What is the role of current mass spectrometry in pharmaceutical analysis?

The role of mass spectrometry (MS) has become more important in most application domains in recent years. Pharmaceutical analysis is specific due to its stringent regulation procedures, the need for good laboratory/manufacturing practices, and a large number of routine quality control analyses to be carried out. The role of MS is, therefore, very different throughout the whole drug development cycle. While it dominates within the drug discovery and development phase, in routine quality control, the role of MS is minor and indispensable only for selected applications. Moreover, its role is very different in the case of analysis of small molecule pharmaceuticals and biopharmaceuticals. Our review explains the role of current MS in the analysis of both small-molecule chemical drugs and biopharmaceuticals. Important features of MS-based technologies being implemented, method requirements, and related challenges are discussed. The differences in analytical procedures for small molecule pharmaceuticals and biopharmaceuticals are pointed out. While a single method or a small set of methods is usually sufficient for quality control in the case of small molecule pharmaceuticals and MS is often not indispensable, a large panel of methods including extensive use of MS must be used for quality control of biopharmaceuticals. Finally, expected development and future trends are outlined.

Exhaled Volatile Organic Compounds for Asthma Control Classification in Children with Moderate to Severe Asthma: Results from the SysPharmPediA Study.

RATIONALE: Early identification of children with poorly controlled asthma is imperative for optimizing treatment strategies. The analysis of exhaled volatile organic compounds (VOCs) is an emerging approach to identify prognostic and diagnostic biomarkers in pediatric asthma. OBJECTIVES: To assess the accuracy of gas chromatography-mass spectrometry based exhaled metabolite analysis to differentiate between controlled and uncontrolled pediatric asthma. METHODS: This study encompassed a discovery (SysPharmPediA) and validation phase (U-BIOPRED, PANDA). Firstly, exhaled VOCs that discriminated asthma control levels were identified. Subsequently, outcomes were validated in two independent cohorts. Patients were classified as controlled or uncontrolled, based on asthma control test scores and number of severe attacks in the past year. Additionally, potential of VOCs in predicting two or more future severe asthma attacks in SysPharmPediA was evaluated. MEASUREMENTS AND MAIN RESULTS: Complete data were available for 196 children (SysPharmPediA=100, U-BIOPRED=49, PANDA=47). In SysPharmPediA, after randomly splitting the population into training (n=51) and test sets (n=49), three compounds (acetophenone, ethylbenzene, and styrene) distinguished between uncontrolled and controlled asthmatics. The area under the receiver operating characteristic curve (AUROCC) for training and test sets were respectively: 0.83 (95% CI: 0.65-1.00) and 0.77 (95% CI: 0.58-0.96). Combinations of these VOCs resulted in AUROCCs of 0.74 ±0.06 (UBIOPRED) and 0.68 ±0.05 (PANDA). Attacks prediction tests, resulted in AUROCCs of 0.71 (95% CI 0.51-0.91) and 0.71 (95% CI 0.52-0.90) for training and test sets. CONCLUSIONS: Exhaled metabolites analysis might enable asthma control classification in children. This should stimulate further development of exhaled metabolites-based point-of-care tests in asthma.

Chemical Profiles Differ between Communal Breeding Groups in a Highly Social Bird.

AbstractGregarious species must distinguish group members from nongroup members. Olfaction is important for group recognition in social insects and mammals but rarely studied in birds, despite birds using olfaction in social contexts from species discrimination to kin recognition. Olfactory group recognition requires that groups have a signature odor, so we tested for preen oil and feather chemical similarity in group-living smooth-billed anis (Crotophaga ani). Physiology affects body chemistry, so we also tested for an effect of egg-laying competition, as a proxy for reproductive status, on female chemical similarity. Finally, the fermentation hypothesis for chemical recognition posits that host-associated microbes affect host odor, so we tested for covariation between chemicals and microbiota. Group members were more chemically similar across both body regions. We found no chemical differences between sexes, but females in groups with less egg-laying competition had more similar preen oil, suggesting that preen oil contains information about reproductive status. There was no overall covariation between chemicals and microbes; instead, subsets of microbes could mediate olfactory cues in birds. Preen oil and feather chemicals showed little overlap and may contain different information. This is the first demonstration of group chemical signatures in birds, a finding of particular interest given that smooth-billed anis live in nonkin breeding groups. Behavioral experiments are needed to test whether anis can distinguish group members from nongroup members using odor cues.

