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Many chemicals in food packaging can leach as complex mixtures to food, potentially including substances hazardous to consumer health. Detecting and identifying all of the leachable chemicals are impractical with current analytical instrumentation and data processing methods. Therefore, our work aims to expand the analytical toolset for prioritizing and identifying chemical hazards in food packaging. We used a high-performance thin-layer chromatography (HPTLC)-based bioassay to detect genotoxic fractions in paperboard packaging. These fractions were then processed with non-targeted liquid chromatography high-resolution mass spectrometry (LC-HRMS/MS) and machine learning-based toxicity prediction (MLinvitroTox). The HPTLC bioassay detected four genotoxic zones in extracts of the paperboard. One-dimensional HPTLC separation and targeted fraction collection reduced the number of chemical features extracted from paperboard and detected with LC-HRMS by at least 98% (from 1695–2693 to 14–50). The entire process was successful for spiked genotoxic chemicals, which were correctly prioritized in the fractionation and non-target analysis workflow. The native chemical with the strongest genotoxicity signal was identified with a suspect list as 5-chloro-2-methyl-4-isothiazolin-3-one and confirmed with LC-HRMS/MS and HPTLC bioassay. Toward identification of the remaining unknown genotoxicants, two-dimensional HPTLC further reduced the number of chemical features. Genotoxicity predictions with MLinvitroTox based on molecular fingerprints of the unknown signals derived from their MS2 fragmentation spectra helped prioritize two chemical features and suggested candidate structures. This work demonstrates strategies for using HPTLC, HRMS, and toxicity prediction to help identify toxicants in food packaging. [ABSTRACT FROM AUTHOR]

A fire and explosion accident at a petrochemical complex sparked concerns over the rice health and production in nearby paddy fields. To unveil the potential effects, this study investigated small molecule changes in rice harvested in nearby counties using non-target analysis. Rice grains were harvested three, eight, 15, and 20 months after the accident from a total of ten townships. Small-molecule (m/z 70–1100) data in brown rice (n = 27) were acquired using high-resolution mass spectrometry (HRMS). Partial least squares discriminant analysis (PLS-DA) models were constructed to illustrate the temporal and spatial trends of rice's small-molecule fingerprints, and markers of production locations were identified. The small-molecule fingerprint in the rice directly exposed to the accident and harvested three months after the explosion differed significantly from those planted after the accident (PLS-DA model Q2 = 0.943, Q2/R2Y = 0.962), probably indicating the exclusion of long-term effects. Besides, in the rice directly exposed to the accident, the rice collected from near the explosion site (< 15 km) exhibited reduced jasmonic acid and increased imidacloprid levels (log2 fold change: -1.53 and 5.46, respectively), compared to that from farther locations. The result would suggest compromised disease defence in rice grown under the stress of explosion. In addition, lipid and amino acid metabolism perturbations are deemed relevant to plant development. [ABSTRACT FROM AUTHOR]

Chemicals enable the development of new technologies while also raising living standards and quality of life. Although chemicals are used in many aspects of daily life, such as the advance of innovative technologies and the improvement of living values, many of them are discharged into the aqueous environment which may lead to negative environmental health effects such as endocrine disorders, reduced reproductive rates, reduced life expectancy and insomnia. In this study, a high performance liquid chromatography connected to hybrid triple quadrupole ion trap mass spectrometer was used for qualitative non-target screening of emerging contaminants in water sources. The analytes were detected in five rivers, five dams, three wastewater treatment works and two drinking water treatment plants. The qualitative screening of emerging contaminants in these urban and natural water sources revealed 32 analytes under pharmaceutical and pesticide groups. From these groups, stimulants and herbicides were the most dominant. Among the analytes found in urban and natural waters of Mangaung District, three stimulants (ephedrine, nicotine, and metformin) and two herbicides (terbuthylazine, and sebuthylazine) were mostly detected. High number of these analytes (diphenhydramine, orphenadrine, cyclicine, paracetamol, sulfamethoxazol, metformin, bezafibrate, lamivudine, THC-COOH, methamphetamine, nicotine, ephedrine, theophylline, hordenine, sebuthylazine, atrazine, simazine, terbuthylazine, metolachlor, carbendazim, diazinon, and simazine) was observed in river samples and least in treated drinking water. Most notable was the detection of terbuthylazine in all samples collected in dams, effluent and treated drinking water. The ubiquitous presence of terbuthylazine in water sources may possibly lead to some environmental health risks. The findings of this study may be used for target analysis of these chemicals in future monitoring and risk assessment studies in the Free State region, where emerging contaminants research is limited. Furthermore, it may assist water managers and policymakers in assessing water quality and managing pollution more effectively. [ABSTRACT FROM AUTHOR]

