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The presence of organic compounds on the particulate matter (PM) or aerosols can arise from the condensation of gaseous organic compounds on the existing aerosols, or from organic precursors to form secondary organic aerosols (SOA) through photochemistry. The objective of this study is to characterize organic constituents on aerosols relevant to their emission sources and the key compounds revealing the evolution of aerosols with the use of a novel analytical technique. A time-of-flight mass spectrometry (TOFMS) coupled with comprehensive two-dimensional gas chromatography (GC×GC) was developed using a flow type of modulator instead of a thermal type as a prelude to field applications without the need for cryogen. The methodology of GC×GC-TOFMS is discussed in this study in detail. Since the coarse PM (PM10-2.5) may exhibit with a relatively high OC content compared to PM2.5, the GC×GC results have been obtained by analyzing PM10 samples collected in parallel with OC/EC analysis of PM2.5 samples at the Lulin Atmospheric Background Station (LABS, 23.47°N, 120.87°E, 2862 m ASL) as the high-mountain background site in East Asia. We found that the organic analytes were in a majority in the range of 12-30 carbon numbers falling in the category of semi-volatile organic compounds (SVOCs) with 43 compounds of alcohol, aldehyde, ketone, and ester varieties if excluding alkanes. Intriguingly, trace amounts of plasticizers and phosphorus flame retardants such as phthalates (PAEs) and triphenyl phosphate (TPP) were also found, likely originating from regions involved in open burning of household solid waste in Southeast Asia or e-waste recycling in southern China and along the long-range transport route. Compounds such as these are unique to the specific sources, demonstrating the wide spread of these hazardous compounds in the environment.

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Fifty-six samples of differently produced commercial Italian ciders were analysed for semi-volatile organic compounds (SVOCs) profiling, using comprehensive two-dimensional gas chromatography coupled to mass spectrometry (GC×GC-TOF-MS) technique for the very first time. To properly support the compositional investigation of this emerging beverage, a chemometric approach through Principal Component Analysis (PCA) was employed. This revealed a sample distribution in agreement with results of the sensory tasting panel performed on such ciders, highlighting an excellent correlation between variables and perceived odorants. In particular, the positions of peculiar and anomalous objects in the Principal Components (PCs) space are explicitly evaluated, exploring the associated loadings (i.e., the importance of the identified chemical compounds), paying attention to their biochemical origin along the cider-making process and their impact on the sample olfactory analysis. Besides this, the t-distributed Stochastic Neighbor Embedding (t-SNE) method was shown to be an efficient tool for gathering pear ciders from the other samples (apple ciders), better than PCA. This study stands for the first survey on Italian commercial craft cider, and its results are aimed to be a milestone for its characterization and to start and promote cider culture in this country.

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Off-flavors are a major challenge for companies using recirculated aquaculture systems (RAS). In the presented work, we comprehensively characterize the odorant composition of Nile tilapia (Oreochromis niloticus) raised in RAS and compare the impact of two depuration processes on the odorant composition and aroma profile of the fish. Fish collected from the production tank and after two different tank pre-disinfection approaches in the depuration process (high pH versus H2O2) were investigated. A combined sensory-instrumental investigation revealed the presence of 115 odorants, of which 83 were successfully identified. The compounds decanal, tridecanal, (Z)-1,5-octadien-3-one, octane-2,3-dione, benzophenone, non-3-yn-1-ol, γ-dodecalactone, (Z)-geranylacetone, 2,3-diethyl-5-methylpyrazine, 1-methylpyrrolidin-2-one, 2-acetyl-2-thiazoline, benzothiazole, skatole, and 5α-androst-16-en-3-one were detected with the highest flavor dilution factors and are described for the first time as odor-active compounds in fish from RAS. The results indicate that depuration decreased the levels of 78 different odorants from the fish, including the potent earthy smelling odorants geosmin, isoborneol and 2,3-diethyl-5-methylpyrazine.

