Exploration of environmental contaminants in honeybees using GC-TOF-MS and GC-Orbitrap-MS

Evaluation of the honeybee exposome in European apiaries by combining passive samplers and liquid chromatography with Zeno trap-time-of-flight mass spectrometry

This study introduces an analytical methodology that combines passive sampling with ultra-high pressure liquid chromatography coupled with a high-end quadrupole-time-of-flight mass spectrometer (UHPLC-QTOF-MS) for monitoring the honeybee (Apis mellifera L.) exposome across various European regions and seasons. The sampling methodology employs the recently developed adsorb pesticide in-hive strips (APIStrip) passive samplers, which use TENAX® TA adsorbent, to collect a wide range of chemicals when placed inside beehives. Following acetonitrile-based desorption, extracts were analyzed by UHPLC-QTOF-MS, equipped with an advanced ion trap -the Zeno trap- that enhances tandem-mass spectrometry (MS/MS) signals and improves mass accuracy, facilitating efficient feature annotation. A non-targeted analysis (NTA) approach, combined with multivariate analysis, was used to simultaneously identify exposure analytes (e.g.natural products) and effect-related metabolites associated with honeybee health and condition (e.g. pheromones and other compounds emitted by bees). This methodology revealed geographical and seasonal variations in the chemical profiles of honeybee hives. In the evaluated Nordic countries, natural products from plants and pollen, along with bee-emitted substances such us neurotransmitters and pheromones, were prevalent. Seasonal analysis in Denmark revealed distinct chemical profiles associated with blooming flowers and peak brood rearing activity in April. This integrated, non-invasive methodology has proven highly effective in assessing the honeybee exposome, providing valuable insights into how environmental factors influence the chemical profiles emitted by bees.

Approaches for GC-HRMS Screening of Organic Microcontaminants: GC-APCI-IMS-QTOF versus GC-EI-QOrbitrap

This study explores the capabilities of GC-APCI-IMS-QTOF MS and GC-EI-QOrbitrap MS in screening applications and different strategies for wide-scope screening of organic microcontaminants using target suspect and nontarget approaches. On one side, GC-APCI-IMS-QTOF MS excels at preserving molecular information and adds ion mobility separation, facilitating screening through the list of componentized features containing accurate mass, retention time, CCS, and fragmentation data. On the other side, the extensive and robust fragmentation of GC-EI-QOrbitrap MS allows the application of different strategies for target and nontarget approaches using the NIST library spectra. Our findings revealed that GC-EI-QOrbitrap MS is more sensitive in target approaches. Automated workflows for suspect screening in GC-APCI-IMS-QTOF MS minimize false annotations but face challenges with false negatives due to in-source fragmentation and limitations when using in silico fragmentation tools. Conversely, a nontarget approach in GC-EI-QOrbitrap MS can reliably identify unknowns but results in more false annotations in complex matrices. This work highlights the strengths and limitations of each system and guides for their optimal application for wide-scope screening in environmental and food safety applications.

Microfluidic synthesis of gold nanoparticle-doped microspherical photonic crystal as SERS substrate for methylene blue detection

A novel microfluidic approach is presented for the one-step synthesis of gold nanoparticle-doped microspherical photonic crystal (AuNP-MPC) for ultrasensitive surface-enhanced Raman spectroscopy (SERS) detection of methylene blue (MB), a common environmental pollutant. The AuNP-MPC microspheres exhibited excellent SERS activity due to the surface plasmon resonance of Au nanoparticles. And the SERS signal was significantly enhanced by strategically manipulating the photonic band gap (PBG) of the AuNP-MPC microspheres to achieve optimal overlap with the excitation laser wavelength. The SERS signal of MB was significantly enhanced by this, reaching an EF as high as 3.03 × 106. The AuNP-MPC microspheres demonstrated rapid adsorption of MB within just 5 min, making them suitable for rapid detection applications. Notably, the limit of quantification was as low as 1 × 10-8 mol/L, highlighting the exceptional sensitivity of this approach. Furthermore, the AuNP-MPC microspheres exhibited excellent homogeneity, reproducibility, and stability of SERS signals, which are crucial qualities for practical SERS applications. This work presents a promising avenue for developing SERS-active microfluidic platforms for the rapid detection of trace organic pollutants in environmental monitoring.

Utilization of AI - reshaping the future of food safety, agriculture and food security - a critical review

Artificial intelligence is an emerging technology which harbors a suite of mechanisms that have the potential to be leveraged for reaping value across multiple domains. Lately, there is an increased interest in embracing applications associated with Artificial Intelligence to positively contribute to food safety. These applications such as machine learning, computer vision, predictive analytics algorithms, sensor networks, robotic inspection systems, and supply chain optimization tools have been established to contribute to several domains of food safety such as early warning of outbreaks, risk prediction, detection and identification of food associated pathogens. Simultaneously, the ambition toward establishing a sustainable food system has motivated the adoption of cutting-edge technologies such as Artificial Intelligence to strengthen food security. Given the myriad challenges confronting stakeholders in their endeavors to safeguard food security, Artificial Intelligence emerges as a promising tool capable of crafting holistic management strategies for food security. This entails maximizing crop yields, mitigating losses, and trimming operational expenses. AI models present notable benefits in efficiency, precision, uniformity, automation, pattern identification, accessibility, and scalability for food security endeavors. The escalation in the global trend for adopting alternative protein sources such as edible insects and microalgae as a sustainable food source reflects a growing recognition of the need for sustainable and resilient food systems to address the challenges of population growth, environmental degradation, and food insecurity. Artificial Intelligence offers a range of capabilities to enhance food safety in the production and consumption of alternative proteins like microalgae and edible insects, contributing to a sustainable and secure food system.