Non-targeted analysis (NTA) was conducted to identify semi-volatile organic compounds (SVOCs) in a museum in China using the gas chromatography (GC)-Orbitrap-mass spectrometer (MS). Approximately 160 SVOCs were detected, of which 93 had not been reported in previous studies of museum environments. Many of the detected SVOCs were found to be associated with the chemical agents applied in conservation treatment and the materials used in furnishings. The results of hierarchical cluster analysis (HCA) indicated a spatial variation of SVOCs in the indoor air in the museum, but there were no obvious temporal differences of SVOCs observed in indoor dust. Spearman's correlation analysis showed that several classes of SVOCs were well correlated, suggesting their common sources. Fragrances and plasticizers were found to be the primary sources of SVOC pollution detected in the museum. Compared with compounds in outdoor air, indoor SVOCs had a lower level of unsaturation and more portions of chemically reduced compounds. This study is the first of its kind to comprehensively characterize SVOCs in a museum using an automated NTA approach with GC-Orbitrap-MS. The SVOCs identified in the current study are likely to be present in other similar museums; therefore, further examination of their potential impacts on cultural heritage artifacts, museum personnel, and visitors may be warranted. [ABSTRACT FROM AUTHOR]

The main techniques, approaches, methods, and information products used in recent years for the identification of chemical compounds are summarized. The methodology used in target analysis has largely remained unchanged; only the identification criteria have undergone some adjustments. The scope of research in non-target analysis has been significantly expanded. In this case, the main problems lie in revealing candidates for identification. These versions are tested against typical criteria of target analysis. Effective search for suitable candidate compounds has become possible with the apearance of modern high-resolution chromatography–mass spectrometers and progress in informatics. The latter includes the development of algorithms and programs for processing chromatographic and mass spectrometric data; comparing them with reference values; and predicting mass spectra, retention parameters, and other quantities. Chemical databases enable the assessment of the prevalence of chemical compounds and, correspondingly, their potential as candidates for identification. [ABSTRACT FROM AUTHOR]

Non-target analyses were conducted to characterize and compare the molecular profiles (UHPLC-HRMS fingerprint) of water samples from a wastewater treatment plant (WWTP). Inlet and outlet samples were collected from three campaigns spaced 6 months apart in order to highlight common trends. A significant impact of the treatment on the sample fingerprints was shown, with a 65–70% abatement of the number of features detected in the effluent, and more polar, smaller and less intense molecules found overall compared to those in WWTP influent waters. Multivariate analysis (PCA) associated with variations of the features between inlets and outlets showed that features appearing or increasing were correlated with effluents while those disappearing or decreasing were correlated with influents. Finally, effluent features considered as relevant to a potentially adverse effect on aqueous media (i.e. those which appeared or increased or slightly varied from the influent) were highlighted. Three hundred seventy-five features common with the 3 campaigns were thus selected and further characterized. For most of them, elementary composition was found to be C, H, N, O (42%) and C, H, N, O, P (18%). Considering the MS2 spectra and several reference MS2 databases, annotations were proposed for 35 of these relevant features. They include synthetic products, pharmaceuticals and metabolites. [ABSTRACT FROM AUTHOR]