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Exhaled breath volatilomics is a powerful non-invasive tool for biomarker discovery in medical applications, but compound annotation is essential for pathophysiological insights and technology transfer. This study was aimed at investigating the interest of a hybrid approach combining real-time proton transfer reaction-time-of-flight mass spectrometry (PTR-TOF-MS) with comprehensive thermal desorption-two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (TD-GCxGC-TOF-MS) to enhance the analysis and characterization of VOCs in clinical research, using COVID-19 as a use case. VOC biomarker candidates were selected from clinical research using PTR-TOF-MS fingerprinting in patients with COVID-19 and matched to the Human Breathomic Database. Corresponding analytical standards were analysed using both a liquid calibration unit coupled to PTR-TOF-MS and TD-GCxGC-TOF-MS, together with confirmation on new clinical samples with TD-GCxGC-TOF-MS. From 26 potential VOC biomarkers, 23 were successfully detected with PTR-TOF-MS. All VOCs were successfully detected using TD-GCxGC-TOF-MS, providing effective separation of highly chemically related compounds, including isomers, and enabling high-confidence annotation based on two-dimensional chromatographic separation and mass spectra. Four VOCs were identified with a level 1 annotation in the clinical samples. For future applications, the combination of real-time PTR-TOF-MS and comprehensive TD-GCxGC-TOF-MS, at least on a subset of samples from a whole study, would enhance the performance of VOC annotation, offering potential advancements in biomarker discovery for clinical research.

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In this study, we aimed to assess the feasibility of re-collecting breath samples using the Centri® (Markes International, Bridgend, UK) followed by two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC×GC-TOFMS) analysis. The work was conducted in two main phases. In the first phase, we evaluated the re-collection performance by analyzing two sets of standards, including a Grob mix primary solution and a standard mixture of 20 selected volatile compounds (VCs) covering different classes of organic species commonly found in breath samples. The intra-day and inter-day precision (reported as relative standard deviation (RSD),%) for the re-collection of the Grob mix primary solution were in the range of 1 % to14 % and 3 % to12 %, respectively. The re-collection accuracy ranged from 78 % to 97 %. The intra-day RSD for the re-collection of the standard mixture of selected VCs was within 20 % for all compounds, except for acetone and nonane. The precision was within 25 % for all compounds, except for nonane, n-hexane, 1,4-dichlorobenzene, and decane, which exhibited less than 36 % RSD. The re-collection accuracy was in the range of 67 % to 129 %. In the second phase of the study, the re-collection performance in breath analysis was evaluated via five repetitive splitting and re-collection of six breath samples obtained from healthy adults, realizing a total of 30 breath analyses. Initially, we evaluated the re-collection performance by considering all features obtained from breath analysis and then focused on the 20 VCs commonly found in breath samples. The re-collection accuracy for total breath features ranged from 86 to 103 %, and the RSDs were in the range of 1.0 % to 10.4 %. For the selected VCs, the re-collection accuracy of all compounds, except for undecane and benzene, was in the range of 71 % to 132 %.

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Herein, two "orthogonal" characteristics of moisture damaged cacao beans (temporally dependent molding kinetics versus the time-independent geographical region of origin) are simultaneously analyzed in a comprehensive two-dimensional (2D) gas chromatography time-of-flight mass spectrometry (GC×GC-TOFMS) dataset using tile-based Fisher ratio (F-ratio) analysis. Cacao beans from six geographical regions were analyzed once a day for six days following the initiation of moisture damage to trigger the molding process. Thus, there are two "extremes" to the experimental sample class design: six time points for the molding kinetics versus the six geographical regions of origin, resulting in a 6 × 6 element signal array referred to as a composite chemical fingerprint (CCF) for each analyte. Usually, this study would involve initial generation of two separate hit lists using F-ratio analysis, one hit list from inputting the data with the six time point classes, then another hit list from inputting the dataset from the perspective of geographic region of origin. However, analysis of two separate hit lists with the intent to distill them down to one hit list is extremely time-consuming and fraught with shortcomings due to the challenges associated with attempting to match analytes across two hit lists. To address this challenge, tile-based F-ratio analysis is "orthogonally applied" to each analyte CCF to simultaneously determine two F-ratios at the chromatographic 2D location (F-ratiokinetic and F-ratioregion) for each hit, by ranking a single hit list using the higher of the two F-ratios resulting in the discovery of 591 analytes. Further, using a pseudo-null distribution approach, at the 99.9% threshold over 400 analytes were deemed suitable for PCA classification. Using a more stringent 99.999% threshold, over 100 analytes were explored more deeply using PARAFAC to provide a purified mass spectrum.