Unravelling the metabolomic diversity of pigmented and non-pigmented traditional rice from Tamil Nadu, India.

Rice metabolomics is widely used for biomarker research in the fields of pharmacology. As a consequence, characterization of the variations of the pigmented and non-pigmented traditional rice varieties of Tamil Nadu is crucial. These varieties possess fatty acids, sugars, terpenoids, plant sterols, phenols, carotenoids and other compounds that plays a major role in achieving sustainable development goal 2 (SDG 2). Gas-chromatography coupled with mass spectrometry was used to profile complete untargeted metabolomics of Kullkar (red colour) and Milagu Samba (white colour) for the first time and a total of 168 metabolites were identified. The metabolite profiles were subjected to data mining processes, including principal component analysis (PCA), Orthogonal Partial Least Square Discrimination Analysis (OPLS-DA) and Heat map analysis. OPLS-DA identified 144 differential metabolites between the 2 rice groups, variable importance in projection (VIP) ≥ 1 and fold change (FC) ≥ 2 or FC ≤ 0.5. Volcano plot (64 down regulated, 80 up regulated) was used to illustrate the differential metabolites. OPLS-DA predictive model showed good fit (R2X = 0.687) and predictability (Q2 = 0.977). The pathway enrichment analysis revealed the presence of three distinct pathways that were enriched. These findings serve as a foundation for further investigation into the function and nutritional significance of both pigmented and non-pigmented rice grains thereby can achieve the SDG 2.

Effect of Secondary Heat Treatment after a Washing on the Electrochemical Performance of Co-Free LiNi0.975 Al0.025 O2 Cathodes for Li-Ion Batteries.

The steadily growing electric vehicle market is a driving force in low-cost, high-energy-density lithium-ion battery development. To meet this demand, LiNi0.975 Al0.025 O2 (LNA), a high-energy-density and cobalt-free cathode material, has been developed using a low-cost and efficient co-precipitation and lithiation process. This article explores how further processing (i.e., washing residual lithium from the secondary particle surface and applying a secondary heat treatment at 650 °C) changes the chemical environment of the surface and the electrochemical performance of the LNA cathode material. After washing, a nonconductive nickel oxide (NiO) phase is formed on the surface, decreasing the initial capacity in electrochemical tests, and suppressing high-voltage (H2) to (H3) phase transition results in enhanced cycle properties. Furthermore, the secondary heat treatment re-lithiates surface NiO back to LNAand increases the initial capacity with enhanced cycle properties. Electrochemical tests are performed with the cells without tap charge to suppress the H2 to H3 phase transition. Results reveal that avoiding charging cells at a high voltage for a long time dramatically improves LNA's cycle life. In addition, the gas analysis tests performed during charge and discharge to reveal how the amount of residual lithium compounds on the surface affects gas formation are studied.

A closer look at high-energy X-ray-induced bubble formation during soft tissue imaging.

Improving the scalability of tissue imaging throughput with bright, coherent X-rays requires identifying and mitigating artifacts resulting from the interactions between X-rays and matter. At synchrotron sources, long-term imaging of soft tissues in solution can result in gas bubble formation or cavitation, which dramatically compromises image quality and integrity of the samples. By combining in-line phase-contrast imaging with gas chromatography in real time, we were able to track the onset and evolution of high-energy X-ray-induced gas bubbles in ethanol-embedded soft tissue samples for tens of minutes (two to three times the typical scan times). We demonstrate quantitatively that vacuum degassing of the sample during preparation can significantly delay bubble formation, offering up to a twofold improvement in dose tolerance, depending on the tissue type. However, once nucleated, bubble growth is faster in degassed than undegassed samples, indicating their distinct metastable states at bubble onset. Gas chromatography analysis shows increased solvent vaporization concurrent with bubble formation, yet the quantities of dissolved gasses remain unchanged. By coupling features extracted from the radiographs with computational analysis of bubble characteristics, we uncover dose-controlled kinetics and nucleation site-specific growth. These hallmark signatures provide quantitative constraints on the driving mechanisms of bubble formation and growth. Overall, the observations highlight bubble formation as a critical yet often overlooked hurdle in upscaling X-ray imaging for biological tissues and soft materials and we offer an empirical foundation for their understanding and imaging protocol optimization. More importantly, our approaches establish a top-down scheme to decipher the complex, multiscale radiation-matter interactions in these applications.