Background: Non-target screening of surface water samples collected over an extended period can reveal interesting temporal patterns in exposome-related pollutants. Additionally, geographical data on pollution sources close to the sampling sites, chemical classification data and the consideration of flow paths can provide valuable information on the origins and potential threat of tentatively identified chemical compounds. In this study, 271 surface water samples from 20 sampling sites across Luxembourg were analysed using high-resolution mass spectrometry, complementing routine target monitoring efforts in 2019–2022. Data analysis was performed using the open source R-package patRoon, which offers a customizable non-target workflow. By employing open source workflows featuring scoring terms, like spectral match and applying identification levels, tentative identifications can be prioritized, e.g. based on spectral similarity. Furthermore, by utilizing supplementary database information such as PubChemLite annotation categories and classification software such as classyFire, an overall assessment of the potential threats posed by the tentatively identified chemicals was conducted, enabling the prioritization of chemicals for future confirmation through targeted approaches. Results: The study tentatively identified 378 compounds associated with the exposome including benzenoids, organoheterocyclic compounds, and organic phosphoric acids and derivatives (11 classyFire superclasses, 50 subclasses). The classification analysis not only revealed temporal variations in agrochemicals, with the majority of identifications occurring in May to July, but also highlighted the prevalence of pharmaceuticals such as venlafaxine in surface waters. Furthermore, potential sources of pollutants, like metallurgic industry or household products were explored by considering common uses and geographical information, as commercial uses of almost 100% of the identified chemicals are known. 41 chemicals were suggested for potential inclusion to governmental monitoring lists for further investigation. Conclusions: The findings of this study complement existing knowledge on the pollution status of surface water in Luxembourg and highlight the usefulness of non-target screening for identifying temporal and spatial trends in pollutant levels. This approach, performed in a complementary manner to routine monitoring, can help to tentatively identify chemicals of concern for potential inclusion in target monitoring methods following additional confirmation and quantification efforts. [ABSTRACT FROM AUTHOR]

Anatoxins (ATXs) are a potent class of cyanobacterial neurotoxins for which only a handful of structural analogues have been well characterized. Here, we report the development of an LC–HRMS/MS method for the comprehensive detection of ATXs. Application of this method to samples of benthic cyanobacterial mats and laboratory cultures showed detection of several new ATXs. Many of these result from nucleophilic addition to the olefinic bond of the α,β-unsaturated ketone functional group of anatoxin-a (ATX) and homoanatoxin-a (hATX), analogous to the conjugation chemistry of microcystins, which contain similar α,β-unsaturated amide functionality. Conjugates with glutathione, γ-glutamylcysteine, methanethiol, ammonia, methanol and water were detected, as well as putative C-10 alcohol derivatives. Structural confirmation was obtained by simple and selective analytical-scale semisynthetic reactions starting from available ATX standards. Methanol, water and ammonia conjugates were found to result primarily from sample preparation. Reduction products were found to result from enzymatic reactions occurring primarily after cell lysis in laboratory cultures of Kamptonema formosum and Cuspidothrix issatschenkoi. The relative contributions of the identified analogues to the anatoxin profiles in a set of 22 benthic-cyanobacterial-mat field samples were estimated, showing conjugates to account for up to 15% of total ATX peak area and 10-hydroxyanatoxins up to 38%. The developed methodology, new analogues and insight into the chemical and enzymatic reactivity of ATXs will enable a more comprehensive study of the class than possible previously. [ABSTRACT FROM AUTHOR]