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The monitoring of organic compounds in aquatic matrices poses challenges due to its complexity and time-intensive nature. To address these challenges, we introduce a novel approach utilizing a dual-channel mono (1D) and comprehensive two-dimensional (2D) gas chromatography coupled with time-of-flight mass spectrometry (GC × GC-TOFMS) system, integrated with a robotic pretreatment platform, for online monitoring of both volatile organic compounds (VOCs) and semivolatile organic compounds (SVOCs) in water matrices. Employing the robotic platform, we establish a suite of online liquid-liquid extraction (LLE) pretreatment processes for water samples, marking the first instance of such procedures. Leveraging the automatic headspace (HS) module, dual robotic preparations of HS and LLE are sequentially executed to extract VOCs and SVOCs from water matrices. The GC × GC-TOFMS system is distinguished by its dual-channel analytical column configuration, facilitating sequential analysis of VOCs in GC-TOFMS mode and SVOCs in GC × GC-TOFMS mode. Quantitative detection of 55 target VOCs and 104 SVOCs is achieved in a water sample using the instrument system. Our method demonstrates excellent correlation coefficients ranging from 0.990 to 1.000, method detection limits ranging from 0.08 to 4.78 µg L-1, relative standard deviations below 19.3 %, and recovery rates ranging from 50.0 % to 124.0 %. To validate the online monitoring capabilities of our system, we assess target SVOCs at three different concentration levels over a 3-day period. Most compounds exhibit recovery rates ranging from 70.0 % to 130.0 %. Furthermore, we apply our method to analyze a real water sample, successfully identifying over 100 target and nontarget VOCs/SVOCs, including alcohols, aldehydes, ketones, acids, esters, and phenols. These results highlight the efficacy of the proposed analysis system, capable of conducting two distinct analyses in automatic sequence, thereby enhancing the efficiency and accuracy of organic compound analysis in water matrices.

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This study integrates genetic algorithm (GA) with partial least squares regression (PLSR) and various variable selection methods to identify impactful regions of interest (ROI) in heterogeneous 2D chromatogram images for predicting wine age. As wine quality and aroma evolve over time, transitioning from youthful fruitiness to mature, complex flavors, which leads to alterations in the composition of essential aroma-contributing compounds. Chromatograms are segmented into subimages, and the GA-PLSR algorithm optimizes combinations based on grayscale, red-green-blue (RGB), and hue-saturation-value (HSV) histograms. The selected subimage histograms are further refined through interval selection, highlighting the compounds with the most significant influence on wine aging. Experimental validation involving 38 wine samples demonstrates the effectiveness of this approach. Cross-validation reduces the PLS model error from 2.8 to 2.4 years within a 10 × 10 subset, and during prediction, the error decreases from 2.5 to 2.3 years. The study presents a novel approach utilizing the selection of ROI for efficient processing of 2D chromatograms focusing on predicting wine age.