Identification and quantification of flavor compounds in smoked tuna fish based on GC-Orbitrap volatolomics approach

Cold smoking enhances the appeal of fish products, offering consumers a smooth texture and a delicate smoky flavor. This study aims to explore variations in the volatile profile from different exposure times during cold smoking processing (light, moderate, and full-cure) in tune samples. An innovative untargeted analytical approach, headspace solid-phase microextraction combined with gas chromatography and a hybrid quadrupole-orbitrap mass analyzer, was employed to identify 86 volatiles associated with the cold smoking process. Most of these compounds, including phenols, furan derivates, aldehydes, cyclic ketones, and different aromatic species, were found to contribute to the smoke odor. The development of a QuEChERS-based extraction and clean-up method facilitated the quantification of 25 relevant smoky markers across all smoking degrees, revealing significant concentration differences after 15 h of smoking. This research sheds light on the dynamics of cold smoking impact and its on the flavor profile and safety quality of processed fish products.

Nitrophenols in the environment: An update on pretreatment and analysis techniques since 2017

Nitrophenols, a versatile intermediate, have been widely used in leather, medicine, chemical synthesis, and other fields. Because these components are widely applied, they can enter the environment through various routes, leading to many hazards and toxicities. There has been a recent surge in the development of simple, rapid, environmentally friendly, and effective techniques for determining these environmental pollutants. This review provides a comprehensive overview of the latest research progress on the pretreatment and analysis methods of nitrophenols since 2017, with a focus on environmental samples. Pretreatment methods include liquid-liquid extraction, solid-phase extraction, dispersive extraction, and microextraction methods. Analysis methods mainly include liquid chromatography-based methods, gas chromatography-based methods, supercritical fluid chromatography. In addition, this review also discusses and compares the advantages/disadvantages and development prospects of different pretreatment and analysis methods to provide a reference for further research.

Optimization and uncertainty assessment of a gas chromatography coupled to Orbitrap mass spectrometry method to determine organic contaminants in blood: A case study of an endangered seabird

Birds are excellent bioindicators of environmental pollution, and blood provides information on contaminant exposure, although its analysis is challenging because of the low volumes that can be sampled. The objective of the present study was to optimize and validate a miniaturized and functional extraction and analytical method based on gas chromatography coupled to Orbitrap mass spectrometry (GCOrbitrap-MS) for the trace analysis of contaminants in avian blood. Studied compounds included 25 organochlorine pesticides (OCPs), 6 polychlorinated biphenyls (PCBs), 8 polybrominated diphenyl ethers (PBDEs) and 15 polycyclic aromatic hydrocarbons (PAHs). Four extraction and clean-up conditions were optimized and compared in terms of efficiency, accuracy, and uncertainty assessment. Extraction with hexane:dichloromethane and miniaturized Florisil pipette clean-up was the most adequate considering precision and accuracy, time, and costs, and was thereafter used to analyse 20 blood samples of a pelagic seabird, namely the Bermuda petrel (Pterodroma cahow). This species, endemic to the Northwest Atlantic, is among the most endangered seabirds of the region that in the '60 faced a decrease in the breeding success likely linked to a consistent exposure to dichloro-diphenyl-trichloroethane (DDT). Indeed, p,p'-DDE, the main DDT metabolite, was detected in all samples and ranged bewteen 1.13 and 6.87 ng/g wet weight. Other ubiquitous compounds were PCBs (ranging from 0.13 to 6.76 ng/g ww), hexachlorobenzene, and mirex, while PAHs were sporadically detected at low concentrations, and PBDEs were not present. Overall, the extraction method herein proposed allowed analysing very small blood volumes (∼ 100 µL), thus respecting ethical principles prioritising the application of less-invasive sampling protocols, fundamental when studying threatened avian species.

The main strategies for soil pollution apportionment: A review of the numerical methods

Nowadays, a large number of compounds with different physical and chemical properties have been determined in soil. Environmental behaviors and source identification of pollutants in soil are the foundation of soil pollution control. Identification and quantitative analysis of potential pollution sources are the prerequisites for its prevention and control. Many efforts have made to develop methods for identifying the sources of soil pollutants. These efforts have involved the measurement of source and receptor parameters and the analysis of their relationships via numerical statistics methods. We have comprehensively reviewed the progress made in the development of source apportionment methodologies to date and present our synthesis. The numerical methods, such as spatial geostatistics analysis, receptor models, and machine learning methods are addressed in depth. In most cases, however, the effectiveness of any single approach for source apportionment remains limited. Combining multiple methods to address soil quality problems can reduce uncertainty about the sources of soil pollution. This review also constructively highlights the key strategies of combining mathematical models with the assessment of chemical profiles to provide more accurate source attribution. This review intends to provide a comprehensive summary of source apportionment methodologies to help promote further development.

Nontargeted analysis and comparison strategies for volatile and semivolatile substances in toys made of different materials

A nontargeted broad-spectrum analysis method for unknown volatile and semivolatile substances in toys was established by gas chromatography-Orbitrap high-resolution mass spectrometry. Based on the NIST spectrum library, unknown substances could be accurately identified by comprehensive scoring, retention index, chemical ionization, and fine comparison of ion fragments. For substances not included in the library, the molecular formulas of unknown substances were retrieved through online compound databases. Possible structural formulas were verified by high-resolution spectra and fragmentation mechanisms. Taking teether toys as an example, the substances differences of products made of different materials were compared through the digitization of chemical composition. Specifically, 59 substances were identified in 50 teether toys. The toys made of two different materials each had their own substance distribution, and the types and quantities of substances in thermoplastic polyurethanes samples were more than those in silicone samples. Substances with high risk included phenol, N-methylaniline, cyclohexanone, and 4-tert-amylphenol. This work can serve as a reference for the identification of unknown substances in toys and other products, as well as for the comparison the chemical composition of products made of different materials. Thus, this work has positive significance in promoting the quality and safety of toys and reducing chemical harm to children.

