., Methods: All serum samples were analyzed using comprehensive two-dimensional gas chromatography (GC × GC) coupled to high resolution time of flight mass spectrometry (TOF-MS) through an optimized and validated untargeted analytical method regulated by a quality control (QC) system. First, we used a specific multi-approaches data (pre)processing workflow to highlight, annotate and assess the performances of the most altered metabolites between CRC patients (n = 18) and healthy control samples (HC, n = 19) specifically matched for age and gender, two of the most influential confounding factors. On the contrary, due to the difficulty to control for all clinical and demographic traits when sampling small cohorts, the samples from patients in remission (n = 17) were not matched. Because of the consequent risk of bias, the usual null hypothesis significance tests (NHST) could not be applied reliably. Therefore, we compared the R-CRC samples to another specifically matched group of healthy controls (R-HC, n = 17), and used this comparison to indirectly address the difference between patients with colorectal cancer and patients in remission through a measure called effect size (ES) whose methodological aspects were investigated., Results: 24 candidate biomarkers were found significantly altered and able to discriminate the CRC and HC samples efficiently (Receiver Operating Characteristic (ROC) area under the curve (AUC) of 0.86, sensitivity and specificity of 0.72 and 0.78). 10 of those were found to have signals close to healthy levels in the R-CRC samples and were therefore specific to colorectal cancer. In the point-biserial case studied here, r-like (strength of association) and d-like (standardized mean difference) ES were directly convertible and only linear and rank-based ES were different. We therefore used and recommend Hedges' g, Spearman's rho and Kendall's tau, along with an unstandardized ES. The confidence intervals, that quantify the uncertainty of the measure, were well represented through scatterplots and distribution curves., Conclusion: The candidate biomarkers found, along with their specificity, could help for the detection of colorectal cancer, the diagnosis of remission, and for the understanding of its pathophysiology, after proper validation on independent cohorts. The effect size, here applied on a MS global profiling data set, is an ideal complement to NHST and a useful tool to compare and combine distinct cohorts, within a study as well as between studies (meta-analysis).

Sampling of volatile organic compounds (VOCs) has shown promise for detection of a range of diseases but results have proved hard to replicate due to a lack of standardization. In this work we introduce the 'Peppermint Initiative'. The initiative seeks to disseminate a standardized experiment that allows comparison of breath sampling and data analysis methods. Further, it seeks to share a set of benchmark values for the measurement of VOCs in breath. Pilot data are presented to illustrate the standardized approach to the interpretation of results obtained from the Peppermint experiment. This pilot study was conducted to determine the washout profile of peppermint compounds in breath, identify appropriate sampling time points, and formalise the data analysis. Five and ten participants were recruited to undertake a standardized intervention by ingesting a peppermint oil capsule that engenders a predictable and controlled change in the VOC profile in exhaled breath. After collecting a pre-ingestion breath sample, five further samples are taken at 2, 4, 6, 8, and 10 h after ingestion. Samples were analysed using ion mobility spectrometry coupled to multi-capillary column and thermal desorption gas chromatography mass spectrometry. A regression analysis of the washout data was used to determine sampling times for the final peppermint protocol, and the time for the compound measurement to return to baseline levels was selected as a benchmark value. A measure of the quality of the data generated from a given technique is proposed by comparing data fidelity. This study protocol has been used for all subsequent measurements by the Peppermint Consortium (16 partners from seven countries). So far 1200 breath samples from 200 participants using a range of sampling and analytical techniques have been collected. The data from the consortium will be disseminated in subsequent technical notes focussing on results from individual platforms.

