Comparative analysis of additive decomposition using one-dimensional and two-dimensional gas chromatography: Part II - Irgafos 168 and zinc stearate.

Plastic production has experienced a significant increase in the last sixty years due to its cost-efficiency and adaptable characteristics, leading to the extensive use of additives to improve its performance and longevity. Due to the high demand for plastic, plastic waste production has increased, contaminating the environment and living beings by leaching additives, among other substances. Pyrolysis stands out among recycling techniques because it can handle mixed polymer waste feedstock. However, understanding the pyrolyzates distribution of additives is fundamental to assessing pyrolysis process of plastic waste. This study investigated the pyrolysis product distributions of two commonly used antioxidants, namely, Irgafos 168 and zinc stearate (ZnSt), using one-dimensional gas chromatography equipped with a quadruple mass spectrometer (GC-MS) and two-dimensional gas chromatography coupled to flame ionization detector and time-of-flight mass spectrometer (GC×GC-FID/TOF-MS). While GC separation technique provided limited information on product distribution, GC×GC offered enhanced resolution and identification of the decomposition products. In the pyrolysis of Irgafos 168 at 550 °C, GC identified 18 products, while GC×GC identified 198 products, representing an increase of approximately 11-fold. Similarly, for ZnSt, GC identified 67 products, while GC×GC identified 434 products, representing a 6-fold increase. GC×GC identified decomposition products from 15 different chemical classes for Irgafos 168 and 16 chemical classes for ZnSt, compared to 4 and 11 chemical classes identified by GC, respectively. Phenols and their derivatives were the major chemical class in the decomposition products of Irgafos 168 with a yield of 9.51 wt.%. In contrast, olefinic products were the dominant ones for ZnSt, with a yield of 9.73 wt.%. The major decomposition product of Irgafos 168 and ZnSt was 2­tert­butyl­methylphenol (C11H16O) and C6 olefin (C6H12) with yields of 3.88 wt.%, and 1.13 wt.%, respectively. Utilizing the GC×GC separation method improved the ability to identify decomposition products, which can ultimately lead to a better understanding of antioxidant degradation that occurs during the pyrolysis process. GC×GC also provided thorough characterization of minor and co-eluted products along with major antioxidant degradation products. Additionally, the decomposition product distribution of Irgafos 168 and ZnSt was also compared with the primary antioxidants, Irganox 1010, Irganox 1076, and BHT, studied in part 1. The analysis indicated that the olefinic chemical class was the predominant one in Irganox 1010, Irganox 1076, and ZnSt, while ketones were the major chemical class in the decomposition of BHT and phenolics had the highest yield in Irgafos 168.

GC-NPD analysis of topiramate in capillary dried plasma: assessing chemical dependency pharmacotherapy.

Aim: This study aimed to develop and validate a GC-NPD method for quantifying topiramate (TPM) in capillary dried plasma spots (DPS).Materials & methods: Extraction involved three 6 mm DPS with albumin 0.1%, alkaline liquid extraction with tert-Butyl methyl ether and TMAH methylation. The method was validated and applied to 15 paired samples of capillary DPS and venous plasma from chemical dependency patients.Results: The method was linear from 1 to 50 µg/ml (r >0.99), precise (CV% 3.62-8.29%) accurate (98.1-107.7%). TPM stability was confirmed in DPS stored at 4, 23 and 45°C for 21 days. DPS TPM measurements were highly correlated plasma concentrations (rs = 0.96), representing on average 102% of the venous plasma measurements.Conclusion: The method was fully validated, demonstrating potential for clinical application.

[Box: see text].

Measuring Dissolved Methane in Aquatic Ecosystems Using An Optical Spectroscopy Gas Analyzer.

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.

Monitoring residual solvents in pharmaceutical products using a portable pre-concentration GC-PID.

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.

Comprehensive two-dimensional gas chromatography using a miniaturized multiloop splitter-based non-cryogenic artificial trapping (M-SNAT) modulation device for analysis of cannabis samples.

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.

Chromatography of Solanum habrochaites extracts with the first record of the docosanoate, hexadecanoate and octadecanoate ethyls in this plant and in Solanaceae.

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.

Gas Chromatography-Sensor System Aids Diagnosis of Inflammatory Bowel Disease, and Separates Crohn's from Ulcerative Colitis, in Children.

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.

Gas chromatographic techniques and spectroscopic approaches for a deep characterization of Piper gaudichaudianum Kunth essential oil from Brazil.