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The present research is focused on the proposal of use of flow-modulation comprehensive two-dimensional enantio-gas chromatography (FM eGC × GC) as a valid, flexible, and possibly superior alternative to heart-cutting multidimensional enantio-GC (eMDGC). The latter, a technique of demonstrated utility, is used specifically for the targeted separation of chiral compounds, whereas FM eGC × GC can produce both targeted and high-resolution untargeted information in a single run. It is clearly possible to use eMDGC for untargeted analysis, often with a flame ionization detector (stand-by analysis), to monitor a first-dimension (1D) separation, of much lower peak capacity compared to FM eGC × GC. If eMDGC is used with mass spectrometry (MS), it is normally exploited to monitor the second-dimension (2D) separation. The analytical instrument consisted of automated solid-phase microextraction (SPME), and a low duty-cycle FM eGC × GC system (with time-of-flight MS), equipped with an enantioselective 1D column (2,3-di-O-methyl-6-t-butyl silyl ß-cyclodextrin derivative) and a 2D polyethylene glycol one. Ten Marsala wines were subjected to analysis, for the determination of chiral lactones (many at the low ppb level, due to the high concentration capacity of SPME) and for general analyte profiling. In many instances, highly complex chromatograms were attained, with statistical analysis (ANOVA-simultaneous component analysis and partial least squares discriminant analysis) used for sample differentiation.

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The impact of desalination brine on the marine environment is a global concern. Regarding this, salinity is generally accepted as the major environmental factor in desalination concentrate. However, recent studies have shown that the influence of organic contaminants in brine cannot be ignored. Therefore, a non-targeted screening method based on comprehensive two-dimensional gas chromatography-quadrupole mass spectrometry (GC × GC-qMS) was developed for identifying organic contaminants in the desalination brine. A total of 404 compounds were tentatively identified from four seawater desalination plants (three reverse osmosis plants and one multiple effect distillation plant) in China. The identified compounds were prioritized based on their persistence, bioaccumulation, ecotoxicity, usage, and detection frequency. Twenty-one (21) compounds (seven phthalates, ten pesticides, four trihalomethanes) were then selected for further quantitative analysis and ecological risk assessment, including compounds from the priority list along with substances from the same chemical classes. Ecologically risky substances in brine include diisobutylphthalate and bis(2-Ethylhexyl) phthalate, atrazine and acetochlor, and bromoform. Most of the contaminants come from raw seawater, and no high risk contaminants introduced by the desalination process have been found except for disinfection by-products. In brine discharge management, people believed that all pollution in raw seawater was concentrated by desalination process. This study shows that not all pollutants are concentrated during the desalination process. In this study, the total concentration of pesticide in the brine increased by 58.42%. The concentration of ∑PAEs decreased by 13.65% in reverse osmosis desalination plants and increased by 10.96% in the multi-effect distillation plant. The concentration of trihalomethane increased significantly in the desalination concentrate. The change in the concentration of pollutants in the desalination concentrate was related to the pretreatment method and the chemical characteristics of the contaminants. The method and results given in this study hinted a new idea to identify and control the environmental impact factors of brine.

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BACKGROUND: Omics 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. RESULTS: Α 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. SIGNIFICANCE: The 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.

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Some truffles are expensive and, therefore, are prone to food fraud. A particular problem is the differentiation of high-priced Tuber magnatum truffles from cheaper Tuber borchii truffles, both of which are white truffles with similar morphological characteristics. Using an untargeted approach, the volatiles isolated from samples of both species were screened for potential marker compounds by comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC×GC-TOFMS) and statistical analysis of the obtained semiquantitative data. Results suggested bis(methylsulfanyl)methane and furan-2(5H)-one as compounds characterizing T. magnatum and T. borchii, respectively. Exact quantitation of both volatiles by conventional one-dimensional gas chromatography-mass spectrometry in combination with stable isotopologues of the target compounds as internal standards confirmed both as marker compounds. The method is suitable to be used in the routine analysis for the objective species differentiation of T. magnatum and T. borchii.