Exhaled breath analysis has a high potential for early non-invasive diagnosis of lung inflammatory diseases, such as asthma. The characterization and understanding of the inflammatory metabolic pathways involved into volatile organic compounds (VOCs) production could bring exhaled breath analysis into clinical practice and thus open new therapeutic routes for inflammatory diseases. In this study, lung inflammation was simulated in vitro using A549 epithelial cells. We compared the VOC production from A549 epithelial cells after a chemically induced oxidative stress in vitro, exposing the cells to H 2 O 2 , and a biological stress, exposing the cells to an inflammatory pool of sputum supernatants. Special attention was devoted to define proper negative and positive controls (8 different types) for our in vitro models, including healthy sputum co-culture. Sputum from 25 asthmatic and 8 healthy patients were collected to create each pool of supernatants. Each sample type was analyzed in 4 replicates using solid-phase microextraction (SPME) comprehensive two-dimensional gas chromatography hyphenated to time-of-flight mass spectrometry (GC×GC-TOFMS). This approach offers high resolving power for complex VOC mixtures. According to the type of inflammation induced, significantly different VOCs were produced by the epithelial cells compared to all controls. For both chemical and biological challenges, an increase of carbonyl compounds (54%) and hydrocarbons (31%) was observed. Interestingly, only the biological inflammation model showed a significant cell proliferation together with an increased VOC production linked to asthma airway inflammation. This study presents a complete GC×GC-TOFMS workflow for in vitro VOC analysis, and its potential to characterize complex lung inflammatory mechanisms.

The present research reports on the development of a methodology to unravel the complex phytochemistry of cannabis. Specifically, cannabis inflorescences were considered and stir bar sorptive extraction (SBSE) was used for the preconcentration of the metabolites. Analytes were thermally desorbed into a comprehensive two-dimensional (2D) gas chromatography (GC × GC) system coupled with low- and high-resolution mass spectrometry (MS). Particular attention was devoted to the optimization of the extraction conditions, to extend the analytes' coverage, and the chromatographic separation, to obtain a robust data set for further untargeted analysis. Monoterpenes, sesquiterpenes, hydrocarbons, cannabinoids, other terpenoids, and fatty acids were considered to optimize the extraction conditions. The response of selected ions for each chemical class, delimited in specific 2D chromatographic regions, enabled an accurate and fast evaluation of the extraction variables (i.e., time, temperature, solvent, salt addition), which were then selected to have a wide analyte selection and good reproducibility. Under optimized SBSE conditions, eight different cannabis inflorescences and a quality control sample were analyzed and processed following an untargeted and unsupervised approach. Principal component analysis on all detected metabolites revealed chemical differences among the sample types which could be associated with the plant subspecies. With the same SBSE-GC × GC-MS methodology, a quantitative targeted analysis was performed on three common cannabinoids, namely, Δ9-tetrahydrocannabinol, cannabidiol, and cannabinol. The method was validated, giving correlation factors over 0.98 and <20% reproducibility (relative standard deviation). The high-resolution MS acquisition allowed for high-confidence identification and post-targeted analysis, confirming the presence of two pesticides, a plasticizer, and a cannabidiol degradation product in some of the samples.

There has been an influx of technology for comprehensive two-dimensional gas chromatography analyses in recent years, calling for development of guided workflows and rigorous reporting of processes. This research focuses on the processing method for data collected on a dual channel detection system using flame ionization detection (FID) and quadrupole mass spectrometry (qMS) for the analysis of volatile organic compounds (VOCs). The samples analyzed were kava ( Piper methysticum ), which has a rich VOC profile that benefits substantially from a multidimensional approach due to enhanced peak capacity. The procedure which was customized here was the data processing workflow from a manual single-sample analysis to an integrated batch workflow that can be applied across studies.•Parameter choice for baseline correction and peak detection were defined when handling batch data.•Elution regions were defined using qMS data to automate compound identification.•Stencils were transformed onto FID data and sequenced for quantitative information.This dataset can be used as a training tool, as all details, methods and results for the workflow have been provided for users to compare with. The focus on data workflow reproducibility in the field of multidimensional chromatography will assist in adoption by users in new application areas., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2020 The Author(s).)

