Measuring greenhouse gas (GHG) fluxes and pools in ecosystems are becoming increasingly common in ecological studies due to their relevance to climate change. With it, the need for analytical platforms adaptable to measuring different pools and fluxes within research groups also grows. This study aims to develop a procedure to use portable optical spectroscopy-based gas analyzers, originally designed and marketed for gas flux measurements, to measure GHG concentrations in aqueous samples. The protocol involves the traditional headspace equilibration technique followed by the injection of a headspace gas subsample into a chamber connected through a closed loop to the inlet and outlet ports of the gas analyzer. The chamber is fabricated from a generic mason jar and simple laboratory supplies, and it is an ideal solution for samples that may require pre-injection dilution. Methane concentrations measured with the chamber are tightly correlated (r2 > 0.98) with concentrations determined separately through gas chromatography-flame ionization detection (GC-FID) on subsamples from the same vials. The procedure is particularly relevant for field studies in remote areas where chromatography equipment and supplies are not readily available, offering a practical, cheaper, and more efficient solution for measuring methane and other dissolved greenhouse gas concentrations in aquatic systems.

The diagnosis of inflammatory bowel disease (IBD) in children and the need to distinguish between subtypes (Crohn\'s disease (CD) and ulcerative colitis (UC)) requires lengthy investigative and invasive procedures. Non-invasive, rapid, and cost-effective tests to support these diagnoses are needed. Faecal volatile organic compounds (VOCs) are distinctive in IBD. VOC profiles can be rapidly determined using a gas chromatography-sensor device (OdoReader©). In an inception-cohort of children presenting with suspected IBD, we directly compared the diagnostic fidelity of faecal calprotectin (FCP, a non-specific protein marker of intestinal inflammation) with OdoReader© VOC profiles of children subsequently diagnosed with IBD with matched controls diagnosed with other gastrointestinal conditions. The OdoReader© was 82% (95% confidence interval 75-89%) sensitive and 71% (61-80%) specific but did not outperform FCP (sensitivity 93% (77-99%) and specificity 86% (67-96%); 250 µg/g FCP cut off) in the diagnosis of IBD from other gastrointestinal conditions when validated in a separate sample from the same cohort. However, unlike FCP and better than other similar technologies, the OdoReader© could distinguish paediatric CD from UC (up to 88% (82-93%) sensitivity and 80% (71-89%) specificity in the validation set) and justifies further validation in larger studies. A non-invasive test based on VOCs could help streamline and limit invasive investigations in children.

Multiloop splitter-based non-cryogenic artificial trapping (M-SNAT) modulation technique was developed, miniaturized and applied in comprehensive two-dimensional gas chromatography (GC×GC) for analysis of cannabis samples. The approach employed deactivated fuse silica (DFS) columns configured into multiple loop splitter system halving the perimeters of the progressively upstream loops. This splitter device was located between the first (1D) semi-nonpolar column outlet and a microfluidic Deans switch (DS). Each splitter loop splits a peak into two subpeaks having the same area with different void times. Three loops were then applied resulting in the number of the split subpeaks (nsplit) of 8 for each peak, and retention time differences between any two adjacent subpeaks (∆tR,split) were the same. By applying periodic heartcut event (H/C) within every artificial modulation period (PAM) of nsplit×∆tR,split, comprehensive split-and-trapped modulation profiles of analytes could be selectively transferred onto the second (2D) polar column (30 m) without cryogen consumption. This artificial modulation system was applied for analysis of cannabis samples with enhanced 2D peak capacity (2nc∼15). The established method was applied to analyse cannabis extracts using vegetable oils with or without frying process. This reveals 454 different peaks with 76, 92, 35 and 70 specific components specifically observed by using olive oil extraction (OE), fried OE, coconut oil extraction (CE) and fried CE, respectively.