Background: Per- and polyfluorinated alkyl substances (PFAS) have received increasing scientific and political attention in recent years. Several thousand commercially produced compounds are used in numerous products and technical processes. Due to their extreme persistence in the environment, humans and all other life forms are, therefore, increasingly exposed to these substances. In the following review, PFAS will be examined comprehensively. Results: The best studied PFAS are carboxylic and sulfonic acids with chain lengths of C4 to C14, particularly perfluorooctanoic acid (PFOA) and perfluorooctane sulfonic acid (PFOS). These substances are harmful to aquatic fauna, insects, and amphibians at concentrations of a few µg/L or less, accumulate in organisms, and biomagnify in food webs. Humans, as the final link in numerous food chains, are subjected to PFAS uptake primarily through food and drinking water. Several PFAS have multiple toxic effects, particularly affecting liver, kidney, thyroid, and the immune system. The latter effect is the basis for the establishment of a tolerable weekly dose of only 4.4 ng/kg body weight for the sum of the four representatives PFOA, PFOS, perfluorononanoic acid (PFNA) and perfluorohexane sulfonic acid (PFHxS) by the European Food Safety Authority (EFSA) in 2020. Exposure estimates and human biomonitoring show that this value is frequently reached, and in many cases exceeded. PFAS are a major challenge for analysis, especially of products and waste: single-substance analyses capture only a fragment of the large, diverse family of PFAS. As a consequence, sum parameters have gained increasing importance. The high mobility of per and polyfluorinated carboxylic and sulfonic acids makes soil and groundwater pollution at contaminated sites a problem. In general, short-chain PFAS are more mobile than long-chain ones. Processes for soil and groundwater purification and drinking water treatment are often ineffective and expensive. Recycling of PFAS-containing products such as paper and food packaging leads to carryover of the contaminants. Incineration requires high temperatures to completely destroy PFAS. After PFOA, PFOS and a few other perfluorinated carboxylic and sulfonic acids were regulated internationally, many manufacturers and users switched to other PFAS: short-chain representatives, per- and polyfluorinated oxo carboxylic acids, telomeric alcohols and acids. Analytical studies show an increase in environmental concentrations of these chemicals. Ultra-short PFAS (chain length C1–C3) have not been well studied. Among others, trifluoroacetic acid (TFA) is present globally in rapidly increasing concentrations. Conclusions: The substitution of individual PFAS recognized as hazardous by other possibly equally hazardous PFAS with virtually unknown chronic toxicity can, therefore, not be a solution. The only answer is a switch to fluorine-free alternatives for all applications in which PFAS are not essential. [ABSTRACT FROM AUTHOR]

Non-target analysis combined with liquid chromatography high resolution mass spectrometry is considered one of the most comprehensive strategies for the detection and identification of known and unknown chemicals in complex samples. However, many compounds remain unidentified due to data complexity and limited number structures in chemical databases. In this work, we have developed and validated a novel machine learning algorithm to predict the retention index (r i ) values for structurally (un)known chemicals based on their measured fragmentation pattern. The developed model, for the first time, enabled the predication of r i values without the need for the exact structure of the chemicals, with an R 2 of 0.91 and 0.77 and root mean squared error (RMSE) of 47 and 67 r i units for the NORMAN ( n = 3131 ) and amide ( n = 604 ) test sets, respectively. This fragment based model showed comparable accuracy in r i prediction compared to conventional descriptor-based models that rely on known chemical structure, which obtained an R 2 of 0.85 with an RMSE of 67. [ABSTRACT FROM AUTHOR]

An important task of physical chemistry is to predict the properties of chemical compounds from their structure. Prediction of the chromatographic retention allows one to reject false candidates in gas chromatography/mass spectrometry analysis and to elucidate structures of unknown compounds. Immediately after establishing the structure of an unknown analyte, the next task is to predict its properties, in particular, toxicity. In this work, the problem of prediction of gas chromatographic retention is considered in detail. A new method for predicting the retention indices on different stationary phases using regression learning is demonstrated in relation to flavors and fragrances. The achieved accuracy is higher than the accuracy of previously published methods. The median absolute error does not exceed 14 units. In addition, prediction of acute toxicity from the molecular structure is considered. The efficiency of various regression learning methods for predicting retention indices and acute toxicity (median lethal dose) of chemical compounds is compared. [ABSTRACT FROM AUTHOR]

