Kaffir lime juice, often treated as production waste, can be a good source of terpenes. These compounds undergo various decomposition processes under the influence of external factors, especially during transportation and storage. In this paper, it was possible to monitor changes in the terpene profile of kaffir lime juice under different storage conditions, namely, 4 °C, 20 °C, and 35 °C. The identification of key decomposition products was achieved using gas chromatography-mass spectrometry (GC-MS) and a data mining protocol. It was followed by tracing those products in different storage conditions using a high-throughput proton transfer reaction mass spectrometry (PTR-MS) approach. Based on our findings, degradation pathways were presented, showing that the main products resulting from storage are p-cymene, p-cymenene, terpinene-4-ol, and α-terpineol. It was shown that conversion to p-cymenene occurs after 5 days of storage. Terpinene-4-ol and α-terpineol were found to be the final products of the conversion at all temperatures. Changes in the composition of terpenes are important from the point of view of their bioactive properties.

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.

Lipids are compounds involved in many biologic functions including cell structure, metabolism, energy storage and are involved in signaling. A prominent lipid in these functions is cholesterol. Cholesterol also plays a part in the signaling of melanocytes, which contain melanosomes. The maturation of these melanosomes happens during melanocyte growth. The deficit of melanogenesis or melanosome maturation is associated with ocular albinism in the eye. Aberrations of melanosome maturation are also associated with pigment dispersion syndrome. Albinism and pigment dispersion manifestations are systemic. Both melanogenesis and melanocyte maturation are affected by cholesterol metabolism. Cholesterol signaling is a part of many pathways in the body, and evaluating these signals can have implications in systemic disease processes of melanogenesis and melanosome maturation, like ocular albinism and pigment dispersion. Cholesterol is carried by lipoprotein particles. Low-density lipoprotein (LDL) is usually the transport vehicle for cholesterol to reach tissues and organelles. The LDL uptake on cells often sends out a cascade of internal signaling within the cells. We describe here LDL signaling related to lipase activity changes using enzymatic methods with a kit. We describe analyses of cholesterol esters and free cholesterol with liquid chromatography and gas chromatography with or in tandem with mass spectrometry (GC-MS and LC-MS/MS). These analyses will provide insight into melanosome maturation and melanogenesis. The methods described here are applicable to all melanocytes within the body of a model mammalian organism.

Increasing consumption of pharmaceuticals and the respective consequences for the aquatic environment have been the focus of many studies over the last thirty years. Various aspects in this field were investigated, considering diverse pharmaceutical groups and employing a wide range of research methodologies. Various questions from the perspectives of different research areas were devised and answered, resulting in a large mix of individual findings and conclusions. Collectively, the results of the studies offer a comprehensive overview. The large variety of methods and strategies, however, demands close attention when comparing and combining information from heterogeneous projects. This review critically examines the application of diverse sampling techniques as well as analytical methods in investigations concerning the behavior of pharmaceutically active compounds (PhACs) and contrast agents (CAs) in wastewater treatment plants (WWTPs). The combination of sampling and analysis is discussed with regard to its suitability for specific scientific problems. Different research focuses need different methods and answer different questions. An overview of studies dealing with the fate and degradation of PhACs and CAs in WWTPs is presented, discussing their strategic approaches and findings. This review includes surveys of anticancer drugs, antibiotics, analgesics and anti-inflammatory drugs, antidiabetics, beta blockers, hormonal contraceptives, lipid lowering agents, antidepressants as well as contrast agents for X-ray and magnetic resonance imaging.

