Optimization and Validation of a Cheaper, Safer, and More Sustainable Methodology for Aflatoxins Determination in Rich-Lipidic Matrices (Pistachio Nuts) Using Deep Eutectic Solvent Extraction and UHPLC-FLD Analysis.

Aflatoxins pose a major health concern and require strict monitoring in food products. Existing methods rely on hazardous organic solvents for extraction, prompting the development of a greener alternative. This study explores deep eutectic solvents (DESs) for aflatoxin extraction from pistachios, a valuable food product prone to aflatoxin contamination. The proposed method utilizes DES extraction followed by solid-phase extraction cleanup and ultrahigh-performance liquid chromatography coupled with fluorescence detector analysis. Recovery rates ranged from 85.5 to 99.1% for pistachios spiked with 1-8 ng/g aflatoxins, in compliance with EU regulations, with coefficients of variation less than 2.94%. The method demonstrates good sensitivity with limits of detection and quantification in the range of 0.02-0.22 ng/g and 0.05-0.72 ng/g, respectively. Greenness assessment using AGREEPrep and White Analytical Chemistry metrics confirms its environmental sustainability. This approach offers a promising, safer, and more eco-friendly alternative for aflatoxin extraction from complex food matrices like pistachios.

Optimization of headspace high-capacity tool coupled to two-dimensional gas chromatography-mass spectrometry for mapping the volatile organic compounds of raw pistachios. A proof-of-concept on the classification ability by geographic origin.

An optimized procedure for extracting and analyzing raw pistachio volatiles was developed through headspace sampling with high-capacity tools and subsequent analysis using comprehensive two-dimensional gas chromatography coupled with mass spectrometry. The examination of 18 pistachio samples belonging to different geographic areas led to the identification of a set of 99 volatile organic compounds (VOCs). Molecules were putatively identified using linear retention index, mass spectra similarity, and two-dimensional plot location. The impact of preprocessing and processing techniques on the aligned data matrix from a set of samples of different geographical origins, after removing contaminants, was evaluated. The combination of scaling with log-transformation, normalization with z-score, and data reduction with random forest machine learning algorithm generated a panel of 16 discriminatory VOC molecules. As a proof of concept, raw pistachios' VOC profile was employed for the first time to tentatively classify them based on their geographical origin.

Defining a core breath profile for healthy, non-human primates.

Non-human primates remain the most useful and reliable pre-clinical model for many human diseases. Primate breath profiles have previously distinguished healthy animals from diseased, including non-human primates. Breath collection is relatively non-invasive, so this motivated us to define a healthy baseline breath profile that could be used in studies evaluating disease, therapies, and vaccines in non-human primates. A pilot study, which enrolled 30 healthy macaques, was conducted. Macaque breath molecules were sampled into a Tedlar bag, concentrated onto a thermal desorption tube, then desorbed and analyzed by comprehensive two-dimensional gas chromatography-time of flight mass spectrometry. These breath samples contained 2,017 features, of which 113 molecules were present in all breath samples. The core breathprint was dominated by aliphatic hydrocarbons, aromatic compounds, and carbonyl compounds. The data were internally validated with additional breath samples from a subset of 19 of these non-human primates. A critical core consisting of 23 highly abundant and invariant molecules was identified as a pragmatic breathprint set, useful for future validation studies in healthy primates.

Composition and nutritional values of fatty acids in marine organisms by one-step microwave-assisted extraction/derivatization and comprehensive two-dimensional gas chromatography -flame ionization detector.

