Search Results (70)

Background/objectives: Prostate cancer (PCa) is the most common cancer among males. Approximately 20–40% of patients with clinically localized PCa will present with a biochemical recurrence after a radical prostatectomy (RP), while some will present with recurrent metastasis. Monitoring the disease post-treatment is crucial for detecting a potential cancer recurrence early. Urinary volatile organic compounds (VOCs) have shown potential to detect PCa. However, their application in disease monitoring remains unexplored. Methods: A total of 165 urine samples were collected from male adults with biopsy-designated PCa-positive results before (n = 55) and after a RP (n = 55), and with biopsy-designated PCa-negative diagnosis (n = 55). The post-RP cohort was subdivided into three groups based on their health status after surgery as recovered healthy, biochemical recurrence, and recurrent metastasis. VOCs in the urine samples were extracted by stir bar sorptive extraction and analyzed using gas chromatography and mass spectrometry. We explored the use of metabolomics and a machine learning algorithm tool to investigate the potential of using VOCs for differentiating PCa diagnoses before and after the RP procedure with different outcomes. Results: Over 100 potential VOCs were identified to differentiate PCa patients before and after a RP, and those with biochemical recurrence and recurrent metastasis. Conclusions: Urinary VOCs are promising biomarkers that could be used to differentiate PCa patients pre- and post-RP. The findings from this research provide preliminary insights and could aid future investigations in developing tools for PCa patients after treatment. The absence of a validation cohort limits the reproducibility and translational impact of these findings; therefore, the results should be considered exploratory and require confirmation in larger, independent cohorts. Full article

This paper constitutes a preliminary study that evaluates the organic pollutants desorbed from “fresh” plastic litter, i.e., recently stranded items, on three beaches in Cadiz (SW Spain): Bajo de Guia, La Jara, and La Puntilla. Beach litter items were collected and classified in laboratory according to their composition and use. Leachates were obtained by stir bar sorptive extraction (SBSE) and analysed with gas chromatography–mass spectrometry (GC–MS). Fifty-five target organic compounds—including polycyclic aromatic hydrocarbons (PAHs), pesticides, fragrances, insect repellents, and UV filters—were quantified. Plastics accounted for the majority of litter by both number and weight. Cigarette butts and wipes were also prevalent and served as key sources of leachable PAHs. With respect to the main pollutants found in plastic films, hard plastics, and wipes, fragrances such as OTNE1 (1-Tetramethyl Acetyloctahydronaphthalene), OTNE2 (2-Tetramethyl Acetyloctahydronaphthalene), DEET (N, N-Diethyl-Meta-Toluamide), galaxolide, and tonalide were dominant, with concentrations exceeding 100 ng/g in some cases. DEET was the most common insect repellent detected. These findings underscore the role of beach litter, especially plastic waste, as a vector for persistent and emerging organic pollutants, highlighting the urgent need for improved waste management and monitoring practices to mitigate ecological risks associated with plastic pollution. Full article

Sparkling wine is a complex alcoholic beverage with high economic value, produced through a secondary fermentation of a still wine, followed by a prolonged aging period that may last from nine months to several years. With the growing global demand for high-quality sparkling wines, understanding the biochemical mechanisms related to aroma development has become increasingly relevant. This review provides a comprehensive overview of the secondary fermentation process, with particular emphasis on yeast selection, types of closure, and the impact of aging on the volatile composition. Special attention is also given to the analytical strategies employed for the identification and quantification of target compounds in sparkling wine matrices. Due to the presence of volatile compounds at trace levels, effective extraction and pre-concentration techniques are essential. Extraction methods such as solid-phase microextraction (SPME), stir-bar sorptive extraction (SBSE), and thin-film SPME (TF-SPME) are discussed, as well as chromatographic techniques, such as gas chromatography (GC) and liquid chromatography (LC). Full article