A high-resolution Orbitrap Mass spectral library for trace volatile compounds in fruit wines

The overall aroma is an important factor of the sensory quality of fruit wines, which attributed to hundreds of volatile compounds. However, the qualitative determination of trace volatile compounds is considered to be very challenging work. GC-Orbitrap-MS with high resolution and high sensitivity provided more possibilities for the determination of volatile compounds, but without the high-resolution mass spectral library. For accuracy of qualitative determination in fruit wines by GC-Orbitrap-MS, a high-resolution mass spectral library, including 76 volatile compounds, was developed in this study. Not only the HRMS spectrum but also the exact ion fragment, relative abundance, retention indices (RI), CAS number, chemical structure diagram, aroma description and aroma threshold (ortho-nasally) were provided and were shown in a database website (Food Flavor Laboratory, http://foodflavorlab.cn/). HRMS library was used to successfully identify the volatile compounds mentioned above in 16 fruit wines (5 blueberry wines, 6 goji berry wines and 5 hawthorn wines). The library was developed as an important basis for further understanding of trace volatile compounds in fruit wines.

Measurement(s)	volatile compounds
Technology Type(s)	GC-Orbitrap-MS

Benefits of Ion Mobility Separation in GC-APCI-HRMS Screening: From the Construction of a CCS Library to the Application to Real-World Samples

The performance of gas chromatography (GC) combined with the improved identification properties of ion mobility separation coupled to high-resolution mass spectrometry (IMS-HRMS) is presented as a promising approach for the monitoring of (semi)volatile compounds in complex matrices. The soft ionization promoted by an atmospheric pressure chemical ionization (APCI) source designed for GC preserves the molecular and/or quasi-molecular ion information enabling a rapid, sensitive, and efficient wide-scope screening. Additionally, ion mobility separation (IMS) separates species of interest from coeluting matrix interferences and/or resolves isomers based on their charge, shape, and size, making IMS-derived collision cross section (CCS) a robust and matrix-independent parameter comparable between instruments. In this way, GC-APCI-IMS-HRMS becomes a powerful approach for both target and suspect screening due to the improvements in (tentative) identifications. In this work, mobility data for 264 relevant multiclass organic pollutants in environmental and food-safety fields were collected by coupling GC-APCI with IMS-HRMS, generating CCS information for molecular ion and/or protonated molecules and some in-source fragments. The identification power of GC-APCI-IMS-HRMS for the studied compounds was assessed in complex-matrix samples, including fish feed extracts, surface waters, and different fruit and vegetable samples.

The Oral Wound Healing Potential of Thai Propolis Based on Its Antioxidant Activity and Stimulation of Oral Fibroblast Migration and Proliferation

Introduction. Propolis has demonstrated wound healing effects. Propolis’ effects vary based on its composition and geographical origin. However, there are few reports on the effects of propolis on oral wound healing. The aim of this study was to evaluate the antioxidant and in vitro gingival wound healing effects of the n-hexane extract of propolis (HEP), ethyl acetate extract of propolis (EEP), and aqueous extract of propolis (AEP) fractions of the ethanol extract of Thai propolis. Materials and Methods. The crude ethanol extract of propolis was obtained by maceration with 95% ethanol that was sequentially fractionated with hexane, ethyl acetate, and distilled water. The chemical profiles of the samples were assessed by thin-layer chromatography (TLC) and gas chromatography-mass spectrometry (GC-MS). Antioxidant activity was determined using DPPH and FRAP assays. The effects of the propolis fractions on human gingival fibroblast (HGF) proliferation, migration, and in vitro wound healing were determined by MTT, modified Boyden chamber, and scratch assay, respectively. Results. We found that solvent polarity greatly affected the extract yield and TLC profiles. The highest extract yield was found in HEP (38.88%), followed by EEP (19.8%) and AEP (1.42%). TLC revealed 7 spots in the crude ethanol extract (Rf 0.36–0.80), 6 spots in HEP (Rf 0.42–0.80) and EEP (Rf 0.36–0.72), and 4 spots in AEP (Rf 0.17–0.79). GC-MS analysis revealed a high amount of triterpenoids in HEP (82.97%) compared with EEP (28.96%). However, no triterpenoid was found in AEP. The highest antioxidant activity and stimulation of HGF proliferation were observed in HEP, followed by EEP and AEP. HEP and EEP, but not AEP, enhanced HGF migration. However, all propolis fractions induced wound closure. Conclusions. HEP contained a large amount of triterpenoids. Antioxidant and in vitro wound closure effects were found in HEP, EEP, and AEP fractions.