Recent advances in mass spectrometry for the detection of doping.

INTRODUCTION: The analysis of doping control samples is preferably performed by mass spectrometry, because obtained results meet the highest analytical standards and ensure an impressive degree of reliability. The advancement in mass spectrometry and all its associated technologies thus allow for continuous improvements in doping control analysis. AREAS COVERED: Modern mass spectrometric systems have reached a status of increased sensitivity, robustness, and specificity within the last decade. The improved sensitivity in particular has, on the other hand, also led to the detection of drug residues that were attributable to scenarios where the prohibited substances were not administered consciously but rather by the unconscious ingestion of or exposure to contaminated products. These scenarios and their doubtless clarification represent a great challenge. Here, too, modern MS systems and their applications can provide good insights in the interpretation of dose-related metabolism of prohibited substances. In addition to the development of new instruments itself, software-assisted analysis of the sometimes highly complex data is playing an increasingly important role and facilitating the work of doping control laboratories. EXPERT OPINION: The sensitive analysis and evaluation of a higher number of samples in a shorter time is made possible by the ongoing developments in mass spectrometry.

Constraining activity and growth substrate of fungal decomposers via assimilation patterns of inorganic carbon and water into lipid biomarkers.

Fungi are among the few organisms on the planet that can metabolize recalcitrant carbon (C) but are also known to access recently produced plant photosynthate. Therefore, improved quantification of growth and substrate utilization by different fungal ecotypes will help to define the rates and controls of fungal production, the cycling of soil organic matter, and thus the C storage and CO2 buffering capacity in soil ecosystems. This pure-culture study of fungal isolates combined a dual stable isotope probing (SIP) approach, together with rapid analysis by tandem pyrolysis-gas chromatography-isotope ratio mass spectrometry to determine the patterns of water-derived hydrogen (H) and inorganic C assimilated into lipid biomarkers of heterotrophic fungi as a function of C substrate. The water H assimilation factor (αW) and the inorganic C assimilation into C18:2 fatty acid isolated from five fungal species growing on glucose was lower (0.62% ± 0.01% and 4.7% ± 1.6%, respectively) than for species grown on glutamic acid (0.90% ± 0.02% and 7.4% ± 3.7%, respectively). Furthermore, the assimilation ratio (RIC/αW) for growth on glucose and glutamic acid can distinguish between these two metabolic modes. This dual-SIP assay thus delivers estimates of fungal activity and may help to delineate the predominant substrates that are respired among a matrix of compounds found in natural environments.IMPORTANCEFungal decomposers play important roles in food webs and nutrient cycling because they can feed on both labile and more recalcitrant forms of carbon. This study developed and applied a dual stable isotope assay (13C-dissolved inorganic carbon/2H) to improve the investigation of fungal activity in the environment. By determining the incorporation patterns of hydrogen and carbon into fungal lipids, this assay delivers estimates of fungal activity and the different metabolic pathways that they employ in ecological and environmental systems.

Analysis of surfactants by mass spectrometry: Coming to grips with their diversity.