Piper gaudichaudianum Kunth essential oil (EO) is a natural source of bioactive components, having multiple therapeutic applications. Its chemical composition is highly variable, and strictly depends on abiotic factors, resulting in various biological activities. The present study details the utilization of multiple gas chromatographic techniques alongside nuclear magnetic resonance (NMR) spectroscopy to characterize the essential oil of Piper gaudichaudianum Kunth from Brazil. Seventy-six components were identified using GC-MS analysis, while enantio­selective multidimensional gas chromatography elucidated the enantiomeric distribution of eight chiral components, for the first time in the literature. Following GC-MS analysis, an unidentified component, constituting approximately 27 % of the total oil, prompted an isolation step through preparative gas chromatography. Through the combined use of nuclear magnetic resonance, GC-Fourier transform infrared spectroscopy (FTIR), and mass spectrometry (MS), the unknown molecule was structurally identified as 4-[(3E)­dec-3-en-1-yl]phenol. Remarkably, it was identified as a known molecule, gibbilimbol B, and not previously listed in any MS database. Subsequently, the spectrum was included in a commercial library, specifically the FFNSC 4.0 MS database, for the first time.

Fuel property modeling by high-speed gas chromatography coupled with partial least squares data analysis.

Partial least squares (PLS) regression is a valuable chemometric tool for property prediction when coupled with gas chromatography (GC). Since the separation run time and stationary phase selection are crucial for effective PLS modeling, we study these GC parameters on the prediction of viscosity, density and hydrogen content for 50 aerospace fuels. Due to the diversity of compounds in the fuels (primarily alkanes, cycloalkanes, and aromatics), we explore both polar and non-polar stationary phase columns. The robustness for the PLS models was evaluated by their normalized root mean square error of cross-validation (NRMSECV). PLS models built for viscosity across 1-min, 3-min, 7-min, and 10-min time window (TW) high-speed GC separations produced nearly the same NRMSECV with the polar column data with an average (standard deviation) of 4.41 % (0.34 %) versus the non-polar column data of 4.69 % (0.15 %). In contrast, while the NRMSECV of density modeling with the polar column data varied more than the viscosity models, averaging 7.54 % (0.67 %), the non-polar column data produced a significantly higher average NRMSECV of 10.06 % (0.35 %). Similarly, for hydrogen content, the NRMSECV with the polar column data averaged 9.50 % (0.87 %), which was significantly lower than the NRMSECV with the non-polar column data averaging 12.10 % (0.88 %). We also investigated the impact of smoothing the GC data on the corresponding PLS models. By applying varying degrees of smoothing, we can effectively obtain similar chromatographic peak patterns in a shorter TW. For example, a 10-min smoothed chromatogram appears like the 1-min separation with no smoothing but resulted in nearly the same NRMSECV. Overall, the fast separation with a 1-min TW produced robust PLS models for viscosity with either stationary phase column, whereas for density and hydrogen content the polar stationary phase column produced superior PLS models, thus with proper stationary phase selection, a fast separation run time could be readily applied with optimal PLS property modeling results.

Large-scale statistical study of the dependence of retention index on heating rate in temperature-programmed gas chromatography.

Retention indices are values that characterize the retention of a compound in gas chromatography. In practice, retention indices are often assumed to depend only on the structure of the molecule and the type of the stationary phase, but this approximation is incorrect. This study is devoted to studying the dependence of retention indices on the column heating rate in the linear temperature programming mode, using a large and diverse data set. In the NIST 20 database, most data records are recorded in this mode. For stationary phases based on poly(5%-diphenyl-95%-dimethyl)siloxane (5%-phenyl-PDMS), there is a high proportion of records with heating rates of 10-15 K/min. In practice, such a high heating rate is rarely used and the use of such data may cause errors. A search was made for groups of records that were taken from the same primary source, recorded for the same compound and the same stationary phase, but differing in a heating rate. For each of these groups, the value D, the angular coefficient (slope) of the dependence of the retention index on the heating rate, was calculated. This value can take both positive and negative values. The highest values and the greatest variation of D values are observed for polar stationary phases, but further consideration was performed for 5%-phenyl-PDMS due to its greater practical significance. For these stationary phases, the highest D values are observed for aromatic and polyaromatic molecules; oxygen-containing compounds, on the contrary, exhibit lower D values. Negative D values are observed for many trimethylsilyl derivatives. A data set of D values for 756 molecules was selected and published online. There is almost no correlation between D and the retention index, lipophilicity factor logP, and molecular weight. Significant correlations with the number of cycles, the number of rotatable bonds, and the number of aromatic atoms were observed. Linear equations quantitatively relating the molecular descriptors to the D value were constructed. A number of cycles and halogen atoms were shown to contribute positively to the D value, while a number of oxygen atoms and bonds subject to internal rotation contributed negatively. The strong influence of the values related to the conformational rigidity of molecules and the weak influence of polarity allow us to suppose that the entropic factor has a key influence on the D value. A simple empirical linear equation for estimating the value of D is derived and presented in this study. Several machine learning methods for predicting D are compared. The best results are shown by gradient boosting and a random forest. However, the random forest does not achieve high accuracy in predicting the retention indices themselves.