The increasing need for sustainable alternatives to synthetic insecticides has driven the analysis of extracts from Solanum habrochaites, a wild tomato, through fractionated column chromatography. Potential bioactive compounds for pest management, a clean and promising biotechnological solution, have been reported from this plant. The objective is to provide detailed gas chromatography data, including peaks, structural formulas, and retention indices for the extracts of S. habrochaites aerial parts. Column chromatographic analysis was conducted with five fractions (F1, F2, F5, F3, and F4) of S. habrochaites extracts. Long-chain hydrocarbons such as hexadecanoic acid and docosano were identified in the F1 fraction; fatty acid esters, including hexadecanoate and octadecenoate ethyls in the F2 and methyl ketones, with tridecan-2-one as the major component in the F5, while no identifiable compounds were disclosed in the F3 and F4 fractions. The column chromatography provided valuable insights into compounds in the F1, F2, and F5 fractions of S. habrochaites extracts, highlighting fatty acid esters, long-chain hydrocarbons, and methyl ketones. The bioactive compounds, from extracts of this plant, including the first record of the docosanoate, hexadecanoate and octadecanoate ethyls in S. habrochaites and Solanaceae, reinforces their promising biological application in different areas of science.

Pharmaceutical manufacturing utilizes solvents at different stages of production. Some of the harmful solvent residuals may be retained in the final product; therefore, they need to be monitored for quality control and to meet the regulation requirement. Here, a novel method capable of rapidly analyzing residual solvents in pharmaceutical products was developed using a compact-portable gas chromatography with a photoionization detector (GC-PID). The method consists of modified Tedlar® bag sampling, online pre-concentration, separation of volatiles by miniaturized GC, and micro-PID detection. The method detection limits of selected residual solvents were in the range of 26.00 - 52.03 pg/mL which is much lower than the pharmaceutical compliance concentration limits. Limits of detection > 520 pg of analyte per grams of sample was also determined for the over-the-counter drugs. The method performance showed rapid speed (5 min), linear calibration (r2 < 0.99), and repeatable retention time (RSD < 0.4 %). Direct analysis of residual solvents in solid samples was conducted without the need for complex sample preparation. The method validation using over-the-counter pharmaceutical products yielded excellent accuracy (recovery > 91.2 %) and precision (RSD < 6.5 %) for the selected residual solvents, including 1,4-dioxane, benzene, chlorobenzene, cyclohexane, xylenes, and toluene. This portable and rapid method could be deployed during the pharmaceutical drug manufacturing processes for quality control.