Surfactants are surface-active agents widely used in numerous applications in our daily lives as personal care products, domestic, and industrial detergents. To determine complex mixtures of surfactants and their degradation products, unselective and rather insensitive methods, based on colorimetric and complexometric analyses are no longer employable. Analytical methodologies able to determine low concentration levels of surfactants and closely related compounds in complex matrices are required. The recent introduction of robust, sensitive, and selective mass spectrometry (MS) techniques has led to the rapid expansion of the surfactant research field including complex mixtures of isomers, oligomers, and homologues of surfactants as well as their chemically and biodegradation products at trace levels. In this review, emphasis is given to the state-of-the-art MS-based analysis of surfactants and their degradation products with an overview of the current research landscape from traditional methods involving hyphenate techniques (gas chromatography-MS and liquid chromatography-MS) to the most innovative approaches, based on high-resolution MS. Finally, we outline a detailed explanation on the utilization of MS for mechanistic purposes, such as the study of micelle formation in different solvents.

Development of metabolome extraction strategy for metabolite profiling of skin tissue.

INTRODUCTION: Changes in skin phenotypic characteristics are based on skin tissue. The study of the metabolic changes in skin tissue can help understand the causes of skin diseases and identify effective therapeutic interventions. OBJECTIVES: We aimed to establish and optimize a non-targeted skin metabolome extraction system for skin tissue metabolomics with high metabolite coverage, recovery, and reproducibility using gas chromatography/mass spectrometry. METHODS: The metabolites in skin tissues were extracted using eleven different extraction systems, which were designed using reagents with different polarities based on sequential solid-liquid extraction employing a two-step strategy and analyzed using gas chromatograph/mass spectrometry. The extraction efficiency of diverse solvents was evaluated by coefficient of variation (CV), multivariate analysis, metabolites coverage, and relative peak area analysis. RESULTS: We identified 119 metabolites and the metabolite profiles differed significantly between the eleven extraction systems. Metabolites with high abundances in the organic extraction systems, followed by aqueous extraction, were involved in the biosynthesis of unsaturated fatty acids, while metabolites with high abundances in the aqueous extraction systems, followed by organic extraction, were involved in amino sugar and nucleotide sugar metabolism, and glycerolipid metabolism. MeOH/chloroform-H2O and MeOH/H2O-chloroform were the extraction systems that yielded the highest number of metabolites, while MeOH/acetonitrile (ACN)-H2O and ACN/H2O-IPA exhibited superior metabolite recoveries. CONCLUSION: Our results demonstrated that our research facilitates the selection of an appropriate metabolite extraction approach based on the experimental purpose for the metabolomics study of skin tissue.

Evaluation of normalization strategies for GC-based metabolomics.

INTRODUCTION: For many samples studied by GC-based metabolomics applications, extensive sample preparation involving extraction followed by a two-step derivatization procedure of methoximation and trimethylsilylation (TMS) is typically required to expand the metabolome coverage. Performing normalization is critical to correct for variations present in samples and any biases added during the sample preparation steps and analytical runs. Addressing the totality of variations with an adequate normalization method increases the reliability of the downstream data analysis and interpretation of the results. OBJECTIVES: Normalizing to sample mass is one of the most commonly employed strategies, while the total peak area (TPA) as a normalization factor is also frequently used as a post-acquisition technique. Here, we present a new normalization approach, total derivatized peak area (TDPA), where data are normalized to the intensity of all derivatized compounds. TDPA relies on the benefits of silylation as a universal derivatization method for GC-based metabolomics studies. METHODS: Two sample classes consisting of systematically incremented sample mass were simulated, with the only difference between the groups being the added amino acid concentrations. The samples were TMS derivatized and analyzed using comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (GC × GC-TOFMS). The performance of five normalization strategies (no normalization, normalized to sample mass, TPA, total useful peak area (TUPA), and TDPA) were evaluated on the acquired data. RESULTS: Of the five normalization techniques compared, TUPA and TDPA were the most effective. On PCA score space, they offered a clear separation between the two classes. CONCLUSION: TUPA and TDPA carry different strengths: TUPA requires peak alignment across all samples, which depends upon the completion of the study, while TDPA is free from the requirement of alignment. The findings of the study would enhance the convenient and effective use of data normalization strategies and contribute to overcoming the data normalization challenges that currently exist in the metabolomics community.

Lipidomic and Fatty Acid Biomarkers in Whole Blood Can Predict the Dietary Intake of Eicosapentaenoic and Docosahexaenoic Acids in a Danish Population.