This work reports the characterization of the lipidic fraction of seven species of marine organisms gathered along the shoreline of the Po Delta Park of Emilia-Romagna Region (Italy) and of the north Adriatic Sea. Two species of oysters (Crassostrea gigas and Ostrea edulis), two species of clams (Chamelea gallina and Ruditapes philippinarum), one species of mussel (Mytilus galloprovincialis), one species of macroalgae (Ulva rigida), and one species of spiny dogfish (Squalus acanthias) were analyzed to characterize their fatty acids profile and related nutritional value. The lipid fraction was simultaneously extracted and transesterified into fatty acid methyl esters (FAMEs) by using a recently developed one-step microwave-assisted extraction/derivatization (MAED) method. The obtained FAMEs extract was analyzed by a rapid comprehensive multidimensional gas chromatography (GC × GC) method (30 min). The system was equipped with a reverse set of columns (polar × non-polar) connected through a reversed fill/flush flow modulator. The GC × GC system was coupled with a flame-ionization detector (FID) for both qualitative and quantitative purposes. The MAED- GC × GC-FID methodology was suitable in the context of samples containing high percentages of omega-3 PUFA. A total of 82 FAMEs were tentatively identified using standards, literature data, and the two-dimensional plot location. FAME profiles obtained with the proposed approach were comparable with reference methods (AOCS Ce 2b-11), showing no significant differences. Moreover, to determine the food nutritional value of the samples investigated, the most common nutritional indices (index of atherogenicity, index thrombogenicity, hypocholesterolemic/hypercholesterolemic ratio, health-promoting index, unsaturation index, and the fish lipid quality index) were calculated from FAME profiles. Among the samples investigated, Squalus acanthias presented the best nutritional score, while Ruditapes philippinarum had the worst score in 3 out of 6 indices.

Microwave-assisted extraction in closed vessel in food analysis.

Microwave-assisted extraction (MAE) is an important technique in analytical chemistry. It offers several advantages over traditional extraction methods, such as improved extraction efficiency, shorter extraction times, reduced solvent consumption, and enhanced analyte recovery. Using microwaves, heat is directly applied to the sample, leading to rapid and efficient extraction of target compounds by enhancing the solubility and diffusion of the target compounds, thus requiring lower solvent volume. Therefore, MAE can be considered a more environmentally friendly and cost-effective option facilitating the transition toward greener and more sustainable analytical chemistry workflows. This contribution systematically reviews the application of MAE to a selection of target compounds/compounds classes of relevance for food quality and safety assessment. As inclusion criteria, MAE active temperature control and molecularly-resolved characterization of the extracts were considered. Contents include a brief introduction of the principles of operation, available systems characteristics, and key parameters influencing extraction efficiency and selectivity. The application section covers functional food components (e.g., phenols, diterpenes, and carotenoids), lipids, contaminants (e.g., polycyclic aromatic hydrocarbons and mineral oil hydrocarbons), pesticides, veterinary drug residues, and a selection of process contaminants and xenobiotics of relevance for food safety.

Impact of column temperature on triacylglycerol regioisomers separation in silver ion liquid chromatography using heptane-based mobile phases.

This work presents the investigation of the use of heptane as an alternative and less toxic mobile phase to the most used hexane for triacylglycerols (TAGs) analysis in silver ion high-performance liquid chromatography (Ag+-HPLC). The impact of column temperature (in the 5 °C-35 °C range) on the retention and resolution of five pairs of regioisomers relevant for the confectionery industry was investigated using a heptane-based mobile phase modified with acetonitrile (ACN). The retention behaviour was compared for a standard TAG mixture and an interesterified cocoa butter. The temperature effect previously observed with hexane-based mobile phases was confirmed for this new system, and it was also observed that the ACN concentration had an important impact on the strength of the temperature effect, with a higher ACN concentration leading to a lesser impact of temperature on the TAGs' elution behaviour. In general, the study allowed to conclude on the equivalence of hexane and heptane for TAGs regioisomers separation in Ag+-HPLC, independently of the used temperature or the ACN concentration. In addition, the applicability of heptane-based mobile phases for the separation of TAGs regioisomers was demonstrated on three other confectionary fat samples, namely palm olein, interesterified palm olein, and interesterified shea olein.

Current Developments of Analytical Methodologies for Aflatoxins' Determination in Food during the Last Decade (2013-2022), with a Particular Focus on Nuts and Nut Products.