In this study, weekly grab samples extracted by solid-phase extraction (SPE) and stir bar sorptive extraction (SBSE) were compared for the analysis of 230 pesticides in surface waters. Samples were collected from three different locations around Melbourne, Australia. Analysis was performed using Gas Chromatography Quadrupole Time of Flight High Resolution Mass Spectrometry (GC-QToF-HRMS). The two extraction techniques were compared, among others, for their limits of detection, recovery, extraction, and quantification efficiency of pesticides, as well as spatial and temporal differences in detected compounds. The target compounds screened were pesticides belonging mainly to the categories of fungicides, insecticides, and herbicides. Although SBSE extracted more pesticides at two out of three sites, SPE extracted total concentrations up to four times higher than SBSE over all sampling sites. The log K_OW of detected pesticides only partially explained the differences in detection, with SBSE performing better in the absorption of hydrophobic compounds. In addition, matrix effects, in particular turbidity, appeared to hinder extraction of contaminants, especially for SBSE. Spatially, SBSE detected 10 pesticides more than SPE at two locations, while the opposite was true at the third location, where turbidity was higher. The types of pesticides detected varied slightly between techniques and locations. The study highlights the complementarity of SBSE and SPE for monitoring pesticides in natural environments. SBSE is an easy-to-use technique and allows for extraction of a higher number of pesticides at trace level, but it might not be the preferred option for highly turbid waters. SPE requires more tedious and complex sample processing but allows for a more accurate quantification of a broader range of pesticides. Full article

In this review, a 5-year overview on environmentally friendly approaches for the extraction of the most relevant organic pollutants in soil, sediment, particulate matter, and sewage sludge coupled with chromatographic analysis is reported. Organic contaminants encompass various compounds derived from personal care products, industrial chemicals, microplastics, organic matter combustion, agricultural practices, and plasticizer material. The principles of green analytical chemistry (GAC) and green sample preparation (GSP) serve as a guideline for the development of more environmentally sustainable analytical protocols. This study focuses attention on microwave-assisted extraction (MAE), ultrasound-assisted extraction (UAE), matrix solid-phase dispersion (MSPD), and microextraction techniques, such as solid-phase microextraction (SPME), stir bar sorptive extraction (SBSE), hollow-fiber liquid-phase microextraction (HF-LPME), spray-assisted droplet formation-based liquid-phase microextraction (SADF-LPME), and dispersive liquid–liquid extraction (DLLME). These approaches represent the most relevant eco-friendly sample preparation for the advanced extraction of target analytes from environmental solid samples. Full article

Background: There is a continuous demand to create new, superior sensory food experiences. In the food industry, yeast-derived flavor products (YPs) are often used as ingredients in foods to create new aromas and taste qualities that are appreciated by consumers. Methods: Chicken bouillon samples containing diverse YPs were chemically and sensorially characterized using statistical multivariate analyses. The sensory evaluation was performed using quantitative descriptive analysis (QDA) by trained panelists. Thirty-four sensory attributes were scored, including odor, flavor, mouthfeel, aftertaste and afterfeel. Untargeted metabolomic profiles were obtained using stir bar sorptive extraction (SBSE) coupled to GC-MS, RPLC-MS and targeted HILIC-MS. Results: In total, 261 volatiles were detected using GC-MS, from chemical groups of predominantly aldehydes, esters, pyrazines and ketones. Random Forest (RF) modeling revealed volatiles associated with roast odor (2-ethyl-5-methyl pyrazine, 2,3,5-trimethyl-6-isopentyl pyrazine) and chicken odor (2,4-nonadienal, 2,4-decadienal, 2-acetyl furan), which could be predicted by our combined model with R² > 0.5. In total, 2305 non-volatiles were detected for RPLC-MS and 34 for targeted HILIC-MS, where fructose-isoleucine and cyclo-leucine-proline were found to correlate with roast flavor and odor. Furthermore, a list of metabolites (glutamate, monophosphates, methionyl-leucine) was linked to umami-related flavor. This study describes a straightforward data-driven approach for studying foods with added YPs to identify flavor-impacting correlations between molecular composition and sensory perception. It also highlights limitations and preconditions for good prediction models. Overall, this study emphasizes a matrix-based approach for the prediction of food taste, which can be used to analyze foods for targeted flavor design or quality control. Full article