OBJECTIVE: the creation of a dextran coating on cerium oxide crystals using different ratios of cerium and dextran to synthesize nanocomposites, and the selection of the best nanocomposite to develop a nanodrug that accelerates quality wound healing with a new type of antimicrobial effect.
METHODS: Nanocomposites were synthesized using cerium nitrate and dextran polysaccharide (6000 Da) at four different initial ratios of Ce(NO3)3x6H2O to dextran (by weight)-1:0.5 (Ce0.5D); 1:1 (Ce1D); 1:2 (Ce2D); and 1:3 (Ce3D). A series of physicochemical experiments were performed to characterize the created nanocomposites: UV-spectroscopy; X-ray phase analysis; transmission electron microscopy; dynamic light scattering and IR-spectroscopy. The biomedical effects of nanocomposites were studied on human fibroblast cell culture with an evaluation of their effect on the metabolic and proliferative activity of cells using an MTT test and direct cell counting. Antimicrobial activity was studied by mass spectrometry using gas chromatography-mass spectrometry against E. coli after 24 h and 48 h of co-incubation.
RESULTS: According to the physicochemical studies, nanocrystals less than 5 nm in size with diffraction peaks characteristic of cerium dioxide were identified in all synthesized nanocomposites. With increasing polysaccharide concentration, the particle size of cerium dioxide decreased, and the smallest nanoparticles (<2 nm) were in Ce2D and Ce3D composites. The results of cell experiments showed a high level of safety of dextran nanoceria, while the absence of cytotoxicity (100% cell survival rate) was established for Ce2D and C3D sols. At a nanoceria concentration of 10-2 M, the proliferative activity of fibroblasts was statistically significantly enhanced only when co-cultured with Ce2D, but decreased with Ce3D. The metabolic activity of fibroblasts after 72 h of co-cultivation with nano composites increased with increasing dextran concentration, and the highest level was registered in Ce3D; from the dextran group, differences were registered in Ce2D and Ce3D sols. As a result of the microbiological study, the best antimicrobial activity (bacteriostatic effect) was found for Ce0.5D and Ce2D, which significantly inhibited the multiplication of E. coli after 24 h by an average of 22-27%, and after 48 h, all nanocomposites suppressed the multiplication of E. coli by 58-77%, which was the most pronounced for Ce0.5D, Ce1D, and Ce2D.
CONCLUSIONS: The necessary physical characteristics of nanoceria-dextran nanocomposites that provide the best wound healing biological effects were determined. Ce2D at a concentration of 10-3 M, which stimulates cell proliferation and metabolism up to 2.5 times and allows a reduction in the rate of microorganism multiplication by three to four times, was selected for subsequent nanodrug creation.

The monitoring of contaminants in fish species is pivotal for fishes\' health and reproduction, as well as for human health. In the specific work, three major categories of contaminants, pesticides, pharmaceuticals, and macro and trace elements, were investigated in two major fish species, Dicentrarchus labrax and Solea solea, collected from Thermaikos Gulf, in Greece. To achieve this goal, three analytical methods using LC-MS/MS, GC-MS/MS, and ICP-MS were developed, validated, and applied to the collected fish samples. The results indicated a very low prevalence of caffeine and acetaminophen, both not exceeding 3.8 μg/kg fish. Similarly, thiabendazole, cypermethrin, and tricyclazole (pesticides) were found in a concentration range of 0.9 to 13.7 μg/kg fish, while in one D. labrax sample, traces of the metabolite of organochlorine pesticide DDT, o,p\'-DDE were detected. Al, Mn, Fe, Zn, and Sr were the predominant trace elements in a concentration range of 500-20,000 μg/kg fish. Macro elements levels varied from 280 to 5405 mg/kg fish. Health risk assessment did not unveil an unacceptable risk for the human health of adults, apart from one sample presenting Hg above the regulatory levels. On the contrary, for children, the calculated hazard quotient values for Hg in all cases and for two As detections were higher than the threshold value of 1, indicating a potential risk.

Chemometric decomposition methods like multivariate curve resolution-alternating least squares (MCR-ALS) are often employed in gas chromatography-mass spectrometry (GC-MS) to improve analyte identification and quantitation. However, these methods can perform poorly for analytes with a low chromatographic resolution (Rs) and a high degree of spectral contamination from noise and background interferences. Thus, we propose a novel computational algorithm, termed mzCompare, to improve analyte identification and quantitation when coupled to MCR-ALS. The mzCompare method utilizes an underlying requirement that the retention time and peak shape between mass channels (m/z) of the same analyte should be similar. By discovering the selective m/z for a given analyte in a chromatogram, a pure elution profile can be generated and used as an equality constraint in MCR-ALS. The performance of the mzCompare methodology is demonstrated with both experimental and simulated chromatograms. Experimentally, unresolved analytes with a Rs as low as 0.05 could be confidently identified with mzCompare assisted MCR-ALS. Furthermore, application of the mzCompare algorithm to a complex aerospace fuel resulted in the discovery of 335 analytes, a 44 % increase compared to conventional peak detection methods. GC-MS simulations of target-interferent analyte pairs demonstrated that the performance of MCR-ALS deteriorated below a Rs of ∼0.25. However, mzCompare assisted MCR-ALS showed excellent identification and acceptable quantitative accuracy at a Rs of ∼0.02. These results show that the mzCompare algorithm can help analysts overcome modeling ambiguities resulting from the chemometric multiplex disadvantage.