After its introduction in the early 1990s, comprehensive two-dimensional gas chromatography (GC×GC) has evolved from a separation science research tool to the central component of many industries. Despite the maturity of the technique, some fields remain reluctant to its use in routine applications. In the case of forensic science, some constraints are the strict requirements enforced in forensic laboratories and the time and effort that must be invested for intralaboratory method validation. Concerns may also arise about whether information could be lost when transitioning to a new technique. This study reports on a method translation from conventional one-dimensional (1D) GC to GC×GC, ensuring the integrity of data as conversion is made. The GC was retrofitted with a reverse fill/flush (RFF) flow modulator and equipped with dual-channel detection using a quadrupole mass spectrometer (qMS) and a flame ionization detector (FID). The parallel use of two detectors, where qMS was applied for qualitative identification and FID for quantification, allowed higher flows and slightly wider peaks to be exploited for the analysis of a volatile organic compound (VOC) reference mixture relevant to forensic VOC profiling. Peak quality assessment and calibration curves using GC-qMS and GC×GC-qMS/FID document the transfer and adaptation of the original method without a loss in data quality. Furthermore, the preprocessing and the data analysis processing steps, including calibration and peak quality assessment for each of the three data sets, are explained in detail. This information provides benchmark data for routine laboratories that want to implement a GC×GC approach into routine workflows.

Headspace gas chromatography is frequently used for aroma profiling thanks to its ability to naturally exploit the volatility of aroma compounds, and also to provide chemical information on sample composition. Its main advantages rely on simplicity, no use of solvent, amenability to automation, and the cleanliness of the extract. In the present contribution, the most effective sampling (dynamic extraction), separation (multidimensional gas chromatography), and detection (mass spectrometry) techniques for untargeted analysis are exploited in combination, showing their potential in unraveling aroma profiles in fruit beers. To complete the overall analytical process, a neat workflow for data analysis is discussed and used for the successful characterization and identification of five different beer flavors (berries, cherry, banana, apple, and peach). From the technical viewpoint, the coupling of purge-and-trap, comprehensive two-dimensional gas chromatography, and mass spectrometry makes the global methodology unique, and it is for the first time discussed. A (low-)flow modulation approach allowed for the full transfer into the second dimension with mass-spectrometry compatible flow (< 7 mL/min), avoiding the need of splitting before detection and making the overall method sensitive (1.2-5.2-fold higher signal to noise ratio compared to unmodulated gas chromatography conditions) and selective., (© 2019 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

While many laboratories take appropriate care, there are still cases where the performances of untargeted profiling methods suffer from a lack of design, control, and articulation of the various steps involved. This is particularly harmful to modern comprehensive analytical instrumentations that otherwise provide an unprecedented coverage of complex matrices. In this work, we present a global analytical workflow based on comprehensive two-dimensional gas chromatography coupled to high-resolution time-of-flight mass spectrometry. It was optimized for sample preparation and chromatographic separation and validated on in-house quality control (QC) and NIST SRM 1950 samples. It also includes a QC procedure, a multiapproach data (pre)processing workflow, and an original bias control procedure. Compounds of interest were identified using mass, retention, and biological information. As a proof of concept, 35 serum samples representing three subgroups of Crohn's disease (with high, low, and quiescent endoscopic activity) were analyzed along with 33 healthy controls. This led to the selection of 33 unique candidate biomarkers able to classify the Crohn's disease and healthy samples with an orthogonal partial least-squares discriminant analysis Q 2 of 0.48 and a receiver-operating-characteristic area under the curve of 0.85 (100% sensitivity and 82% specificity in cross validation). Fifteen of these 33 candidates were reliably annotated (Metabolomics Standards Initiative level 2).