A Stir Bar Sorptive Extraction-Gas Chromatography-Mass Spectrometry (SBSE-GC-MS) method has been optimized and validated for the determination of eight volatile sulphur compounds in wine distillates: diethyl sulphide (DES), dimethyl disulphide (DMDS), diethyl disulphide (DEDS), 2-thiophenecarboxaldehyde (TC), dibutyl sulphide (DBS), dipropyl disulphide (DPDS), dipropyl sulphide (DPS), and dimethyl trisulphide (DMTS). After optimization by 2⁴ factorial design, the SBSE-GC-MS extraction conditions were as follows: a polydimethylsiloxane twister (10 mm × 0.5 mm), 35 °C as the extraction temperature, 10 mL as the sample volume, 7% (v/v) as the alcoholic grade, 47 min as the extraction time, 10% (w/v) of NaCl, and 1% (w/v) of EDTA (ethylenediaminetetraacetic acid). Under optimal conditions, adequate analytical figures of merit were obtained for eight of the ten compounds initially considered, with low quantification and detection limits and relative standard deviations for inter-twister and inter-day repeatability values ranging from 7.5 to 21.8% and from 7.2 to 27.5%, respectively. The methodology was applied to 34 wine distillates (continuous column distillation and distillation in pot still) elaborated for the production of Brandy de Jerez: 15 aged distillates aged for different periods of time in American oak wood and 19 non-aged distillates. The most significant volatile sulphur compounds were DBS, DMDS, and DPS. The Cluster Analysis (CA) on the volatile sulphur compounds grouped the samples according to the use of sulphur dioxide. In general, lower amounts of volatile sulphur compounds were found in the aged samples, although the high standard deviations obtained highlight that their contents depend on multiple factors related to the elaboration process. Full article

Rizhao green tea (RZT), a renowned green tea, is cultivated in China’s northernmost tea region. Its unique environment endows it with a strong chestnut- and seaweed-like aroma. This study sought to explore the volatile profiles of RZT and pinpoint its key odorants by employing stir bar sorptive extraction (SBSE) coupled with gas chromatography–mass spectrometry (GC-MS), determining the odor activity value (OAV), and performing gas chromatography–olfactometry (GC-O). A total of 112 volatiles were identified, and the major volatile compounds were esters (2035.25 μg/kg), alcohols (1799.02 μg/kg), alkanes (991.88 μg/kg), and ketones (691.96 μg/kg), comprising 74.91% of the total. A molecular aroma wheel was preliminarily established based on these key odorants. These insights might contribute to the scientific elucidation of the flavor chemical basis of RZT. Full article

A simple, fast, green, and sensitive method for determining Bisphenol A (BPA) levels in commercial milk was developed using a solventless sample preparation technique known as stir bar sorptive extraction, coupled with thermal desorption–gas chromatography/mass spectrometry. BPA was selected due to its ubiquitous presence in the environment and its classification as an endocrine-disrupting chemical of concern (i.e., its ability to mimic hormone functions). Studies have reported that BPA can leach into various food sources, including milk, a dietary staple for infants. It is critical to have an effective and efficient process for monitoring the presence of BPA in milk to protect children’s health. Current detection methods for BPA in milk are lengthy and tedious and tend to require the use of organic solvents for the extraction of BPA. This optimized “green” method provides an effective alternative for BPA detection in a challenging matrix, e.g., milk. Factors such as pH (1.5, 6, and 13), temperature (70–80 °C), and sonication (1 h, 2 h, and 3 h) were studied with a BPA-spiked whole milk sample (final concentration of 8 ppb) to optimize the extraction efficiency without the use of solvents. The developed methodology improves BPA recovery from whole milk by over 50%, with a detection limit in the parts per trillion range (45 ng/L). The sample preparation developed in this report rendered a more sensitive option for analyzing BPA in milk, with a limit of detection in the parts per trillion range (compared to low ppb) even though the recovery performance is not as good as in reported studies (54% vs. >85%); nonetheless, it provides a green alternative for future studies assessing BPA exposure through dairy products. Full article