The development of analytical methodologies to monitor different antibiotic families in water and the implementation of alternatives for their efficient elimination are a great challenge. The aim of this research was to develop a method based on solid-phase extraction followed by ultra-high performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry to analyse multi-class antibiotics, including macrolides, cephalosporins, fluoroquinolones, sulfonamides and diaminopyrimidines, in waters. Several parameters affecting the extraction such as the sample pH, type of sorbent and cartridge, elution volume and breakthrough volume were optimized. The method was validated in real samples, and matrix effect was assessed, demonstrating that the use of isotopically labelled surrogate compounds was mandatory to avoid standard addition calibration for each individual samples. Urban and hospital wastewater samples, as well as natural waters, were analysed, confirming the presence of 12 of the 14 target compounds at concentrations up to 3.5 µg L−1. Non-target analysis based on data-independent workflow was also performed, enabling the identification of 94 pollutants. Preliminary photodegradation experiments were also assessed, revealing the total removal of many target compounds after the first 5–10 min of UVC irradiation. In addition, 20 by-products formed after photolysis could be identified using a non-target approach. [ABSTRACT FROM AUTHOR]

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We review the main techniques, procedures, and information products used in non-target analysis (NTA) to reveal the composition of substances. Sampling and sample preparation methods are preferable that ensure the extraction of analytes from test samples in a wide range of analyte properties with the most negligible loss. The necessary techniques of analysis are versions of chromatography–high-resolution tandem mass spectrometry (HRMS), yielding individual characteristics of analytes (mass spectra, retention properties) to accurately identify them. The prioritization of the analytical strategy discards unnecessary measurements and thereby increases the performance of the NTA. Chemical databases, collections of reference mass spectra and retention characteristics, algorithms, and software for processing HRMS data are indispensable in NTA. [ABSTRACT FROM AUTHOR]

There is a rise in concern across the globe over the contaminants of emerging concerns (CECs) such as pharmaceuticals, personal care products (PCPs), UV stabilizers, surfactants, endocrine disrupting compounds (EDCs), etc. In the present study, we have identified some compounds belonging to the classes of pharmaceuticals, PCPs, and EDCs in the water samples collected from the coastal area of Ernakulam district of Kerala (India) (sea and lake). The analysis was carried out using ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-ToF–MS) after enrichment by solid-phase extraction. The nine CECs were identified in both positive and negative electrospray ionization mode (ESI). In both the matrices (sea and lake water), the highest concentration levels were noted for benzophenone (26.5–33.2 µg/l) and dibutyl phthalate (12.65–35.21 µg/l), whereas butyl and propyl parabens occurred at low concentration levels. The normality (Kolmogorov–Smirnov and Shapiro–Wilk) tests indicated that the concentration levels of contaminants among lake water samples were non-normally distributed. Whereas in seawater samples, the contaminant concentration levels were normally distributed. The analysis of homogeneity of variance and ANOVA test revealed no significant relationship between the contaminants detected from the lake and seawater samples. The risk assessment analysis showed that the organisms in the lake are at more risk compared to that of the sea. The results from the risk quotient (RQ) values obtained for each identified compound showed that the presence of dibutyl phthalate, butylparaben, and oxybenzone pose a medium risk to biological populations than other CECs. [ABSTRACT FROM AUTHOR]

Hydrolysis characteristics of a novel 3,4-dichloroisothiazole based fungicide with activating plant defense responses as a candidate plant-activator LY5-24-2 were investigated under different conditions (pH and temperature) using ultra-performance liquid chromatography (UPLC) and quadrupole Time-of-Flight (Q-TOF). The hydrolysis case complied with the first-order kinetic model, with half-lives ranging from 4.8 h to 3.2 days at pH 4, 7, 9 and temperature at 25 and 50℃. One of the hydrolysis metabolite 3,4-dichloroisothiazole-5-carboxylic acid (metabolite 1, M1) was determined and quantified using authentic standard. The other hydrolysate 3-chloro-5-(trifluoromethyl) pyridin-2-amine (metabolite 2, M2) was determined and identified according to accurate mass information, fragmentation patterns and principle component analysis (PCA). By utilizing high-resolution mass spectrometry and multivariate statistical analysis, hydrolysis dynamic of the metabolites was characterized and figured out. This research provided a non-target screening method to analyze hydrolysis metabolites of a new plant-activator and to find its degradation products in aqueous solution. [ABSTRACT FROM AUTHOR]