This review aims to provide a clear overview of the most important analytical development in aflatoxins analysis during the last decade (2013-2022) with a particular focus on nuts and nuts-related products. Aflatoxins (AFs), a group of mycotoxins produced mainly by certain strains of the genus Aspergillus fungi, are known to impose a serious threat to human health. Indeed, AFs are considered carcinogenic to humans, group 1, by the International Agency for Research on Cancer (IARC). Since these toxins can be found in different food commodities, food control organizations worldwide impose maximum levels of AFs for commodities affected by this threat. Thus, they represent a cumbersome issue in terms of quality control, analytical result reliability, and economical losses. It is, therefore, mandatory for food industries to perform analysis on potentially contaminated commodities before the trade. A full perspective of the whole analytical workflow, considering each crucial step during AFs investigation, namely sampling, sample preparation, separation, and detection, will be presented to the reader, focusing on the main challenges related to the topic. A discussion will be primarily held regarding sample preparation methodologies such as partitioning, solid phase extraction (SPE), and immunoaffinity (IA) related methods. This will be followed by an overview of the leading analytical techniques for the detection of aflatoxins, in particular liquid chromatography (LC) coupled to a fluorescence detector (FLD) and/or mass spectrometry (MS). Moreover, the focus on the analytical procedure will not be specific only to traditional methodologies, such as LC, but also to new direct approaches based on imaging and the ability to detect AFs, reducing the need for sample preparation and separative techniques.

The contribution of high-resolution GC separations in plastic recycling research.

One convenient strategy to reduce environmental impact and pollution involves the reuse and revalorization of waste produced by modern society. Nowadays, global plastic production has reached 367 million tons per year and because of their durable nature, their recycling is fundamental for the achievement of the circular economy objective. In closing the loop of plastics, advanced recycling, i.e., the breakdown of plastics into their building blocks and their transformation into valuable secondary raw materials, is a promising management option for post-consumer plastic waste. The most valuable product from advanced recycling is a fluid hydrocarbon stream (or pyrolysis oil) which represents the feedstock for further refinement and processing into new plastics. In this context, gas chromatography is currently playing an important role since it is being used to study the pyrolysis oils, as well as any organic contaminants, and it can be considered a high-resolution separation technique, able to provide the molecular composition of such complex samples. This information significantly helps to tailor the pyrolysis process to produce high-quality feedstocks. In addition, the detection of contaminants (i.e., heteroatom-containing compounds) is crucial to avoid catalytic deterioration and to implement and design further purification processes. The current review highlights the importance of molecular characterization of waste stream products, and particularly the pyrolysis oils obtained from waste plastics. An overview of relevant applications published recently will be provided, and the potential of comprehensive two-dimensional gas chromatography, which represents the natural evolution of gas chromatography into a higher-resolution technique, will be underlined.

Analysis of mixed plastic pyrolysis oil by comprehensive two-dimensional gas chromatography coupled with low- and high-resolution time-of-flight mass spectrometry with the support of soft ionization.

According to the annual production of plastics worldwide, in 2020 about 370 million tons of plastic were produced in the world. Chemical recycling, particularly pyrolysis of plastic wastes, could be a valuable solution to resolve these problems and provide an alternative pathway to produce "recycled" chemical products for the petrochemical industry. Nevertheless, the pyrolysis oils need a detailed characterization before the upgrading test to re-use them to generate new recycled products. Multidimensional gas chromatography coupled with both low- and high-resolution time-of-flight mass spectrometers was employed for a detailed investigation among and within different chemical classes present in bio-plastic oil. The presence of several isomeric species as well as homologs series did not allow a reliable molecular identification, except for a few compounds that showed both MS similarity >800/1000 and retention index within ±20. Indeed, the identification of several isomeric species was assessed by high-resolution mass spectrometry equipped with photoionization interface. This soft ionization mode was an additional filter in the identification step allowing unambiguous identification of analytes not identified by the standard electron ionization mode at 70 eV. The injection method was also optimized using a central composite design to successfully introduce a wide range of carbon number compounds without discrimination of low/high boiling points.

Comprehensive Chemical Characterization of Chia (Salvia hispanica L.) Seed Oil with a Focus on Minor Lipid Components.