An analytical methodology based on thermal desorption and comprehensive two-dimensional gas chromatography with dual time-of-flight mass spectrometry and flame ionization detection (TD-GC × GC-TOFMS/FID) has been developed for non-target analysis of volatile organic compounds (VOCs). The technique was optimised for the measurement of the VOC content of the particulate phase (PP) fraction of aerosols produced by a tobacco heating product (THP1.0) and 3R4F mainstream tobacco smoke (MTS). The method involves sampling the PP fraction on quartz wool packed in a sorbent tube directly connected to machine-puffing, followed by a dilution through a TD recollection procedure over Tenax/Sulficarb sorbent before TD-GC × GC-TOFMS/FID analysis. The comparison of the VOC content of the PP fraction of aerosols produced by THP1.0 and MTS highlighted the compositional difference between tobacco combustion (592 peaks) and tobacco heating process (160 peaks). Mass spectrometric signals were used for qualitative analyses based on linear retention indices, mass spectral matches, and GC × GC structured chromatograms, which collectively identified up to 90% of analytes detected in PP samples. FID signals were used for semi-quantitative analyses based on a chemical class external calibration method. The global chemical composition of PP samples showed that hydrocarbons, oxygenated, and nitrogen-containing compounds were fewer in number and much less abundant in THP1.0 PP. Overall, 93 compounds were common to the two sample types. Excepted for a few highly volatile compounds (mainly furan family) as well as glycerine and its acetate, analyte concentrations were higher in MTS PP., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Rationale: Analysis of exhaled breath for asthma phenotyping using endogenously generated volatile organic compounds (VOCs) offers the possibility of noninvasive diagnosis and therapeutic monitoring. Induced sputum is indeed not widely available and markers of neutrophilic asthma are still lacking. Objectives: To determine whether analysis of exhaled breath using endogenously generated VOCs can be a surrogate marker for recognition of sputum inflammatory phenotypes. Methods: We conducted a prospective study on 521 patients with asthma recruited from the University Asthma Clinic of Liege. Patients underwent VOC measurement, fraction of exhaled nitric oxide (Fe NO ) spirometry, sputum induction, and gave a blood sample. Subjects with asthma were classified in three inflammatory phenotypes according to their sputum granulocytic cell count. Measurements and Main Results: In the discovery study, seven potential biomarkers were highlighted by gas chromatography-mass spectrometry in a training cohort of 276 patients with asthma. In the replication study ( n  = 245), we confirmed four VOCs of interest to discriminate among asthma inflammatory phenotypes using comprehensive two-dimensional gas chromatography coupled to high-resolution time-of-flight mass spectrometry. Hexane and 2-hexanone were identified as compounds with the highest classification performance in eosinophilic asthma with accuracy comparable to that of blood eosinophils and Fe NO . Moreover, the combination of Fe NO , blood eosinophils, and VOCs gave a very good prediction of eosinophilic asthma (area under the receiver operating characteristic curve, 0.9). For neutrophilic asthma, the combination of nonanal, 1-propanol, and hexane had a classification performance similar to Fe NO or blood eosinophils in eosinophilic asthma. Those compounds were found in higher levels in neutrophilic asthma. Conclusions: Our study is the first attempt to characterize VOCs according to sputum granulocytic profile in a large population of patients with asthma and provide surrogate markers for neutrophilic asthma.