Application of a novel prioritisation strategy using non-target screening for evaluation of temporal trends (1969-2017) of contaminants of emerging concern (CECs) in archived lynx muscle tissue samples

Most environmental monitoring studies of contaminants of emerging concern (CECs) focus on aquatic species and target specific classes of CECs. Even with wide-scope target screening methods, relevant CECs may be missed. In this study, non-target screening (NTS) was used for tentative identification of potential CECs in muscle tissue of the terrestrial top predator Eurasian lynx (Lynx lynx). Temporal trend analysis was applied as a prioritisation tool for archived samples, using univariate statistical tests (Mann-Kendall and Spearman rank). Pooled lynx muscle tissue collected from 1969 to 2017 was analysed with an eight-point time series using a previously validated screening workflow. Following peak detection, peak alignment, and blank subtraction, 12,941 features were considered for statistical analysis. Prioritisation by time-trend analysis detected 104 and 61 features with statistically significant increasing and decreasing trends, respectively. Following probable molecular formula assignment and elucidation with MetFrag, two compounds with increasing trends, and one with a decreasing trend, were tentatively identified. These results show that, despite low expected concentration levels and high matrix effects in terrestrial species, it is possible to prioritise CECs in archived lynx samples using NTS and univariate statistical approaches.

Non-targeted analysis of unknown volatile chemicals in medical masks

This paper reports the non-targeted analysis of unknown volatile chemicals in medical masks through headspace gas chromatography-Orbitrap high-resolution mass spectrometry. In view of the difficulties that may be encountered in the qualitative analysis of unknown substances, several typical cases and the corresponding reliable solutions are given from the perspective of comprehensive score and retention index, chemical ionization identification molecular formula, fragment ion detail comparison for distinguishing isomers, and identification of alkanes. With this method, 69 volatile substances were identified in 60 masks. The identified substances were divided into nine categories. Alkanes, esters, benzenes, and alcohols were the top four groups of substances identified in masks and accounted for 34.8%, 15.9%, 10.1%, and 7.2% of the total substances, respectively. In addition, ketones, ethers, phenolics, amides, and other substances were identified. Ethanol, 1,4-dichlorobenzene, toluene, m-xylene, dimethyl glutarate, and N,N-dimethylacetamide had high detection rates. The identified substances were further filtered and screened according to their detection rate, toxicity, and response intensity. Finally, 12 high-risk volatile chemicals in medical masks were listed. This study could serve as a reference for identifying unknown substances and a guide for monitoring volatile chemicals in masks and promoting chemical safety improvements in products.

Linking plant-root exudate changes to micropollutant exposure in aquatic plants (Lemna minor and Salvinia natans). A prospective metabolomic study

Recent findings indicate that plant-root exudates can stimulate plant-associated microorganisms to enhance the biodegradation of contaminants in constructed wetlands. To understand this process, we studied the root-exudation changes of two aquatic plants (Lemna minor and Salvinia natans) upon micropollutants exposure (10, 100 and 1000 μg/L mixes containing naproxen, diclofenac, carbamazepine, and benzotriazole). After a 2-day exposure, plant exudates were collected, extracted and non-target analysis was performed with a gas chromatography-high resolution Orbitrap mass-spectrometer. Plants didn't show morphological or growth differences between the control and spiked reactors, but exudation changes were observed in both plants at all concentration levels. Partial least squares discriminant analysis showed that, for Lemna minor, the increase of micropollutants exposure was linked to the reduction of sugar and fatty acid exudation. This may trigger changes in the microbial community living on complex carbon forms. Instead, in Salvinia natans, micropollutants exposure was linked to the release of long-chain compounds such as cuticular waxes and sesquiterpenoids, which might be related to stress signaling. These results demonstrate that plant micropollutant-exposure at environmentally relevant concentration levels triggers changes in root exudates. This may help to design new strategies to enhance micropollutants degradation in nature based solutions such as in constructed wetlands.

Sample preparation techniques for suspect and non-target screening of emerging contaminants

The progress in sensitivity and resolution in mass spectrometers in recent years provides the possibility to detect a broad range of organic compounds in a single procedure. For this reason, suspect and non-target screening techniques are gaining attention since they enable the detection of hundreds of known and unknown emerging contaminants in various matrices of environmental, food and human sources. Sample preparation is a critical step before analysis as it can significantly affect selectivity, sensitivity and reproducibility. The lack of generic sample preparation protocols is obvious in this fast-growing analytical field, and most studies use those of traditional targeted analysis methods. Among them, solvent extraction and solid phase extraction (SPE) are widely used to extract emerging contaminants from solid and liquid sample types, respectively. Sequential solvent extraction and a combination of different SPE sorbents can cover a broad range of chemicals in the samples. Gel permeation chromatography (GPC) and adsorption chromatography, including acidification, are typically used to remove matrix components such as lipids from complex matrices, but usually at the expense of compound losses. Ideally, the purification of samples intended for non-target analysis should be selective of matrix interferences. Recent studies have suggested quality assurance/quality control measures for suspect and non-target screening, based on expansion and extrapolation of target compound lists, but method validations remain challenging in the absence of analytical standards and harmonized sample preparation approaches.

Targeted and Nontargeted Detection and Characterization of Trace Organic Chemicals in Human Serum and Plasma Using QuEChERS Extraction

Humans are exposed to a broad range of organic chemicals. Although targeted gas chromatography mass spectrometry techniques are used to quantify a limited number of persistent organic pollutants and trace organic contaminants in biological samples, nontargeted, high-resolution mass spectrometry (HRMS) methods assess the human exposome more extensively. We present a QuEChERS extraction for targeted and nontargeted analysis of trace organic contaminants using HRMS and compare this method to a traditional, cartridge-based solid-phase extraction (SPE). Following validation using reference and spiked serum samples, the method was applied to plasma samples (n = 75) from the Prospective investigation of Obesity, Energy, and Metabolism (POEM) study. We quantified 44 analytes using targeted analysis and 6247 peaks were detected using the nontargeted approach. Over 90% of targeted analytes were at least 90% recovered using the QuEChERS method in spiked serum samples. In nontargeted analysis, 84% of the peaks were above the method detection limit with area counts up to 3.0 × 105 times greater using the QuEChERS method. Of the targeted compounds, 88% were also identified in the nontargeted analysis. We categorized the 4212 chemicals assigned an identity in using EPA's CompTox Dashboard and 1076 chemicals were found in at least one list. The category with the highest number of chemicals was "androgen or estrogen receptor activity." The findings demonstrate that a QuEChERS technique is suitable for both targeted and nontargeted analysis of trace organic contaminants in biological samples.