Comparative analysis of additive decomposition using one-dimensional and two-dimensional gas chromatography: Part I - Irganox 1010, Irganox 1076, and BHT.

Plastics incorporate diverse additives, including primary antioxidants with a typical amount between 0.05 to 3 wt.%, to enhance plastics functionality and durability, preventing their oxidation and maintaining their mechanical properties. While these antioxidants offer substantial benefits, their degradation can significantly impact plastic pyrolysis by changing the pyrolysis oil product distribution. Understanding the intricate distribution of decomposition products resulting from pyrolysis is essential yet often overlooked. This study delved into the analysis of the decomposition of common primary antioxidants, namely, Irganox 1010, Irganox 1076, and butylated hydroxytoluene (BHT), utilizing both one-dimensional gas chromatography coupled with a quadruple mass spectrometer (GC-MS) and two-dimensional gas chromatography equipped with flame ionization detector and time-of-flight mass spectrometer (GC×GC-FID/TOF-MS). This study showed that GC×GC-FID/TOF-MS provided a more detailed characterization of the pyrolysis product distribution of primary antioxidants used in plastics in comparison to GC-MS. For each of the antioxidants, using the GC×GC-FID/TOF-MS analytical approach enhanced the identification of degradation products at least fivefold. Furthermore, GC×GC-FID/TOF-MS identified products of more chemical classes than GC-MS. For instance, compounds from 14 chemical classes were identified from GC×GC-FID/TOF-MS in the pyrolysis of Irganox 1010, whereas only 9 chemical classes were identified in GC-MS. Olefins were the major chemical class for both Irganox 1010 and Irganox 1076 in the decomposition process, accounting for 23.25 wt.% and 20.76 wt.%, respectively. Ketones were the major chemical class in the case of BHT, having a 6.68 wt.% yield. This research enhanced the understanding of the decomposition of primary antioxidant and their product distribution during pyrolysis and shed light on the potential necessity for using two-dimensional gas chromatography.

Recent advances in the chromatographic analysis of endocannabinoids and phytocannabinoids in biological samples.

Endocannabinoid system, including endocannabinoid neurotransmitters (eCBs), has gained much attention over the last years due to its involvement with the pathophysiology of diseases and the potential use of Cannabis sativa (marijuana). The identification of eCBs and phytocannabinoids in biological samples for forensic, clinical, or therapeutic drug monitoring purposes constitutes a still significant challenge. In this scoping review, the recent advantages, and limitations of the eCBs and phytocannabinoids quantification in biological samples are described. Published studies from 2018-2023 were searched in 8 databases, and after screening and exclusions, the selected 38 articles had their data tabulated, summarized, and analyzed. The main characteristics of the eCBs and phytocannabinoids analyzed and the potential use of each biological sample were described, indicating gaps in the literature that still need to be explored. Well-established and innovative sample preparation protocols, and chromatographic separations, such as GC, HPLC, and UHPLC, are reviewed highlighting their respective advantages, drawbacks, and challenges. Lastly, future approaches, challenges, and tendencies in the quantification analysis of cannabinoids are discussed.

[Application of ion chromatographic fingerprint analysis for quality evaluation of tobacco flavors].

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.

Enantioseparation of pesticides by gas chromatography. Measurement of association constants enantiomer-chiral selector.

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.

Screening for compounds with bioaccumulation potential in breast milk using their retention behavior in two-dimensional gas chromatography.

Discovery of emerging pollutants in breast milk will be helpful for understanding the hazards to human health. However, it is difficult to identify key compounds among thousands present in complex samples. In this study, a method for screening compounds with bioaccumulation potential was developed. The method can decrease the number of compounds needing structural identification because the partitioning properties of bioaccumulative compounds can be mapped onto GC×GC chromatograms through their retention behaviors. Twenty pooled samples from seven provinces in China were analyzed. 1,286 compounds with bioaccumulation potential were selected from over 3,000 compounds. Sixty-two compounds, including aromatic compounds, phthalates, and phenolics etc., were identified with a high level of confidence and then quantified. Among them, twenty-seven compounds were found for the first time in breast milk. Three phthalate plasticizers and two phenolic antioxidants were found in significantly higher concentrations than other compounds. A toxicological priority index approach was applied to prioritize the compounds considering their concentrations, detection frequencies and eight toxic effects. The prioritization indicated that 13 compounds, including bis(2-ethylhexyl) phthalate, dibutyl phthalate, 1,3-di-tert-butylbenzene, phenanthrene, 2,6-di-tert-butyl-1,4-benzoquinone, 2,4-di-tert-butylphenol, and others, showed higher health risks. Meanwhile, some compounds with high risk for a particular toxic effect, such as benzothiazole and geranylacetone, were still noteworthy. This study is important for assessing the risks of human exposure to organic compounds.

