The request for novel hyphenated instruments and techniques, capable of affording exhaustive information and results, is a focus continuously watched out. In this context, the present work aimed at the development of an integrated system combining gas chromatographic (GC) separation with mass spectrometry (MS) and (solid deposition) Fourier transform infrared spectroscopy (FTIR) detection. An external transfer line was designed in the lab for the parallel coupling of the two detectors, in such a way to obtain complementary analytical information consisting of an MS spectrum, an IR spectrum and linear retention indices (LRI), within a single analysis. The instrument performance was demonstrated for the analysis of a commercial mixture consisting of 139 hydrocarbons, comprising linear, branched, unsaturated and aromatic compounds. A 100-m poly(dimethylsiloxane) column was employed for the separation, and the outlet flow was split 95:5 between the IR and MS detectors using two uncoated capillaries. The IR spectra were acquired from solid deposits on a zinc selenide disc (-90 °C), over a spot (detector area) of about 0.1 mm2, in the range of 4000-700 cm-1 and at a resolution of 4 cm-1. Final identification of the separated compounds by a library search was achieved by excluding incorrect results, sequentially using a three-filter approach (85% similarity against reference MS and IR library spectra and ±10 LRI unit tolerance). Based on these preliminary results, the GC-MS/sd-FTIR system is a promising tool for the characterization of complex matrix constituents, for which identification is cumbersome, by using only one detection technique.

The study examined the effects of herb drying, salt concentration, pH, and sampling approach on essential oil yield and composition in Pimenta dioica (L.) Merr. Fresh samples yielded higher essential oil (EO) (1.25%) than shade-dried ones. Increasing NaCl concentration correlated with higher EO yields, while a basic pH favoured superior yields. Gas Chromatography identified Eugenol and β-myrcene as primary constituents. Eugenol content peaked at 10% NaCl (56.429%) and was lowest at pH 4 (42.850%). β-myrcene content was highest at pH 4 (31.476%). Hydro distillation with systematic sampling evaluated the effects of 14 fractions in different time frames. Phenylpropanoids (mainly eugenol) and acyclic monoterpene (mainly β-myrcene) dominated all fractions, with cyclic monoterpene (mainly limonene) enriched in the first four fractions. Fractions 10 to 14 showed significant increases in eugenol compared to the control. These findings provide insights for meeting market demands, enhancing the commercial potential of P. dioica EO.

The present study is based on the development of a straightforward method for the determination (semi-quantification) of 16 polycyclic aromatic hydrocarbons (PAHs) in extra virgin olive oil (EVOO) using \"cryogenic-zone-compression\" (CZC) gas chromatography-single quadrupole mass spectrometry (GC-QMS). The use of CZC (through a loop-type cryogenic modulator) to achieve enhanced signal-to-noise ratios (s/n), enabled a simplification of the sample preparation step. In fact, a single extraction process (using only 500 µL of acetonitrile) was performed prior to injection. The CZC GC-QMS method aligns with the principles of green analytical chemistry, and enabled an average s/n increase of 14-fold compared to conventional GC-QMS. The method limits of quantification were in the 0.07-8.33 µg kg-1 range. Accuracy (at the 2 μg kg-1 and 10 μg kg-1 concentration levels) was in the 82-103 % range. Intra-day and inter-day precision (at 2 μg kg-1 and 10 μg kg-1 concentration levels) were in the 1.9-14.7 % and 5.9-9.1 % ranges, respectively, while the recovery values (at 10 µg kg-1) ranged from 24 % to 99 %. For all the PAHs investigated, a positive matrix effect was observed. Two PAHs were detected (in the selected-ion-monitoring mode) in six EVOOs among the ten samples (not more than one PAH per sample).

The intestinal microbiota and its metabolites are essential for the health and growth development of animals. Current research indicates that sex has a certain impact on the structure and function of the intestinal microbiota, but there are few reports on sex differences in intestinal microbiota metabolites, including those of castrated male animals. This study aimed to explore the impact of sex on the intestinal microbial metabolites of Hainan special wild boars (10 entire male pigs, 10 female pigs, and 10 castrated male pigs, denoted EM, FE, and CM, respectively) by employing non-targeted metabolomics and gas chromatography. A total of 1086 metabolites were detected, with the greatest number of differential metabolites observed between EM and FE (54 differential metabolites, including 18 upregulated and 36 downregulated metabolites), the fewest between CM and FE (7 differential metabolites, including 1 upregulated and 6 downregulated metabolites), and an intermediate number between CM and EM (47 differential metabolites, including 35 upregulated and 12 downregulated metabolites). Differential metabolites were involved in more pathways between EM and FE and between CM and EM, including amino acid metabolism and digestive system pathways, whereas differential metabolites were involved in the fewest pathways between CM and FE. Correlation analysis showed Ruminococcaceae UCG-009, uncultured_bacterium_o_SAR324_cladeMarine_group_B, and Candidatus Saccharimonas contributed to the production of metabolites such as trehalose, docosatrienoic acid, D(-)-beta-hydroxy butyric acid, and acetyl-DL-leucine. The levels of acetic acid, propionic acid, butyric acid, isobutyric acid, valeric acid, and isovaleric acid were significantly higher in EM than in FE, with CM falling between the two. Streptococcus, Lachnospiraceae_NK4A136_group and Rikenellaceae_RC9_gut_group showed a significant positive correlation with the production of short-chain fatty acids (SCFAs), while [Eubacterium]_coprostanoligenes_group, uncultured_bacterium_f_p-251-o5 and Ruminococcaceae_UCG-005 showed a significant negative correlation with the generation of SCFAs. This study provides foundational data and significant insights into precision feeding strategies for Hainan special wild boars of different sexes, as well as the study of sex differences in intestinal microbial metabolites in animals.