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This work presents an accurate yet simplified partial least squares model to predict the kinematic viscosity of conventional and alternative jet fuels at -20°C using comprehensive two-dimensional gas chromatography coupled to a flame ionization detector (GC × GC/FID). Three different normalization methods (mean-centering, logarithmic, and Yeo-Johnson) were evaluated to identify their impact in the prediction of middle distillates' physical properties. Results using Yeo-Johnson transformation exhibited improved viscosity prediction capabilities over the validation set with a mean absolute percentage error of 5.3%, a root-mean-squared error of 0.23, and a coefficient of determination (R2 ) of 0.9404 using only 10 latent variables. Unlike previously reported correlations, this model allowed the identification of specific hydrocarbon groups and carbon numbers that drive jet fuel viscosity at low temperatures. The presence of even small amounts of large branched-alkanes (C15 -C17 ), dicyclic-alkanes (C10 ), and cycloaromatics (C11 ) have the potential to strongly increase the kinematic viscosity of jet fuels. Contrastingly, light monocycloalkanes and branched-alkanes (≤ C10 ) were associated with lower viscosity values. Novelly, this model suggests the implementation of Yeo-Johnson transformations to predict the physical properties of middle distillates to further improve the performance metrics of partial least squares models based on GC data.

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Our objective was to analyze the changes in fatty acid (FA) profiles of bovine colostrum and immature milk during the first four days of lactation and assess their potential impact on human health. Colostrum and immature milk samples were collected from Czech Fleckvieh cows during their first to third lactation and the FA profiles were analyzed using multidimensional gas chromatography with a vacuum ultraviolet detector (GC×GC-VUV). The colostrum of primiparous cows contained lower levels of medium-chain and saturated fatty acids, and higher levels of mono- and unsaturated fatty acids compared to that of multiparous cows. The atherogenic and thrombogenicity indexes, as well as the hypocholesterolemic-to-hypercholesterolemic fatty acid ratio, were more favourable in primiparous cows. This makes colostrum fat an attractive product for human nutrition. To obtain the maximum health benefits, we recommend collecting and processing the colostrum of primiparous cows and immature milk at the end of the milk transition separately.

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The formidable challenge posed by the presence of extremely high amounts of compounds and large differences in concentrations in plasma significantly complicates non-targeted metabolomics analyses. In this study, a comprehensive two-dimensional gas chromatography-quadrupole mass spectrometry (GC×GC-qMS) method with a solid-state modulator (SSM) for non-targeted metabolomics in beagle plasma was first established based on a GC-MS method, and the qualitative and quantitative performance of the two platforms were compared. Identification of detected compounds was accomplished utilizing NIST database match scores, retention indices (RIs) and standards. Semi-quantification involved the calculation of peak area ratios to internal standards. Metabolite identification sheets were generated for plasma samples on both analytical platforms, featuring 22 representative metabolites chosen for validating qualitative accuracy, and for conducting comparisons of linearity, accuracy, precision, and sensitivity. The outcomes revealed a threefold increase in the number of identifiable metabolites on the GC×GC-MS platform, with lower limits of quantitation (LLOQs) reduced to 0.5-0.05 times those achieved on the GC-MS platform. Accuracy in quantification for both GC×GC-MS and GC-MS fell within the range of 85-115%, and the vast majority of intra- and inter-day precisions were within the range of 20%. These findings underscore that relative to the conventional GC-MS method, the GC×GC-MS method developed in this study, combined with SSM, exhibits enhanced qualitative capabilities, heightened sensitivity, and comparable accuracy and precision, rendering it more suitable for non-targeted metabolomics analyses.

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Carbohydrates, in particular the d-enantiomers of ribose, 2-deoxyribose, and glucose, are essential to life's informational biopolymers (RNA/DNA) and for supplying energy to living cells through glycolysis. Considered to be potential biosignatures in the search of past or present life, our capacity to detect and quantify these essential sugars is crucial for future space missions to the Moon, Mars or Titan as well as for sample-return missions. However, the enantioselective analysis of carbohydrates is challenging and both research and routine applications, are lacking efficient methods that combine highly sensitive and reproducible detection with baseline enantioselective resolution and reliable enantiomeric excess (ee) measurements. Here, we present four different derivatization strategies in combination with multidimensional gas chromatography coupled to a reflectron time-of-flight mass spectrometer (GC×GC-TOF-MS) for the enantioselective resolution of C3 to C6 carbohydrates potentially suitable for sample-return analyses. Full mass spectral interpretation and calibration curves for one single-step (cyclic boronate derivatives) and three two-step derivatization protocols (aldononitrile-acetate, hemiacetalization-trifluoroacetylation, and hemiacetalization-permethylation) are presented for concentrations ranging from 1 to 50 pmol µL⁻1 with correlation coefficients R2 > 0.94. We compared several analytical parameters including reproducibility, sensitivity (LOD and LOQ), overall separation, chiral resolution (RS), mass spectrum selectivity, stability during long term storage, and reliability of ee measurements to guide the application-dependent selection of optimal separation and quantification performance.