Tobacco flavor, an important tobacco additive, is an essential raw material in cigarette production that can effectively improve the quality of tobacco products, add aroma and taste, and increase the suction flavor. The quality consistency of tobacco flavors affects the quality stability of branded cigarettes. Therefore, the quality control of tobacco flavors is a major concern for cigarette and flavor manufacturers. Physical and chemical indices, odor similarity, and sensory efficacy are employed to evaluate the quality of tobacco flavors, and the analysis of chemical components in tobacco flavors is usually conducted using gas chromatography (GC) and high performance liquid chromatography (HPLC). However, because the composition of tobacco flavors is complex, their quality cannot be fully reflected using a single component or combination of components. Therefore, establishing an objective analytical method for the quality control of tobacco flavors is of extreme importance. Chromatographic fingerprint analysis is routinely used for the discriminative analysis of tobacco flavors. Chromatographic fingerprints refer to the general characteristics of the concentration profiles of different chemical compounds. In the daily procurement process, fingerprints established by GC and HPLC are effective for the evaluation and identification of tobacco flavors. However, given continuous improvements in aroma-imitation technology, some flavors with high similarity cannot be directly distinguished using existing methods. In this study, a method for the determination of organic acids and inorganic anions in tobacco flavors based on ion chromatography (IC) was developed to ensure the quality consistency of tobacco flavors. A 1.0 g sample of tobacco flavors and 10 mL of deionized water were mixed and vibrated for 30 min. The aqueous sample solution was passed through a 0.45 μm membrane filter and RP pretreatment column in succession to eliminate interferences and then subjected to IC. Standard solutions containing nine organic acids and seven inorganic anions were used to identify the anions in the tobacco flavors, and satisfactory reproducibility was obtained. The relative standard deviations (RSDs) for retention times and peak areas were <0.71% and <6.02%, respectively. The chromatographic fingerprints of four types of tobacco flavors (samples A-D) from five different batches were obtained. Nine tobacco flavor samples from different manufacturers (samples AY1-AY3, BY1-BY2, CY1-CY2, DY1-DY2) were also analyzed to obtain their chromatographic fingerprints. Hierarchical cluster and similarity analyses were used to evaluate the quality of tobacco flavors from different manufacturers. Hierarchical clustering refers to the process of subdividing a group of samples into clusters that exhibit a high degree of intracluster similarity and intercluster dissimilarity. The dendrograms obtained using SPSS 12.0 indicated good quality consistency among the samples in different batches. Samples AY3, BY2, CY2, and DY1 clustered with the batches of standard tobacco flavors. Therefore, hierarchical cluster analysis can effectively distinguish the quality of products from different manufacturers. The Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine (version 2.0) was used to evaluate the similarity between the standard tobacco flavors and products from different manufacturers. Among the samples analyzed, samples AY3, BY2, CY2, and DY1 showed the highest similarity values (>97.7%), which was consistent with the results of the hierarchical cluster analysis. This finding indicates that IC combined with chromatographic fingerprint analysis could accurately determine the quality of tobacco flavors. GC combined with ultrasonic-assisted liquid-liquid extraction was also used to analyze the tobacco flavors and verify the accuracy of the proposed method. Compared with GC coupled with ultrasonic-assisted liquid-liquid extraction, IC demonstrated more significant quality differences among certain tobacco flavors.

Ibuprofen is a well-known and broadly used, nonsteroidal anti-inflammatory and painkiller medicine. Ibuprofen is a chiral compound, and its two isomers have different biological effects, therefore, their chiral separation is necessary. Ibuprofen and its derivatives were used as model compounds to establish transportable structure chiral selectivity relationships. Chiral selectors were permethylated α-, β-, and γ-cyclodextrins containing gas chromatographic stationary phases. The chiral selectivity of ibuprofen as a free acid and its various alkyl esters (methyl, ethyl, propyl, isopropyl, butyl, isobutyl, and isoamyl esters) derivatives were tested at different temperatures. Every tested stationary phase was capable of the chiral separations of ibuprofen in its free acid form. The less strong included S optical isomers eluted before R optical isomers in every separate case. The results offer to draw transportable guidelines for the chiral selectivity vs. analyte structures. It was recognized that the S isomers of free ibuprofen acid showed an overloading phenomenon, but the R isomer did not. The results were supported by molecular modeling studies.

In this study, the association constants of sixteen pesticides with the chiral selector octakis(6-O-tert-butyldimethylsilyl-2,3-di-O-acetyl)-γ-cyclodextrin were determined. The procedure only involved a few experimental measurements; namely, gas hold-up time and retention time of pesticides in capillary columns, as well as column phase ratio at each temperature condition. Fundamental equations of gas-liquid chromatography were used to estimate association constants. Two sets of columns containing different concentrations of the mentioned chiral selector dissolved in (14 %-cyanopropyl-phenyl)-86 %-methyl-polysiloxane were used. One set included capillary columns without any chemical treatment and the other group included columns that were crosslinked. The systematic comparison between both groups indicated a deleterious effect of the crosslinking on enantioselectivity. Our main objective is to promote the use of gas chromatography for the analysis of volatile and semi-volatile chiral pesticides. Thus, we proposed a simple methodology, based only on chromatographic measurements, to obtain information about the enantiorecognition ability of a particular chiral selector constituting the stationary phase and the influence of the selected polymer on the selectivity experimentally obtained.