Review of harmful chemical pollutants of environmental origin in honey and bee products

Honey is a natural food with many pro-health properties, which comprises a wide variety of valuable ingredients. It can also be the source of chemical contaminants of environmental origin, including POPs that can contribute to adverse health effects to human. Monitoring the degree of pollution of honey/bee products with hazardous chemicals is important from a nutraceutical point of view. In the present work, overview of recent literature data on chemical pollutants in honey/bee products originating from the environment was performed. Their MLs, MRLs and EDI were discussed. It can be concluded that huge amount of research concerned on the presence of TMs and pesticides in honey. Most of the studies have shown that honey/bee products sampled from urban and industrialized areas were more contaminated than these sampled from ecological and rural locations. More pollutants were usually detected in propolis and bee pollen than in honey. Based on their research and regulations, authors stated, that most of the toxic pollutants of environmental origin in honey/bee products are at levels that do not pose a threat to the health of the potential consumer. The greatest concern relates to pesticides and TMs, because in some research MLs in individual samples were highly exceeded.

Development and application of an in-house library and workflow for gas chromatography-electron ionization-accurate-mass/high-resolution mass spectrometry screening of environmental samples

This work presents an optimized gas chromatography–electron ionization–high-resolution mass spectrometry (GC-EI-HRMS) screening method. Different method parameters affecting data processing with the Agilent Unknowns Analysis SureMass deconvolution software were optimized in order to achieve the best compromise between false positives and false negatives. To this end, an accurate-mass library of 26 model compounds was created. Then, five replicates of mussel extracts were spiked with a mixture of these 26 compounds at two concentration levels (10 and 100 ng/g dry weight in mussel, 50 and 500 ng/mL in extract) and injected in the GC-EI-HRMS system. The results of these experiments showed that accurate mass tolerance and pure weight factor (combination of reverse-forward library search) are the most critical factors. The validation of the developed method afforded screening detection limits in the 2.5–5 ng range for passive sampler extracts and 1–2 ng/g for mussel sample extracts, and limits of quantification in the 0.6–3.2 ng and 0.1–1.8 ng/g range, for the same type of samples, respectively, for 17 model analytes. Once the method was optimized, an accurate-mass HRMS library, containing retention indexes, with ca. 355 spectra of derivatized and non-derivatized compounds was generated. This library (freely available at https://doi.org/10.5281/zenodo.5647960), together with a modified Agilent Pesticides Library of over 800 compounds, was applied to the screening of passive samplers, both of polydimethylsiloxane and polar chemical integrative samplers (POCIS), and mussel samples collected in Galicia (NW Spain), where a total of 75 chemicals could be identified.

Removing Disturbing Matrix Constituents from Biota Extracts from Total Extraction and Silicone-Based Passive Sampling

Contaminant analysis in biota extracts can be hampered by matrix interferences caused by, for example, co-extracted lipids that compromise the quality of the analytical data and require frequent maintenance of the analytical instruments. In the present study, using gas chromatography coupled to high resolution mass spectrometry (GC-HRMS), we aimed to develop and validate a straightforward, robust, and reproducible cleanup method with acceptable recoveries for diverse compound classes with a wide range of physicochemical properties representative of pollutant screening in biota extracts. We compared Oasis PRiME HLB cartridges, Agilent Captiva EMR-Lipid cartridges, and "Freeze-Out" with salmon lipids spiked with 113 target chemicals. The EMR-Lipid cartridges provided extracts with low matrix effects at reproducible recoveries of the multi-class target analytes (93 ± 9% and 95 ± 7% for low and high lipid amounts, respectively). The EMR-Lipid cartridges were further tested with spiked pork lipids submitted to total extraction or silicone-based passive sampling. Reproducible recoveries were achieved and matrix residuals were largely removed as demonstrated gravimetrically for both types of extracts. Ion suppression of halogenated compounds was not as efficiently removed by the cleanup of total and silicone-based extracts of pork lipids as for the salmon lipids. However, the samples with clean up provided better instrument robustness than those without cleanup. Hence, EMR-Lipid cartridges were shown to be efficient as a cleanup method in multi-class monitoring of biota samples and open up new possibilities as a suitable cleanup method for silicone extracts in biota passive sampling studies using GC-HRMS analysis. Environ Toxicol Chem 2021;40:2693-2704. © 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Non-targeted identification of unknown chemical hazardous substances in infant teether toys by gas chromatography-Orbitrap high resolution mass spectrometry

Chemical hazardous substances in teethers may migrate into infant's body through oral exposure, resulting in a potential health risk. In recent years, researchers have performed a series of studies for detecting target chemicals in teethers and other toys, but the presence of unknown chemicals has not been systematically investigated yet. This paper reports the non-targeted identification of unknown chemical hazards that may have migrated from teethers to infants based on gas chromatography-Orbitrap high resolution mass spectrometry. In view of the difficulties that may be encountered in the qualitative analysis of substances, several typical cases and the corresponding reliable solutions are given from the perspective of comprehensive score and retention index, isotope-aided qualitative analysis, chemical ionization identification formula, and fragment ion detail comparison for distinguishing isomers. Finally, 28 substances are identified in 10 teether samples. Among them, phenol, N-methylaniline, 1,6-dioxacyclododecane-7,12-dione and cyclohexanone have higher detection rates. This study not only has valuable reference for the identification of unknown substances, but also has positive guiding role in monitoring potential chemical hazards in toys and promoting the safety of products.