Polychlorodibenzo- p -dioxins (PCDDs), polychloro-dibenzofurans (PCDFs), dioxin-like (DL), and non dioxin-like (NDL) polychlorinated biphenyls (PCBs) are currently regulated in food and feed within the European territory (EU 2017/644-771). The confirmatory methods of analysis for checking compliance with maximum levels (MLs) for these involve either the historically-established GC-magnetic sector high-resolution mass spectrometry (GC-HRMS) and, more recently, GC-triple quadrupole mass spectrometry operating in tandem mode (GC-QQQMS/MS). In this study, the performance of a novel triple quadrupole GC-QQQMS/MS system equipped with a programable temperature vaporization (PTV) injector was evaluated for the analysis of regulated PCDD/Fs and PCBs in food and feed. The MS analyzer was equipped with a titanium ionization chamber and a new short collision cell capable to accumulate and eject ions by means of very narrow pulses that allow to minimize the noise and to adapt accumulation times for sensitive multiple reaction monitoring (MRM). The analytical capability of the system was confronted by the strict requirements (selectivity, reproducibility, linearity, quant/qual MRM transitions, accuracy, robustness) set by the EU Regulation for a range of standards, quality control (QC) and food/feed samples. In this respect, the approach showed high precision (1.9-15% relative standard deviation (RSD) at low pg/µL) and accuracy (>80%, except for one hexa-CDD). The quantitative results were also compared to the most used GC-HRMS. In this case, comparable results in terms of single congener concentration basis and total toxic equivalent (TEQ) basis for PCDD/Fs and DL-PCBs were obtained for the QC samples analyzed.

Lung cancer is the deadliest cancer in developed countries. To reduce its mortality rate, it is important to enhance our capability to detect it at earlier stages by developing early diagnostic methods. In that context, the analysis of exhaled breath is an interesting approach because of the simplicity of the medical act and its non-invasiveness. Thermal desorption comprehensive two-dimensional gas chromatography time of flight mass spectrometry (TD-GC × GC-TOFMS) has been used to characterize and compare the volatile content of human breath of lung cancer patients and healthy volunteers. On the sampling side, the contaminations induced by the bags membrane and further environmental migration of VOCs during and after the sampling have also been investigated. Over a realistic period of 6 h, the concentration of contaminants inside the bag can increase from 2 to 3 folds based on simulated breath samples. On the data processing side, Fisher ratio (FR) and random forest (RF) approaches were applied and compared in regards to their ability to reduce the data dimensionality and to extract the significant information. Both approaches allow to efficiently smooth the background signal and extract significant features (27 for FR and 17 for RF). Principal component analysis (PCA) was used to evaluate the clustering capacity of the different models. For both approaches, a separation along PC-1 was obtained with a variance score around 35%. The combined model provides a partial separation with a PC-1 score of 52%. This proof-of-concept study further confirms the potential of breath analysis for cancer detection but also underlines the importance of quality control over the full analytical procedure, including the processing of the data., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Comprehensive two-dimensional gas chromatography (GC × GC) coupled to time-of-flight mass spectrometry is a powerful separation tool for complex petroleum product analysis. However, the most commonly used electron ionization (EI) technique often makes the identification of the majority of hydrocarbons impossible due to the exhaustive fragmentation and lack of molecular ion preservation, prompting the need of soft-ionization energies. In this study, three different soft-ionization techniques including photo ionization (PI), chemical ionization (CI), and field ionization (FI) were compared against EI to elucidate their relative capabilities to reveal different base oil hydrocarbon classes. Compared with EI (70 eV), PI (10.8 eV) retained significant molecular ion (M +· ) information for a large number of isomeric species including branched-alkanes and saturated monocyclic hydrocarbons along with unique fragmentation patterns. However, for bicyclic/polycyclic naphthenic and aromatic compounds, EI played upper hand by retaining molecular as well as fragment ions to identify the species, whereas PI exhibited mainly molecular ion signals. On the other hand, CI revealed selectivity towards different base oil groups, particularly for steranes, sulfur-containing thiophenes, and esters, yielding protonated molecular ions (M + H) + for unsaturated and hydride abstracted ions (M-H + ) for saturated hydrocarbons. FI, as expected, generated intact molecular ions (M +· ) irrespective to the base oil chemical classes. It allowed elemental composition by TOFMS with a mass resolving power up to 8000 (FWHM) and a mass accuracy of 1 mDa, leading to the calculation of heteroatomic content, double bond equivalency, and carbon number of the compounds. The qualitative and quantitative results presented herein offer a unique perspective into the detailed comparison of different ionization techniques corresponding to several hydrocarbon classes., (© 2018 John Wiley & Sons, Ltd.)