Ionic liquids, i.e., organic salts with a low melting point, can be used as gas chromatographic liquid stationary phases. These stationary phases have some advantages such as peculiar selectivity, high polarity, and thermostability. Many previous works are devoted to such stationary phases. However, there are still no large enough retention data sets of structurally diverse compounds for them. Consequently, there are very few works devoted to quantitative structure-retention relationships (QSRR) for ionic liquid-based stationary phases. This work is aimed at closing this gap. Three ionic liquids with substituted pyridinium cations are considered. We provide large enough data sets (123-158 compounds) that can be used in further works devoted to QSRR and related methods. We provide a QSRR study using this data set and demonstrate the following. The retention index for a polyethylene glycol stationary phase (denoted as RI_PEG), predicted using another model, can be used as a molecular descriptor. This descriptor significantly improves the accuracy of the QSRR model. Both deep learning-based and linear models were considered for RI_PEG prediction. The ability to predict the retention indices for ionic liquid-based stationary phases with high accuracy is demonstrated. Particular attention is paid to the reproducibility and reliability of the QSRR study. It was demonstrated that adding/removing several compounds, small perturbations of the data set can considerably affect the results such as descriptor importance and model accuracy. These facts have to be considered in order to avoid misleading conclusions. For the QSRR research, we developed a software tool with a graphical user interface, which we called CHERESHNYA. It is intended to select molecular descriptors and construct linear equations connecting molecular descriptors with gas chromatographic retention indices for any stationary phase. The software allows the user to generate several hundred molecular descriptors (one-dimensional and two-dimensional). Among them, predicted retention indices for popular stationary phases such as polydimethylsiloxane and polyethylene glycol are used as molecular descriptors. Various methods for selecting (and assessing the importance of) molecular descriptors have been implemented, in particular the Boruta algorithm, partial least squares, genetic algorithms, L1-regularized regression (LASSO) and others. The software is free, open-source and available online: https://github.com/mtshn/chereshnya.

The solvation parameter model uses six descriptors identified as excess molar refraction, E, dipolarity/polarizability, S, overall hydrogen-bond acidity, A, overall hydrogen-bond basicity, B, McGowan\'s characteristic volume, V, and the gas-liquid partition constant on hexadecane at 25 °C, L to model the distribution of neutral compounds in biphasic systems. Abraham\'s version of this model uses all six descriptors with two separate linear free energy relationship models for the transfer of compounds from a gas phase to a condensed phase and between condensed phases. Goss proposed a modification to this model that uses a single calibration model regardless of the physical state for each phase and five of the descriptors employed in Abraham\'s model (E descriptor is eliminated). The capability of Abraham\'s model and the Goss-modified model to characterize the contribution of intermolecular interaction to retention for gas and reversed-phase liquid chromatographic systems and distribution in liquid-liquid partition systems is evaluated using the WSU compound descriptor database. These more accurate values for the Abraham descriptors have not been utilized previously for the evaluation of the Goss-modified model and should be more capable of discerning subtle differences in model performance. It is shown that model quality defined by statistical parameters favors Abraham\'s model over the Goss-modified model with differences in model quality greater for systems in which Abraham\'s model indicates a significant contribution from electron lone pair interactions and for systems in which one phase is a solvent containing perfluoroalkyl substituents. There is a small systematic difference for the terms describing the combined contributions of cavity formation and dispersion interactions and for interactions of a dipole-type. The contribution of hydrogen-bonding interactions is virtually identical for the two models. The model intercepts are generally different and potentially assigned to a larger contribution from lack-of-fit for the Goss-modified model. Although the Abraham model descriptors have been routinely employed for applications using the Goss-modified model the possibility that Goss-model specific descriptors should be employed was evaluated. Using the Solver method and Goss-model specific calibration models for chromatographic and liquid-liquid partition systems a new set of Goss-specific descriptors was calculated for 28 varied compounds. These descriptors show good statistical agreement with the Abraham descriptor values with an average deviation of 0.009, -0.003, -0.004, and -0.023, respectively, for the S, A, B, and L descriptors, corresponding to a relative absolute deviation in percent of 2.2 %, 3.9 %, 4.3 %, and 1.2 %, respectively.