How and why beekeepers participate in the INSIGNIA citizen science honey bee environmental monitoring project

In the "contributory" citizen science project INSIGNIA, beekeepers carried out non-invasive sampling of their own honey bee colonies for an environmental investigation of pesticide residues and pollen plant origin. We surveyed several traits and attitudes of 69 of the volunteering beekeepers from ten countries. We found that their motivation was similar to that found in previous studies of environmental volunteer motivation, with helping the environment and contributing to scientific knowledge being strong motivators. Our results suggest that receiving laboratory analysis results of the samples from their colonies is the most meaningful way of appreciation for beekeepers, but is not their primary reason for participation. A citizen scientist beekeeper in this study spent on average 10.4 working hours on the project during a sampling season. Our study indicates that most of our volunteers would participate in similar future investigations, or would recommend participation to other beekeepers, underlining the potential of beekeepers as citizen scientists in honey bee research.

Advances in high resolution GC-MS technology: a focus on the application of GC-Orbitrap-MS in metabolomics and exposomics for FAIR practices

Gas chromatography-mass spectrometry (GC-MS) provides a complementary analytical platform for capturing volatiles, non-polar and (derivatized) polar metabolites and exposures from a diverse array of matrixes. High resolution (HR) GC-MS as a data generation platform can capture data on analytes that are usually not detectable/quantifiable in liquid chromatography mass-spectrometry-based solutions. With the rise of high-resolution accurate mass (HRAM) GC-MS systems such as GC-Orbitrap-MS in the last decade after the time-of-flight (ToF) renaissance, numerous applications have been found in the fields of metabolomics and exposomics. In a short span of time, a multitude of studies have used GC-Orbitrap-MS to generate exciting new high throughput data spanning from diverse basic to applied research areas. The GC-Orbitrap-MS has found application in both targeted and untargeted efforts for capturing metabolomes and exposomes across diverse studies. In this review, I capture and summarize all the reported studies to date, and provide a snapshot of the milieu of commercial and open-source software solutions, spectral libraries, and informatics solutions available to a GC-Orbitrap-MS system instrument user or a data analyst dealing with these datasets. Lastly, but importantly, I provide an account on data sharing and meta-data capturing solutions that are available to make HRAM GC-MS based metabolomics and exposomics studies findable, accessible, interoperable, and reproducible (FAIR). These FAIR practices would allow data generators and users of GC-HRMS instruments to help the community of GC-MS researchers to collaborate and co-develop exciting tools and algorithms in the future.

Screening of chemicals migrating from plastic food contact materials for oven and microwave applications by liquid and gas chromatography - Orbitrap mass spectrometry

Contamination of food with chemicals migrating from food contact materials (FCMs) is an important area of food safety. This study was aimed to investigate migration of chemicals from plastic FCMs used for microwave and conventional oven heating. Migration tests were conducted for samples of microwave trays, microwave oven bags, and oven bags. GC- and LC-Orbitrap mass spectrometry (MS) was used for non-targeted screening and identification of chemicals with mass error <5 ppm. A non-targeted identification approach was validated with isotopically labeled chemicals to establish acceptable criteria for identification of migrated compounds. A total of 74 migrated compounds were tentatively identified: 24 chemicals by GC-Orbitrap MS with electron ionization (EI), plus 35 and 19 by LC-Orbitrap MS electrospray ionization (ESI) with positive and negative polarities, respectively. Four migrated chemicals were identified by more than one instrumental analysis. Both intentionally added substances (IAS), i.e. additives used in the production of polymeric materials and plastics, and non-intentionally added substances (NIAS), i.e. derivatives and degradation/oxidation products of IAS, were identified among the migrated chemicals. The levels of 25 migrated chemicals were significantly different (p < 0.05) between microwave treatments and conventional oven treatments, where 20 migrants had higher levels for microwave compared with 5 for conventional oven treatments. For several identified chemicals, no previous reports on their migration from FCMs were found.

Optimized workflow for unknown screening using gas chromatography high-resolution mass spectrometry expands identification of contaminants in silicone personal passive samplers

RATIONALE

Silicone wristbands have emerged as valuable passive samplers for monitoring of personal exposure to environmental contaminants in the rapidly developing field of exposomics. Once deployed, silicone wristbands collect and hold a wealth of chemical information that can be interrogated using high-resolution mass spectrometry (HRMS) to provide a broad coverage of chemical mixtures.

METHODS

Gas chromatography coupled to Orbitrap™ mass spectrometry (GC/Orbitrap™ MS) was used to simultaneously perform suspect screening (using in-house database) and unknown screening (using vendor databases) of extracts from wristbands worn by volunteers. The goal of this study was to optimize a workflow that allows detection of low levels of priority pollutants, with high reliability. In this regard, a data processing workflow for GC/Orbitrap™ MS was developed using a mixture of 123 environmentally relevant standards consisting of pesticides, flame retardants, organophosphate esters, and polycyclic aromatic hydrocarbons as test compounds.

RESULTS

The optimized unknown screening workflow using a search index threshold of 750 resulted in positive identification of 70 analytes in validation samples, and a reduction in the number of false positives by over 50%. An average of 26 compounds with high confidence identification, 7 level 1 compounds and 19 level 2 compounds, were observed in worn wristbands. The data were further analyzed via suspect screening and retrospective suspect screening to identify an additional 36 compounds.