BACKGROUND: The intake of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) have been associated with health benefits. Blood levels of these fatty acids, measured by gas chromatography (GC), are associated with their dietary intake, but the relationships with lipidomic measurements are not well defined. OBJECTIVES: This study aimed to determine the lipidomic biomarkers in whole blood that predict intakes of EPA + DHA and examine the relationship between lipidomic and GC-based n-3 polyunsaturated fatty acid (n-3 PUFA) biomarkers. METHODS: Lipidomic and fatty acid analyses were completed on 120 whole blood samples collected from Danish participants. Dietary intakes were completed using a web-based 7-d food diary. Stepwise multiple linear regression was used to identify the fatty acid and lipidomic variables that predict intakes of EPA + DHA and to determine lipidomic species that predict commonly used fatty acid biomarkers. RESULTS: Stepwise regression selected lipidomic variables with an R2 = 0.52 for predicting EPA + DHA intake compared to R2 = 0.40 for the selected fatty acid GC-based variables. More predictive models were generated when the lipidomic variables were selected for females only (R2 = 0.62, n = 68) and males only (R2 = 0.72, n = 52). Phosphatidylethanolamine plasmalogen species containing EPA or DHA tended to be the most predictive lipidomic variables. Stepwise regression also indicated that selected lipidomic variables can predict commonly used fatty acid GC-based n-3 PUFA biomarkers as the R2 values ranged from 0.84 to 0.91. CONCLUSIONS: Both fatty acid and lipidomic data can be used to predict EPA + DHA intakes, and fatty acid GC-based biomarkers can be emulated by lipidomic species. Lipidomic-based biomarkers appear to be influenced by sex differences, probably in n-3 PUFA and lipoprotein metabolism. These results improve our ability to understand the relationship between novel lipidomic data and GC fatty acid data and will increase our ability to apply lipidomic methods to fatty acid and lipid nutritional research.

Development of the gas chromatography/mass spectrometry-based aroma designer capable of modifying volatile chemical compositions in complex odors.

Many volatile organic compounds (VOCs) are used to produce various commercial products with aromas mimicking natural products. The VOCs responsible for aromas have been identified from many natural products. The current major strategy is to analyze chemical compositions and aroma qualities of individual VOCs using gas chromatography/mass spectrometry (GC/MS) and GC-olfactometry. However, such analyses cannot determine whether candidate VOCs contribute to the characteristic aroma in mixtures of many VOCs. In this study, we developed a GC/MS-based VOC collection/omission system that can modify the VOC compositions of samples easily and rapidly. The system is composed of GC/MS with a switching unit that can change gas flow routes between MS and a VOC collection device. We first applied this system to prepare gas samples for omission tests, and the aroma qualities of VOC mixtures with and without some VOCs were evaluated by panelists. If aroma qualities were different between the 2 samples, the omitted VOCs were likely key odorants. By collecting VOCs in a gas bag attached to the collection device and transferring some VOCs to MS, specific VOCs could be omitted easily from the VOC mixture. The system could prepare omission samples without chemical identification, preparation of each VOC, and laborious techniques for mixing VOCs, thus overcoming the limitations of previous methods of sample preparation. Finally, the system was used to prepare artificial aromas by replacing VOC compositions between different samples for screening of key odorants. In conclusion, the system developed here can improve aroma research by identifying key odorants from natural products.

Mechanical Interatomic Bond Formation in Ethanol and Methanol-Ethanol Mixture by Laser-Driven Shock Waves.

Molecules, which were predicted to be produced by C-C or C-O bond formation between ethanol molecules induced by a laser-driven shock wave, were identified by gas chromatography-mass spectrometry. Moreover, the laser irradiation of a methanol-ethanol mixture revealed the formation of C-C and C-O bonds between both components. Particularly, four hemiacetals (methoxymethanol, 1-methoxyethanol, ethoxymethanol, and 1-ethoxyethanol) were identified in the Ar-saturated alcohol samples, whereas acetalization dominated sufficiently in the CO2-saturated samples, significantly reducing the hemiacetals. It was verified that some molecules were produced by the dropout of an ethanol part during the C-C or C-O bond formation, supporting the contribution of laser-driven shock waves.