Chiral Selectivities of Permethylated α-, ß-, and γ-Cyclodextrins Containing Gas Chromatographic Stationary Phases towards Ibuprofen and Its Derivatives.

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-, ß-, 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.

Evaluation of the Goss-modified solvation parameter model for the characterization of biphasic systems and descriptor assignments.

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.

Quantitative structure-retention relationships for pyridinium-based ionic liquids used as gas chromatographic stationary phases: convenient software and assessment of reliability of the results.

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.

Chemical composition, antioxidant and antimicrobial activities of essential oil from the aerial parts of Chuquiraga arcuataHarling grown in the highlands of Ecuador / Composición química, actividades antioxidantes y antimicrobianas del aceite esencial de las partes aéreas de Chuquiraga arcuataHarling cultivado en las tierras altas del Ecuador

Thechemical composition, antioxidant and antimicrobial activities of the essential oil from aerial parts (leaves and flowers) of Chuquiraga arcuataHarling grown in the Ecuadorian Andes were studied. One hundred and twenty-six compounds were identified in the essential oil. Monoterpene hydrocarbons (45.8%) and oxygenated monoterpenes (44.1%) had the major percentages. The most abundant compounds were camphor (21.6%), myrcene (19.5%), and 1,8-cineole (13.4%). Antioxidant activity was examined using DPPH, ABTS,and FRAP assays. The essential oil had a moderate scavenging effect and reduction of ferric ion capacity through FRAP assay. Antimicrobial activity of the essential oil was observed against four pathogenic bacteria and a fungus. The essential oil exhibited activity against all microorganism strains under test, particularly against Candida albicansand Staphylococcus aureuswith MICs of 2.43-12.10 µg/mL.

Se estudió la composición química, actividades antioxidantes y antimicrobianas del aceite esencial procedente de las partes aérea (hojas y flores) de Chuquiraga arcuataHarling cultivadas en los Andes ecuatorianos. Se identificaron 126 compuestos en el aceite esencial. Los hidrocarburos monoterpénicos (45,8%) y los monoterpenos oxigenados (44,1%) tuvieron el mayor porcentaje. Los compuestos más abundantes fueron alcanfor (21,6%), mirceno (19,5%) y 1,8-cineol (13,4%). La actividadantioxidante se examinó mediante ensayos DPPH, ABTS y FRAP. El aceite esencial tuvo un efecto eliminador moderado y una reducción de la capacidad de iones férricos mediante el ensayo FRAP. Se observó actividad antimicrobiana del aceite esencial contra cuatro bacterias y un hongo patógenos. El aceite esencial mostró actividad contra todas las cepas de microorganismos bajo prueba, particularmente contra Candida albicansy Staphylococcus aureuscon CMI de 2,43-12,10 µg/mL.

Validation of the identification reliability of known and assumed UDMH transformation products using gas chromatographic retention indices and machine learning.

Thirty two commercially available standards were used to determine chromatographic retention indices for three different stationary phases (non-polar, polar and mid-polar) commonly used in gas chromatography. The selected compounds were nitrogen-containing heterocycles and amides, which are referred to in the literature as unsymmetrical dimethylhydrazine (UDMH) transformation products or its assumed transformation products. UDMH is a highly toxic compound widely used in the space industry. It is a reactive substance that forms a large number of different compounds in the environment. Well-known transformation products may exceed UDMH itself in their toxicity, but most of the products are poorly investigated, while posing a huge environmental threat. Experimental retention indices for the three stationary phases, retention indices from the NIST database, and predicted retention indices are presented in this paper. It is shown that there are virtually no retention indices for UDMH transformation products in the NIST database. In addition, even among those compounds for which retention indices were known, inconsistencies were identified. Adding retention indices to the database and eliminating erroneous data would allow for more reliable identification when standards are not available. The discrepancies identified between experimental retention index values and predicted values will allow for adjustments to the machine learning models that are used for prediction. Previously proposed compounds as possible transformation products without the use of standards and NMR method were confirmed.