CONCLUSIONS

This study provides three important findings: (1) a clear evidence of the importance of sample cleanup in addressing complex sample matrices for unknown analysis, (2) a valuable workflow for the identification of unknown contaminants in silicone wristband samplers using electron ionization HRMS data, and (3) a novel application of GC/Orbitrap™ MS for the unknown analysis of organic contaminants that can be used in exposomics studies.

Comparison of new approach of GC-HRMS (Q-Orbitrap) to GC-MS/MS (triple-quadrupole) in analyzing the pesticide residues and contaminants in complex food matrices

Performances of multiresidue analysis of one hundred of pesticides and contaminants, using GC-Q-Orbitrap method in full scan mode were compared to those obtained with GC-triple-quadrupole method in multiple reaction monitoring mode. In terms of sensitivity, 86% of molecules exhibited lower limit of detection values using GC-Q-Orbitrap than using GC-triple-quadrupole. For the GC-Q-Orbitrap method, more than 85% of the pesticides and contaminants showed good recovery [70-120%] in wheat samples, with relative standard deviation values < 20%. GC-Q-Orbitrap method appeared the most sensitive for most pesticides studied in wheat with limit of quantification values ranged between 0.1 µg/kg and 4 µg/kg. Moreover, the matrix effect was acceptable in wheat extracts for 84 molecules but strong suppression of the chromatographic signal was observed for 16 molecules for the GC-Q-Orbitrap method. The injection of unpurified wheat extracts spiked at 10 µg/kg proved the potential of the GC-Q-Orbitrap method for use in performing high-throughput pesticide screening.

Route Determination of Sulfur Mustard Using Nontargeted Chemical Attribution Signature Screening

Route determination of sulfur mustard was accomplished through comprehensive nontargeted screening of chemical attribution signatures. Sulfur mustard samples prepared via 11 different synthetic routes were analyzed using gas chromatography/high-resolution mass spectrometry. A large number of compounds were detected, and multivariate data analysis of the mass spectrometric results enabled the discovery of route-specific signature profiles. The performance of two supervised machine learning algorithms for retrospective synthetic route attribution, orthogonal partial least squares discriminant analysis (OPLS-DA) and random forest (RF), were compared using external test sets. Complete classification accuracy was achieved for test set samples (2/2 and 9/9) by using classification models to resolve the one-step routes starting from ethylene and the thiodiglycol chlorination methods used in the two-step routes. Retrospective determination of initial thiodiglycol synthesis methods in sulfur mustard samples, following chlorination, was more difficult. Nevertheless, the large number of markers detected using the nontargeted methodology enabled correct assignment of 5/9 test set samples using OPLS-DA and 8/9 using RF. RF was also used to construct an 11-class model with a total classification accuracy of 10/11. The developed methods were further evaluated by classifying sulfur mustard spiked into soil and textile matrix samples. Due to matrix effects and the low spiking level (0.05% w/w), route determination was more challenging in these cases. Nevertheless, acceptable classification performance was achieved during external test set validation: chlorination methods were correctly classified for 12/18 and 11/15 in spiked soil and textile samples, respectively.

GC-HRMS with Complementary Ionization Techniques for Target and Non-target Screening for Chemical Exposure: Expanding the Insights of the Air Pollution Markers in Moscow Snow

Environmental exposure assessment is an important step in establishing a list of local priority pollutants and finding the sources of the threats for proposing appropriate protection measures. Exposome targeted and non-targeted analysis as well as suspect screening may be applied to reveal these pollutants. The non-targeted screening is a challenging task and requires the application of the most powerful analytical tools available, assuring wide analytical coverage, sensitivity, identification reliability, and quantitation. Moscow, Russia, is the largest and most rapidly growing European city. That rapid growth is causing changes in the environment which require periodic clarification of the real environmental situation regarding the presence of the classic pollutants and possible new contaminants. Gas chromatography - high resolution time-of-flight mass spectrometry (GC-HR-TOFMS) with electron ionization (EI), positive chemical ionization (PCI), and electron capture negative ionization (ECNI) ion sources were used for the analysis of Moscow snow samples collected in the early spring of 2018 in nine different locations. Collection of snow samples represents an efficient approach for the estimation of long-term air pollution, due to accumulation and preservation of environmental contaminants by snow during winter period. The high separation power of GC, complementary ionization methods, high mass accuracy, and wide mass range of TOFMS allowed for the identification of several hundred organic compounds belonging to the various classes of pollutants, exposure to which could represent a danger to the health of the population. Although quantitative analysis was not a primary aim of the study, targeted analysis revealed that some priority pollutants exceeded the established safe levels. Thus, dibutylphthalate concentration was over 10-fold higher than its safe level (0.001 mg/L), while benz[a]pyrene concentration exceeded Russian maximal permissible concentration value of 5 ng/L in three samples. The large amount of information generated during the combination of targeted and non-targeted analysis and screening samples for suspects makes it feasible to apply the big data analysis to observe the trends and tendencies in the pollution exposome across the city.