A comprehensive chemical characterization of different lipid components, namely fatty acid composition after derivatization in fatty acid methyl esters (FAMEs), triacylglycerols (TAGs), phospholipids (PLs), free fatty acids (FFAs), sterols, carotenoids, tocopherols, and polyphenols in Chia seed oil, obtained by Soxhlet extraction, was reported. Reversed phase liquid chromatography (RP-LC) coupled to UV and mass spectrometry (MS) detectors was employed for carotenoids, polyphenols, and TAGs determination; normal phase-LC in combination with fluorescence detector (FLD) was used for tocopherols analysis; PL and FFA fractions were investigated after a rapid solid phase extraction followed by RP-LC-MS and NanoLC coupled to electron ionization (EI) MS, respectively. Furthermore, gas chromatography (GC)-flame ionization (FID) and MS detectors were used for FAMEs and sterols analysis. Results demonstrated a significant content of bioactive compounds, such as the antioxidant tocopherols (22.88 µg mL-1), and a very high content of essential fatty acids (81.39%), namely α-linolenic (62.16%) and linoleic (19.23%) acids. In addition, for the best of authors knowledge, FFA profile, as well as some carotenoid classes has been elucidated for the first time. The importance of free fatty acids in vegetable matrices is related to the fact that they can be readily involved in metabolic processes or biosynthetic pathways of the plant itself. For a fast and reliable determination of this chemical class, a very innovative and sensitive NanoLC-EI-MS analytical determination was applied.

Deeper investigation of oxygen-containing compounds in oleaginous feedstock (animal fat) by preparative column chromatography and comprehensive two-dimensional gas chromatography coupled with high-resolution time-of-flight mass spectrometry.

The production of renewable fuels as biodiesel and bio-jet fuel is usually originated by the transformation and processing of oleaginous feedstocks, mainly composed of triacylglycerols. Currently, a significant part of the triacylglycerol production relies on grassy oil crops or other woody oil plants, representing more than 120 million metric tons every year. Considering that the worldwide triacylglycerol demand is expected to rise in the future, alternative routes are necessary to ensure a sustainable biodiesel industry and limit diesel price volatility. In this context, the use of animal fats could be an interesting alternative for biodiesel production as the production of animal byproducts represents nearly 17 million tons per year in the European Union only (2020). Animal fats, however, contain large amounts of no-esterified fatty acids and other oxygen compounds, reducing the yield of biodiesel. Therefore, a specific pretreatment is needed before the trans-esterification process. The setup of such appropriate pretreatments requires detailed upstream characterization of the minor components present in the feedstock. For this purpose, the minor component profile of animal fat was investigated by comprehensive two-dimensional gas chromatography coupled with high-resolution time-of-flight mass spectrometry. This was preceded by an innovative sample fractionation and focalization of these minor components by a preparative liquid chromatographic column method. The overall method permitted to extract different levels of information from the two-dimensional chromatograms, leading to a tentative identification of more than 150 compounds, mainly oxygenated, belonging to different chemical classes.

Investigating Bacterial Volatilome for the Classification and Identification of Mycobacterial Species by HS-SPME-GC-MS and Machine Learning.

Species of Mycobacteriaceae cause disease in animals and humans, including tuberculosis and leprosy. Individuals infected with organisms in the Mycobacterium tuberculosis complex (MTBC) or non-tuberculous mycobacteria (NTM) may present identical symptoms, however the treatment for each can be different. Although the NTM infection is considered less vital due to the chronicity of the disease and the infrequency of occurrence in healthy populations, diagnosis and differentiation among Mycobacterium species currently require culture isolation, which can take several weeks. The use of volatile organic compounds (VOCs) is a promising approach for species identification and in recent years has shown promise for use in the rapid analysis of both in vitro cultures as well as ex vivo diagnosis using breath or sputum. The aim of this contribution is to analyze VOCs in the culture headspace of seven different species of mycobacteria and to define the volatilome profiles that are discriminant for each species. For the pre-concentration of VOCs, solid-phase micro-extraction (SPME) was employed and samples were subsequently analyzed using gas chromatography-quadrupole mass spectrometry (GC-qMS). A machine learning approach was applied for the selection of the 13 discriminatory features, which might represent clinically translatable bacterial biomarkers.

Exploring 20 eV electron impact ionization in gas chromatography-tandem mass spectrometry for the determination of estrogenic compounds.