Although vinegar is a product obtained by a well-known bioprocess from a technical point of view, the complex microbiota responsible for its production and their involvement in the organoleptic profiles are not clear yet. In this work, three acetification profiles in submerged culture using both synthetic and raw materials from Andalusia (Spain) were characterized by metagenomic (16S rRNA amplicon sequencing) and metabolomic tools (stir-bar sorptive extraction with thermo-desorption coupled to gas chromatography–mass spectrometry (SBSE-TD-GC−MS) and high-performance liquid chromatography (HPLC)). A total of 29 phyla, 208 families, and many more genera were identified, comprising bacteria and archaea as well as 75 metabolites, including minor volatile compounds, amino acids, biogenic amines, and other nitrogenous compounds. It can be concluded that Komagataeibacter and Acetobacter were not only the predominant genera but also the ones that most influenced vinegar metabolite profiles by using different metabolic strategies for mutual collaboration, and together with other microbial groups, some of them were previously practically unknown in vinegar. These results can be of interest not only to deepen the basic knowledge about vinegar but also to the vinegar industry by elucidating microbial succession and the key associated metabolites. Full article

A covalent organic framework (COF) based on imine was synthesized using 2,5-dihexoxyterephthalaldehyde (DHT) and 1,3,5-tris(4-aminophenyl) benzene (TAPB) as starting materials. The TAPB-DHT-COF exhibited satisfactory chemical stability, making it a promising adsorbing material for stir bar sorptive extraction (SBSE) of four estrogens, including estrone (E1), β-estradiol (E2), hexestrol (HES), and mestranol (MeEE2), in ambient water samples. The extracted analytes were subsequently analyzed using a high-performance liquid chromatography-diode array detector (HPLC-DAD). A series of parameters affecting the SBSE process, such as solution pH, ionic strength, extraction time, and desorption solvent, were investigated by the controlled variable method. Under optimal conditions, the limit of detection (LODs) for the four targeted estrogens ranged from 0.06 to 0.15 µg/L, with a linear range from 0.2 to 100 µg/L. The observed enrichment factor (EF) ranged from 39 to 49, while the theoretical EF was estimated to be 50-fold. This methodology can be applied to the identification of estrogens in three environmental water samples. Full article

The coupling of Solid-Phase Microextraction (SPME) technology with gas chromatography (GC) has a well-established and successful history. Traditionally, SPME fibers have been the most popular form thanks to their versatility and the ease with which they can be fully automated. However, alternative geometries for SPME have been developed over the years, beginning with Stir Bar Sorptive Extraction (SBSE) and later evolving into Thin-Film SPME (TF-SPME) devices. Each of these formats offers distinct advantages and disadvantages, which are explored in this study. The primary objective of this study was to comprehensively compare available forms of SPME devices, with a special focus on the advantages of TF-SPME, a novel microextraction method particularly suited for the analysis of odorants in food. The study involved analyzing a standard mixture of 11 key food odorants, representing a range of polarities, to evaluate the efficiency of TF-SPME devices in terms of the number of analytes extracted. Furthermore, four types of TF-SPME devices were compared against each other in both standard mixtures and actual food samples. The final stage of the study employed GCxGC-ToFMS analysis to showcase the potential of the most efficient HLB-TF-SPME device in the non-targeted analysis of complex samples, exemplified by unfiltered wheat beer. This analysis demonstrated the significant capability of HLB-TF-SPME in capturing and identifying a wide range of volatile compounds in complex matrices. Full article