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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.

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Traditional Chinese medicines (TCMs) possess a rich historical background, unique theoretical framework, remarkable therapeutic efficacy, and abundant resources. However, the modernization and internationalization of TCMs have faced significant obstacles due to their diverse ingredients and unknown mechanisms. To gain deeper insights into the phytochemicals and ensure the quality control of TCMs, there is an urgent need to enhance analytical techniques. Currently, two-dimensional (2D) chromatography, which incorporates two independent separation mechanisms, demonstrates superior separation capabilities compared to the traditional one-dimensional (1D) separation system when analyzing TCMs samples. Over the past decade, new techniques have been continuously developed to gain actionable insights from complex samples. This review presents the recent advancements in the application of multidimensional chromatography for the quality evaluation of TCMs, encompassing 2D-gas chromatography (GC), 2D-liquid chromatography (LC), as well as emerging three-dimensional (3D)-GC, 3D-LC, and their associated data-processing approaches. These studies highlight the promising potential of multidimensional chromatographic separation for future phytochemical analysis. Nevertheless, the increased separation capability has resulted in higher-order data sets and greater demands for data-processing tools. Considering that multidimensional chromatography is still a relatively nascent research field, further hardware enhancements and the implementation of chemometric methods are necessary to foster its robust development.

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In the present work vacuum (Vac) and multiple cumulative trapping (MCT) headspace solid phase microextraction (HS-SPME) were evaluated as alternative or combined techniques for the volatile profiling. A higher extraction performance for semi-volatiles was shown by all three techniques. Synergic combination of Vac and MCT showed up to 5-times extraction power for less volatile compounds. The hyphenation of said techniques with comprehensive two-dimensional gas chromatography (GC × GC) enabled a comprehensive analysis of the volatilome. Firstly, 18 targeted quality markers, previously defined by means of classical HS-SPME, were explored for their ability to classify commercial categories. The applicability of such markers proved to be limited with the alternative sampling techniques. An untargeted approach enables the selection of specific features for each technique showing a better classification capacity of the commercial categories. No misclassifications were observed, except for one extra virgin olive oil classified as virgin olive oil in 3 × 10 min Vac-MCT-HS-SPME.

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Lipids in human colostrum provide the majority of energy intake and essential fatty acids for developing infants. The fatty acid composition of human colostrum is highly variable and influenced by multiple factors. Human colostrum is a complex sample bringing challenges to fatty acid profiling. This work aimed to optimize the use of ionic liquid (IL) columns and flow-modulated comprehensive two-dimensional gas chromatography coupled to mass spectrometry (FM-GC×GC-MS) for fatty acid profiling in human colostrum. Derivatization strategies were optimized and the elution behavior of fatty acid methyl esters (FAME) on various 1D column phases (Solgel-WAX, SLB-IL60i, SLB-IL76i, and SLB-IL111i). Derivatization with sodium methoxide yielded a satisfactory recovery rate (90%) at milder conditions and reduced time. The use of IL60 as the 1D column provided superior separation, good peak shape, and better utilization of elution space. As a proof of concept, the developed method was applied to access the effects of the mode of neonatal delivery (vaginal vs. C-section) on the fatty acid profile of human colostrum samples. The integrated multidimensional gas chromatography strategy improved FAME detection and separation and can be a useful tool for accessing the effects of different factors on the fatty acid profiling of complex samples.

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