In electron ionization mass spectrometry (MS), the generation of characteristic fragmentation patterns allows reliable and sensitive identification of compounds. However, loss or a less intense signal of the molecular ion (or more diagnostic ions) can often be observed, which can be detrimental for identification and/or sensitivity, even when MS/MS approaches are applied for quantification. The benefits of applying lower ionization energy (i.e., 20 eV compared to 70 eV) using a gas chromatography (GC) - tandem MS (MS/MS) instrument were investigated in the detection of three estrogenic compounds, namely estrone (E1), 17ß-estradiol (E2), and 17α-ethynylestradiol (EE2), emerging aquatic pollutants included in the European Commission Watch List. As expected, the relative intensity of molecular ions (M+.) or high-mass fragments closely related (M+.-CH3) increased significantly at 20 eV compared to 70 eV (from 4.6 % to 35.0 % for EE2, from 22.5 % to 87.3 % for E2, and from 76 % to 100 % for E1). This change in the spectrum profile led to an overall increase in the sensitivity of the compounds when detected using the multiple reaction monitoring mode. These results were compared with the instrumental limit of quantification obtained in liquid chromatography - MS/MS showing a limit of quantification of about 100-folds lower for GC-MS/MS and a completely neglectable matrix effect, thus posing the base for the development of a miniaturized sample preparation method (with an overall lower concentration factor) to achieve the challenging low limits of detection required by the EU regulation for estrogenic compounds.

Advanced mono- and multi-dimensional gas chromatography-mass spectrometry techniques for oxygen-containing compound characterization in biomass and biofuel samples.

A wide variety of biomass, from triglycerides to lignocellulosic-based feedstock, are among promising candidates to possibly fulfill requirements as a substitute for crude oils as primary sources of chemical energy feedstock. During the feedstock processing carried out to increase the H:C ratio of the products, heteroatom-containing compounds can promote corrosion, thus limiting and/or deactivating catalytic processes needed to transform the biomass into fuel. The use of advanced gas chromatography techniques, in particular multi-dimensional gas chromatography, both heart-cutting and comprehensive coupled to mass spectrometry, has been widely exploited in the field of petroleomics over the past 30 years and has also been successfully applied to the characterization of volatile and semi-volatile compounds during the processing of biomass feedstock. This review intends to describe advanced gas chromatography-mass spectrometry-based techniques, mainly focusing in the period 2011-early 2020. Particular emphasis has been devoted to the multi-dimensional gas chromatography-mass spectrometry techniques, for the isolation and characterization of the oxygen-containing compounds in biomass feedstock. Within this context, the most recent advances to sample preparation, derivatization, as well as gas chromatography instrumentation, mass spectrometry ionization, identification, and data handling in the biomass industry, are described.

Current developments in LC-MS for pharmaceutical analysis.

Liquid chromatography (LC) based techniques in combination with mass spectrometry (MS) detection have had a large impact on the development of new pharmaceuticals in the past decades. Continuous improvements in mass spectrometry and interface technologies, combined with advanced liquid chromatographic techniques for high-throughput qualitative and quantitative analysis, have resulted in a wider scope of applications in the pharmaceutical field. LC-MS tools are increasingly used to analyze pharmaceuticals across a variety of stages in their discovery and development. These stages include drug discovery, product characterization, metabolism studies (in vitro and in vivo) and the identification of impurities and degradation products. The increase in LC-MS applications has been enormous, with retention times and molecular weights (and related fragmentation patterns) emerging as crucial analytical features in the drug development process. The goal of this review is to give an overview of the main developments in LC-MS based techniques for the analysis of small pharmaceutical molecules in the last decade and give a perspective on future trends in LC-MS in the pharmaceutical field.

Evaluation of different adsorbent materials for the untargeted and targeted bacterial VOC analysis using GC×GC-MS.

The analysis of bacterial volatile organic compounds has gained attraction as a non-invasive way to identify disease-causing organisms, given that bacteria have unique metabolisms and volatile metabolic byproducts. In the present research, different adsorbent materials (Carbopack Y, X, B, Carboxen 1000 and Tenax TA), packed singularly or in combination, were compared in terms of sampling performance (sensitivity, repeatability and selectivity) for the extraction of standards and bacterial volatile metabolites in vitro (from Staphylococcus aureus, Pseudomonas aeruginosa, and Escherichia coli). After extraction, bacterial volatile organic compounds were desorbed and analyzed in a comprehensive two-dimensional gas chromatography system coupled to a time-of-flight mass spectrometer (GC × GC-ToF MS). The results show that Tenax has the greater ability to extract the standard mix as well as volatile organic compounds with better repeatability (4-26 RSD%), higher sensitivity (on average ∼24 fold) compared to Carbopack Y, X and Carboxen 1000 tube, which followed in terms of performance. In addition, Tenax confirmed the best sensitivity and discriminatory power with no misclassification in the untargeted and unsupervised analysis for the differentiation of the bacterial species.