Suspect Screening Analysis of Pooled Human Serum Samples Using GC × GC/TOF-MS.

Humans interact with thousands of chemicals. This study aims to identify substances of emerging concern and in need of human health risk evaluations. Sixteen pooled human serum samples were constructed from 25 individual samples each from the National Institute of Environmental Health Sciences' Clinical Research Unit. Samples were analyzed using gas chromatography (GC) × GC/time-of-flight (TOF)-mass spectrometry (MS) in a suspect screening analysis, with follow-up confirmation analysis of 19 substances. A standard reference material blood sample was also analyzed through the confirmation process for comparison. The pools were stratified by sex (female and male) and by age (≤45 and >45). Publicly available information on potential exposure sources was aggregated to annotate presence in serum as either endogenous, food/nutrient, drug, commerce, or contaminant. Of the 544 unique substances tentatively identified by spectral matching, 472 were identified in females, while only 271 were identified in males. Surprisingly, 273 of the identified substances were found only in females. It is known that behavior and near-field environments can drive exposures, and this work demonstrates the existence of exposure sources uniquely relevant to females.

Plastic Quantification and Polyethylene Overestimation in Agricultural Soil Using Large-Volume Pyrolysis and TD-GC-MS/MS.

Quantification of microplastics in soil is needed to understand their impact and fate in agricultural areas. Often, low sample volume and removal of organic matter (OM) limit representative quantification. We present a method which allows simultaneous quantification of microplastics in homogenized, large environmental samples (>1 g) and tested polyethylene (PE), polyethylene terephthalate (PET), and polystyrene (PS) (200-400 µm) overestimation by fresh and diagenetically altered OM in agricultural soils using a new combination of large-volume pyrolysis adsorption with thermal desorption-gas chromatography-tandem mass spectrometry (TD-GC-MS/MS). Characteristic MS/MS profiles for PE, PET, and PS were derived from plastic pyrolysis and allowed for a new mass separation of PET. Volume-defined standard particles (125 × 125 × 20 µm3) were developed with the respective weight (PE: 0.48 ± 0.12, PET: 0.50 ± 0.10, PS: 0.31 ± 0.08 µg), which can be spiked into solid samples. Diagenetically altered OM contained compounds that could be incorrectly identified as PE and suggest a mathematical correction to account for OM contribution. With a standard addition method, we quantified PS, PET, and PEcorrected in two agricultural soils. This provides a base to simultaneously quantify a variety of microplastics in many environmental matrices and agricultural soil.

Unveiling Small-Sized Plastic Particles Hidden behind Large-Sized Ones in Human Excretion and Their Potential Sources.

Health risks of microplastic exposure have drawn growing global concerns due to the widespread distribution of microplastics in the environment. However, more evidence is needed to understand the exposure characteristics of microplastics owing to the limitation of current spectrum technologies, especially the missing information on small-sized particles. In the present study, laser direct infrared spectroscopy and thermal desorption-gas chromatography-mass spectrometry combined pyrolysis using a tubular furnace (TD-GC/MS) were employed to comprehensively detect the presence of plastic particles down to 0.22 µm in human excreted samples. The results showed that polyethylene (PE), polyvinyl chloride, PE terephthalate (PET), and polypropylene dominated large-sized (>20 µm) and small-sized plastic plastics (0.22-20 µm) in feces and urine. Moreover, fragments accounted for 60.71 and 60.37% in feces and urine, respectively, representing the most pervasive shape in excretion. Surprisingly, the concentration of small-sized particles was significantly higher than that of large-sized microplastics, accounting for 56.54 and 50.07% in feces (345.58 µg/g) and urine (6.49 µg/mL). Significant positive correlations were observed between the level of plastic particles in feces and the use of plastic containers and the consumption of aquatic products (Spearman correlation analysis, p < 0.01), suggesting the potential sources for plastic particles in humans. Furthermore, it is estimated that feces was the primary excretory pathway, consisting of 94.0% of total excreted microplastics daily. This study provides novel evidence regarding small-sized plastic particles, which are predominant fractions in human excretion, increasing the knowledge of the potential hazards of omnipresent microplastics to human exposure.