The study examines the unique production process of Aceto Balsamico Tradizionale di Modena PDO (ABTM), emphasizing its complex phases and the impact of raw materials and artisanal skill on its flavor characteristics. Analytical tests focused on the volatile composition of vinegars from different wood barrels at different aging stages, using solid-phase micro-extraction (SPME) coupled with gas chromatography, either with mass spectrometry (GC/MS) or flame ionization detector (FID). Multivariate analysis, including principal component analysis (PCA), was employed to investigate the presence of peculiarities among the volatile profiles of samples of different barrel origin. The research focuses on characterizing the volatile composition of vinegars sourced from individual wood barrels, such as Cherry, Chestnut, Mulberry, Juniper, and Oak. Although it was not possible to identify molecules directly connected to the woody essence, some similarities emerged between vinegar samples from mulberry and cherry barrels and between those of juniper and oak. The former group is characterized by analytes with high molecular weights, such as furfural and esters, while the latter group shows more intense peaks for ethyl benzoate. Moreover, ethyl benzoate appears to predominantly influence samples from chestnut barrels. Due to the highly complex production process of ABTM, where each battery is influenced by several factors, this study\'s findings are specific to the current experimental conditions.

The thermally stable zirconium-based MOF, UiO-66, was employed for the preparation of bonded porous-layer open-tubular (PLOT) GC columns. The synthesis included the in situ growth of the UiO-66 film on the inner wall of the capillary through a one-step solvothermal procedure. SEM-EDX analysis revealed the formation of a thin, continuous, uniform, and compact layer of UiO-66 polycrystals on the functionalized inner wall of the column. The average polarity (ΔIav = 700) and the McReynolds constants reflected the polar nature of the UiO-66 stationary phase. Several mixtures of small organic compounds and real samples were used to evaluate the separation performance of the fabricated columns. Linear alkanes from n-pentane to n-decane were baseline separated within 1.35 min. Also, a series of six n-alkylbenzenes (C3-C8) were separated within 3 min with a minimum resolution of 3.09, whereas monohalobenzene mixtures were separated at 220 °C within 14s. UiO-66 PLOT columns are ideally suited for the isothermal separation of chlorobenzene structural isomers at 210 °C within 45 s with Rs ≥ 1.37. The prepared column featured outstanding thermal stability (up to 450 °C) without any observed bleeding or significant impact on its performance. This feature enabled the analysis of various petroleum-based samples.

Polycyclic aromatic hydrocarbons are considered to be potentially genotoxic and carcinogenic to humans. For non-smoking populations, food is the main source of polycyclic aromatic hydrocarbons exposure. Due to their lipophilic nature, oils and fats rank among the food items with the highest polycyclic aromatic hydrocarbon content. Consequently, the detection of polycyclic aromatic hydrocarbons in edible oils is critical for the promotion of human health. This paper reviews sample pretreatment methods, such as liquid-phase-based extraction methods, adsorbent-based extraction methods, and the QuEChERS (quick, easy, cheap, effective, rugged, and safe) method, combined with detection techniques like mass spectrometry and chromatography-based techniques for accurate quantification of polycyclic aromatic hydrocarbons in edible oils since 2010. An overview on the advances of the methods discussed herein, along with a commentary addition of current challenges and prospects, will guide researchers to focus on developing more effective detection methods and control measures to reduce the potential risks and hazards posed by polycyclic aromatic hydrocarbons.