Exhaled human breath analysis in active pulmonary tuberculosis diagnostics by comprehensive gas chromatography-mass spectrometry and chemometric techniques.

Tuberculosis (TB) is the deadliest infectious disease, and yet accurate diagnostics for the disease are unavailable for many subpopulations. In this study, we investigate the possibility of using human breath for the diagnosis of active TB among TB suspect patients, considering also several risk factors for TB for smokers and those with human immunodeficiency virus (HIV). The analysis of exhaled breath, as an alternative to sputum-dependent tests, has the potential to provide a simple, fast, non-invasive, and readily available diagnostic service that could positively change TB detection. A total of 50 individuals from a clinic in South Africa were included in this pilot study. Human breath has been investigated in the setting of active TB using the thermal desorption-comprehensive two-dimensional gas chromatography-time of flight mass spectrometry methodology and chemometric techniques. From the entire spectrum of volatile metabolites in breath, three machine learning algorithms (support vector machines, partial least squares discriminant analysis, and random forest) to select discriminatory volatile molecules that could potentially be useful for active TB diagnosis were employed. Random forest showed the best overall performance, with sensitivities of 0.82 and 1.00 and specificities of 0.92 and 0.60 in the training and test data respectively. Unsupervised analysis of the compounds implicated by these algorithms suggests that they provide important information to cluster active TB from other patients. These results suggest that developing a non-invasive diagnostic for active TB using patient breath is a potentially rich avenue of research, including among patients with HIV comorbidities.

Investigation of mycobacteria fatty acid profile using different ionization energies in GC-MS.

Gas chromatography (GC) coupled with electron ionization (EI) mass spectrometry (MS) is a well-established technique for the analysis of volatile and semi-volatile compounds. The main advantage is the highly repeatable fragmentation of the compounds into the ion source, generating intense and diagnostic fragmentation when the ionization is performed at 70 eV; this is considered the standard ionization condition and has been used for creating many established databases, which are of great support in the analyte identification process. However, such an intense fragmentation often causes the loss of the molecular ion or more diagnostic ions, which can be detrimental for the identification of homologous series or isomers, as for instance fatty acids. To obtain this information chemical or soft ionization can be used, but dedicated ion sources and conditions are required. In this work, we explored different ionization voltages in GC-EI-MS to preserve the intensity of the molecular ion using a conventional quadrupole MS. Twenty, 30, 50, and 70 eV were tested using a mixture of fatty acid methyl esters standards. Intensity and repeatability of the most informative ions were compared. Twenty and 70 eV were then used to analyze the fatty acid composition of six different strains of mycobacteria. Two approaches were used for elaborating the data: (1) a single average spectrum of the entire chromatogram was derived, which can be considered (in terms of concept) as a direct EI-MS analysis; (2) the actual chromatographic separation of the compounds was considered after automatic alignment. The results obtained are discussed herein. Graphical abstract ᅟ.

SPME-GC×GC-TOF MS fingerprint of virally-infected cell culture: Sample preparation optimization and data processing evaluation.

Untargeted metabolomics study of volatile organic compounds produced by different cell cultures is a field that has gained increasing attention over the years. Solid-phase microextraction has been the sampling technique of choice for most of the applications mainly due to its simplicity to implement. However, a careful optimization of the analytical conditions is necessary to obtain the best performances, which are highly matrix-dependent. In this work, five different solid-phase microextraction fibers were compared for the analysis of the volatiles produced by cell culture infected with the human respiratory syncytial virus. A central composite design was applied to determine the best time-temperature combination to maximize the extraction efficiency and the salting-out effect was evaluated as well. The linearity of the optimized method, along with limits of detection and quantification and repeatability was assessed. Finally, the effect of i) different normalization techniques (i.e. z-score and probabilistic quotient normalization), ii) data transformation (i.e. in logarithmic scale), and iii) different feature selection algorithms (i.e. Fisher ratio and random forest) on the capability of discriminating between infected and not-infected cell culture was evaluated.