Volatilomes of human infection.

The human volatilome comprises a vast mixture of volatile emissions produced by the human body and its microbiomes. Following infection, the human volatilome undergoes significant shifts, and presents a unique medium for non-invasive biomarker discovery. In this review, we examine how the onset of infection impacts the production of volatile metabolites that reflects dysbiosis by pathogenic microbes. We describe key analytical workflows applied across both microbial and clinical volatilomics and emphasize the value in linking microbial studies to clinical investigations to robustly elucidate the metabolic species and pathways leading to the observed volatile signatures. We review the current state of the art across microbial and clinical volatilomics, outlining common objectives and successes of microbial-clinical volatilomic workflows. Finally, we propose key challenges, as well as our perspectives on emerging opportunities for developing clinically useful and targeted workflows that could significantly enhance and expedite current practices in infection diagnosis and monitoring.

Novel method for rapid monitoring of OPFRs by LLE and GC-MS as a tool for assessing biodegradation: validation and applicability.

Organophosphate flame retardants (OPFRs) are high-production volume chemicals widely present in environmental compartments. The presence of water-soluble OPFRs (tri-n-butyl phosphate (TnBP), tris(2-butoxyethyl) phosphate (TBEP), tris(2-chloroethyl) phosphate (TCEP), tris(2-chloroisopropyl) phosphate (TCPP), and triethyl phosphate (TEP)) in water compartments evidences the struggle of conventional wastewater treatment plants (WWTPs) to effectively eliminate these toxic compounds. This study reports for the first time the use of white-rot fungi as a promising alternative for the removal of these OPFRs. To accomplish this, a simple and cost-efficient quantification method for rapid monitoring of these contaminants' concentrations by GC-MS while accounting for matrix effects was developed. The method proved to be valid and reliable for all the tested parameters. Sample stability was examined under various storage conditions, showing the original samples to be stable after 60 days of freezing, while post-extraction storage techniques were also effective. Finally, a screening of fungal degraders while assessing the influence of the glucose regime on OPFR removal was performed. Longer chain organophosphate flame retardants, TBP and TBEP, could be easily and completely removed by the fungus Ganoderma lucidum after only 4 days. This fungus also stood out as the sole organism capable of partially degrading TCEP (35% removal). The other chlorinated compound, TCPP, was more easily degraded and 70% of its main isomer was removed by T. versicolor. However, chlorinated compounds were only partially degraded under nutrient-limiting conditions. TEP was either not degraded or poorly degraded, and it is likely that it is a transformation product from another OPFR's degradation. These results suggest that degradation of chlorinated compounds is dependent on the concentration of the main carbon source and that more polar OPFRs are less susceptible to degradation, given that they are less accessible to radical removal by fungi. Overall, the findings of the present study pave the way for further planned research and a potential application for the degradation of these contaminants in real wastewaters.

Solid-phase microextraction coupled to comprehensive multidimensional gas chromatography for food analysis.

Solid-phase microextraction and comprehensive multidimensional gas chromatography represent two milestone innovations that occurred in the field of separation science in the 1990s. They have a common root in their introduction and have found a perfect coupling in their evolution and applications. This review will focus on food analysis, where the paradigm has changed significantly over time, moving from a targeted analysis, focusing on a limited number of analytes at the time, to a more holistic approach for assessing quality in a larger sense. Indeed, not only some major markers or contaminants are considered, but a large variety of compounds and their possible interaction, giving rise to the field of foodomics. In order to obtain such detailed information and to answer more sophisticated questions related to food quality and authenticity, the use of SPME-GC × GC-MS has become essential for the comprehensive analysis of volatile and semi-volatile analytes. This article provides a critical review of the various applications of SPME-GC × GC in food analysis, emphasizing the crucial role this coupling plays in this field. Additionally, this review dwells on the importance of appropriate data treatment to fully harness the results obtained to draw accurate and meaningful conclusions.