Using the US EPA CompTox Chemicals Dashboard to interpret targeted and non-targeted GC-MS analyses from human breath and other biological media

The U.S. EPA CompTox Chemicals Dashboard is a freely available web-based application providing access to chemistry, toxicity, and exposure data for ∼900 000 chemicals. Data, search functionality, and prediction models within the Dashboard can help identify chemicals found in environmental analyses and human biomonitoring. It was designed to deliver data generated to support computational toxicology to reduce chemical testing on animals and provide access to new approach methodologies including prediction models. The inclusion of mass and formula-based searches, together with relevant ranking approaches, allows for the identification and prioritization of exogenous (environmental) chemicals from high resolution mass spectrometry in need of further evaluation. The Dashboard includes chemicals that can be detected by liquid chromatography, gas chromatography-mass spectrometry (GC-MS) and direct-MS analyses, and chemical lists have been added that highlight breath-borne volatile and semi-volatile organic compounds. The Dashboard can be searched using various chemical identifiers (e.g. chemical synonyms, CASRN and InChIKeys), chemical formula, MS-ready formulae monoisotopic mass, consumer product categories and assays/genes associated with high-throughput screening data. An integrated search at a chemical level performs searches against PubMed to identify relevant published literature. This article describes specific procedures using the Dashboard as a first-stop tool for exploring both targeted and non-targeted results from GC-MS analyses of chemicals found in breath, exhaled breath condensate, and associated aerosols.

Impact of Varroa destructor and associated pathologies on the colony collapse disorder affecting honey bees

Varroa mite is the major threat to the western honey bee, Apis mellifera, and the cause of significant economic losses in the apiculture industry. Varroa destructor feeds on brood and adult bees being responsible for vectoring virus infections and other diseases. This study analyses the role of Varroa and other associated pathogens, such as viruses or the fungus Nosema ceranae, and their relationships regarding the viability of the bee colony. It has been carried out during one beekeeping season, with the subspecies A. m. iberiensis, commonly used in the apiculture industry of Spain. Our study shows a significant relationship between the presence of Varroa destructor and viral infection by deformed wing virus and acute bee paralysis virus. Nosema ceranae behaved as an opportunistic pathogen. In addition, this study explored a potential naturally occurring subset of peptides, responsible for the humoral immunity of the bees. The expression of the antimicrobial peptides abaecin and melittin showed a significant relationship with the levels of Varroa mite and the deformed wing virus.

Polycyclic aromatic compounds (PACs) in the Canadian environment: A review of sampling techniques, strategies and instrumentation

A wide variety of sampling techniques and strategies are needed to analyze polycyclic aromatic compounds (PACs) and interpret their distributions in various environmental media (i.e., air, water, snow, soils, sediments, peat and biological material). In this review, we provide a summary of commonly employed sampling methods and strategies, as well as a discussion of routine and innovative approaches used to quantify and characterize PACs in frequently targeted environmental samples, with specific examples and applications in Canadian investigations. The pros and cons of different analytical techniques, including gas chromatography - flame ionization detection (GC-FID), GC low-resolution mass spectrometry (GC-LRMS), high performance liquid chromatography (HPLC) with ultraviolet, fluorescence or MS detection, GC high-resolution MS (GC-HRMS) and compound-specific stable (δ¹³C, δ²H) and radiocarbon (Δ¹⁴C) isotope analysis are considered. Using as an example research carried out in Canada's Athabasca oil sands region (AOSR), where alkylated polycyclic aromatic hydrocarbons and sulfur-containing dibenzothiophenes are frequently targeted, the need to move beyond the standard list of sixteen EPA priority PAHs and for adoption of an AOSR bitumen PAC reference standard are highlighted.

Estimation of Dietary Exposure to Contaminants Transferred from the Packaging in Fatty Dry Foods Based on Cereals

Food packaging has received special attention from the food safety standpoint since it could be a potential source of contamination through the migration of chemical substances from the packaging material into food. The assessment of the exposure through the diet to these contaminants from food packaging is necessary. In this work, an estimation of dietary exposure of the young Spanish population (1–17 years) to target chemicals from packaging for fatty dried foods based on cereals was assessed. For this purpose, a gas chromatography coupled to mass spectrometry (GC–MS) method was developed for screening of volatile and semivolatile compounds, potential migrants from the packaging. Then, this technique was used to quantify 8 target analytes, which were previously identified in the packaging (including phthalates, acetyl tributyl citrate (ATBC), butylated hydroxytoluene (BHT) and octocrylene), in composite food samples of fatty cereals prepared according to the consumption data for different age groups. Among the phthalates, exposure to diethyl phthalate (DEP) was the highest for the three groups considered (0.0761–0.545 µg/kg body weight/day), followed by bis(2-ethylhxyl)phathalate (DEHP), while the lowest mean intake was found for di-n-octyl phathalate (DNOP; 0.00463–0.0209 µg/kg body weight/day). The estimated dietary exposures did not exceed for any of the analytes the corresponding established tolerable daily intakes.

Portable dehumidifiers condensed water: A novel matrix for the screening of semi-volatile compounds in indoor air

The comprehensive identification of organic species existing in indoor environments is a key issue to understand their impact in human health. This study proposes the analysis of condensed water samples, collected with portable dehumidifiers, to characterize semi-volatile compounds in the gas phase of confined areas. Water samples are concentrated by solid-phase extraction (SPE). The obtained extracts are analysed by gas chromatography (GC) time-of-flight mass spectrometry (TOF-MS), following a non-target screening data mining approach. In first term, spectra of deconvoluted compounds are compared with those in NIST low resolution library; thereafter, tentative identifications are verified using an in-house database of accurate electron ionization (EI) MS spectra. Chromatographic (retention index) and spectral data are combined for unambiguous species identification. The potential of condensed water samples to reflect changes in the composition of indoor atmospheres, the match between data obtained using different dehumidifiers, and the relative concentration efficiency of condensed water compared to that attained by active sampling of moderate air volumes are discussed. A total of 141 semi-volatile compounds were identified (98 confirmed against authentic standards) in a set of 21 samples obtained from different homes and working places. This list contains more than 40 fragrances (including several potential allergens), solvents and intermediates in the production of polymeric materials, plasticizers and flame retardants.