Background: Clear cell renal cell carcinoma (ccRCC) comprises the majority, approximately 70–80%, of renal cancer cases and often remains asymptomatic until incidentally detected during unrelated abdominal imaging or at advanced stages. Currently, standardized screening tests for renal cancer are lacking, which presents challenges in disease management and improving patient outcomes. This study aimed to identify ccRCC-specific volatile organic compounds (VOCs) in the urine of ccRCC-positive patients and develop a urinary VOC-based diagnostic model. Methods: This study involved 233 pretreatment ccRCC patients and 43 healthy individuals. VOC analysis utilized stir-bar sorptive extraction coupled with thermal desorption gas chromatography/mass spectrometry (SBSE-TD-GC/MS). A ccRCC diagnostic model was established via logistic regression, trained on 163 ccRCC cases versus 31 controls, and validated with 70 ccRCC cases versus 12 controls, resulting in a ccRCC diagnostic model involving 24 VOC markers. Results: The findings demonstrated promising diagnostic efficacy, with an Area Under the Curve (AUC) of 0.94, 86% sensitivity, and 92% specificity. Conclusions: This study highlights the feasibility of using urine as a reliable biospecimen for identifying VOC biomarkers in ccRCC. While further validation in larger cohorts is necessary, this study’s capability to differentiate between ccRCC and control groups, despite sample size limitations, holds significant promise. Full article

The preparation of samples for instrumental analysis is the most essential and time-consuming stage of the entire analytical process; it also has the greatest impact on the analysis results. Concentrating the sample, changing its matrix, and removing interferents are often necessary. Techniques for preparing samples for analysis are constantly being developed and modified to meet new challenges, facilitate work, and enable the determination of analytes in the most comprehensive concentration range possible. This paper focuses on using metal-organic frameworks (MOFs) as sorbents in the most popular techniques for preparing liquid samples for analysis, based on liquid-solid extraction. An increase in interest in MOFs-type materials has been observed for about 20 years, mainly due to their sorption properties, resulting, among others, from the high specific surface area, tunable pore size, and the theoretically wide possibility of their modification. This paper presents certain advantages and disadvantages of the most popular sample preparation techniques based on liquid-solid extraction, the newest trends in the application of MOFs as sorbents in those techniques, and, most importantly, presents the reader with a summary, which a specific technique and MOF for the desired application. To make a tailor-made and well-informed choice as to the extraction technique. Full article

Despite advancements in the sensitivity and performance of analytical instruments, sample preparation remains a bottleneck in the analytical process. Currently, solid-phase extraction is more widely used than traditional organic solvent extraction due to its ease of use and lower solvent requirements. Moreover, various microextraction techniques such as micro solid-phase extraction, dispersive micro solid-phase extraction, solid-phase microextraction, stir bar sorptive extraction, liquid-phase microextraction, and magnetic bead extraction have been developed to minimize sample size, reduce solvent usage, and enable automation. Among these, in-tube solid-phase microextraction (IT-SPME) using capillaries as extraction devices has gained attention as an advanced “green extraction technique” that combines miniaturization, on-line automation, and reduced solvent consumption. Capillary tubes in IT-SPME are categorized into configurations: inner-wall-coated, particle-packed, fiber-packed, and rod monolith, operating either in a draw/eject system or a flow-through system. Additionally, the developments of novel adsorbents such as monoliths, ionic liquids, restricted-access materials, molecularly imprinted polymers (MIPs), graphene, carbon nanotubes, inorganic nanoparticles, and organometallic frameworks have improved extraction efficiency and selectivity. MIPs, in particular, are stable, custom-made polymers with molecular recognition capabilities formed during synthesis, making them exceptional “smart adsorbents” for selective sample preparation. The MIP fabrication process involves three main stages: pre-arrangement for recognition capability, polymerization, and template removal. After forming the template-monomer complex, polymerization creates a polymer network where the template molecules are anchored, and the final step involves removing the template to produce an MIP with cavities complementary to the template molecules. This review is the first paper to focus on advanced MIP-based IT-SPME, which integrates the selectivity of MIPs into efficient IT-SPME, and summarizes its recent developments and applications. Full article