Volatile halogenated hydrocarbons (VHHs) are annually produced and released into the environment, posing a threat to public health. In this study, a simple, rapid, sensitive and automated method based on headspace and gas chromatography (GC) with electron-capture detection was described for the determination of VHHs in different concentration levels in water samples. The proposed headspace GC method was initially optimized, and the optimum experimental conditions found were 10-mL water sample containing 20% w/v sodium chloride placed in a 20-mL vial and stirred at 60°C for 35 min, and then 14 VHHs were well separated on DB-35 MS capillary column with a split ratio of 12.5: 1. The limits of detection were in the low μg/L level, ranging between 0.01 and 0.6 μg/L. Finally optimized method was applied for determination 14 VHHs in drinking and environmental waters. The total mean concentrations of VHHs were 34.962, 26.183, 3.228 and 647.344 μg/L in tap water, purified water with 1-year-old filter element, seawater and effluents, respectively. However, no VHHs was detected in purified water with a new filter element. The main composition is different among different water matrix, which may be attributed to their different sources.

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.

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.

The plant cuticle acts as a vital shield, safeguarding against environmental and biological stresses. Tuberose flowers, specifically the \'Calcutta Single\' and \'Calcutta Double\' cultivars of Agave amica (syn. Polianthes tuberosa), are highly prized in India for their aromatic and aesthetic appeal. This research examines the tuberose floral cuticle using GC-MS to identify key chemical components and their characteristics. The analysis uncovered six major chemical classes viz. fatty acids, fatty alcohols, esters, alkanes, alkenes, and aldehydes as the primary constituents of the cuticular wax. Fatty acids and fatty alcohols are dominant in both cultivars, with \'Calcutta Single\' displaying a higher ester content than \'Calcutta Double\'. This study represents the inaugural in-depth exploration of cuticular wax in tuberose flowers, presenting a comparative investigation into these prominent cultivars.

The strawberry (genus Fragaria) is a plant from the rose family (Rosaceae). As the fruits are likely to be picked mechanically, they are grown close to consumption centers. The aim of this work was to develop a suitable method for detecting as many molecules as possible in order to be able to distinguish between different strawberry cultivars and geographical origins in the future. Whole strawberries of the \"Albion\" cultivar, grown in the Jagodica Purgerica region of Zagreb, were used. Gas chromatography-mass spectrometry (GC-MS) in SCAN mode was used to analyze the aroma profile and to determine the proportion of individual components. The samples were prepared and analyzed using the solid-phase microextraction method (SPME). The impact of SPME fiber selection and GC column type was investigated, as well as sample weight, ionic strength, agitation temperature, and sampling time. A higher ionic strength was achieved by adding a 20% NaCl solution to the sample. The aroma profile of the studied strawberry cultivar consisted of furanone, esters, aldehydes, and carboxylic acids. Optimal results were achieved by adjusting the ionic strength during 15 min of extraction and incubation. The individual compounds were identified using NIST, Wiley libraries, and the \"area normalization\" method.

In the past, polyacrylamide hydrogel was a popular choice for breast augmentation filler, and many women underwent mammoplasty with this gel. However, due to frequent complications, the use of polyacrylamide hydrogel in mammoplasty has been banned. Despite this ban, patients experiencing complications still seek medical treatment. The aim of this study was to investigate the fate of the polymer over a defined implantation period. Biopsies of breast implants were obtained from patients with 23 and 27 years of post-mammoplasty. These biopsies were meticulously purified from biological impurities and subjected to analysis using IR spectrometry, liquid chromatography-mass spectrometry, gas chromatography, and differential scanning calorimetry. The findings revealed the presence of polyacrylamide hydrogel residues, along with degradation products, within the infected material. Notably, the low-molecular-weight degradation products revealed via gas chromatography are aggressive and toxic substances capable of inducing chronic inflammation. This study sheds light on the long-term consequences of polyacrylamide hydrogel implantation, highlighting the persistence of harmful degradation products and their role in exacerbating patient complications.