Background: Applying non-target analysis (NTA) in regulatory environmental monitoring remains challenging—instead of having exploratory questions, regulators usually already have specific questions related to environmental protection aims. Additionally, data analysis can seem overwhelming because of the large data volumes and many steps required. This work aimed to establish an open in silico workflow to identify environmental chemical unknowns via retrospective NTA within the scope of a pre-existing Swiss environmental monitoring campaign focusing on industrial chemicals. The research question addressed immediate regulatory priorities: identify pollutants with industrial point sources occurring at the highest intensities over two time points. Samples from 22 wastewater treatment plants obtained in 2018 and measured using liquid chromatography–high resolution mass spectrometry were retrospectively analysed by (i) performing peak-picking to identify masses of interest; (ii) prescreening and quality-controlling spectra, and (iii) tentatively identifying priority "known unknown" pollutants by leveraging environmentally relevant chemical information provided by Swiss, Swedish, EU-wide, and American regulators. This regulator-supplied information was incorporated into MetFrag, an in silico identification tool replete with "post-relaunch" features used here. This study's unique regulatory context posed challenges in data quality and volume that were directly addressed with the prescreening, quality control, and identification workflow developed. Results: One confirmed and 21 tentative identifications were achieved, suggesting the presence of compounds as diverse as manufacturing reagents, adhesives, pesticides, and pharmaceuticals in the samples. More importantly, an in-depth interpretation of the results in the context of environmental regulation and actionable next steps are discussed. The prescreening and quality control workflow is openly accessible within the R package Shinyscreen, and adaptable to any (retrospective) analysis requiring automated quality control of mass spectra and non-target identification, with potential applications in environmental and metabolomics analyses. Conclusions: NTA in regulatory monitoring is critical for environmental protection, but bottlenecks in data analysis and results interpretation remain. The prescreening and quality control workflow, and interpretation work performed here are crucial steps towards scaling up NTA for environmental monitoring. [ABSTRACT FROM AUTHOR]

Mass spectrometry based non-target analysis is increasingly adopted in environmental sciences to screen and identify numerous chemicals simultaneously in highly complex samples. However, current data processing software either lack functionality for environmental sciences, solve only part of the workflow, are not openly available and/or are restricted in input data formats. In this paper we present patRoon, a new R based open-source software platform, which provides comprehensive, fully tailored and straightforward non-target analysis workflows. This platform makes the use, evaluation and mixing of well-tested algorithms seamless by harmonizing various common (primarily open) software tools under a consistent interface. In addition, patRoon offers various functionality and strategies to simplify and perform automated processing of complex (environmental) data effectively. patRoon implements several effective optimization strategies to significantly reduce computational times. The ability of patRoon to perform time-efficient and automated non-target data annotation of environmental samples is demonstrated with a simple and reproducible workflow using open-access data of spiked samples from a drinking water treatment plant study. In addition, the ability to easily use, combine and evaluate different algorithms was demonstrated for three commonly used feature finding algorithms. This article, combined with already published works, demonstrate that patRoon helps make comprehensive (environmental) non-target analysis readily accessible to a wider community of researchers. [ABSTRACT FROM AUTHOR]

Artificial insemination is common practice in mass livestock farming. Recently, it was shown that chemicals leaching from multilayer plastic bags affect the fertility of boars, although common quality tests did not show any impact on the sperm. It is not clear whether this incidence was a single case or whether it could be a systematic problem. Therefore, we studied six multilayer plastic bags. A total of 49 compounds were found, but most of them were at very low intensity. Nonylphenols in the range of 19-99 μg/g plastic were found. Migration tests using water and 10% ethanol as simulants, to mimic the behavior of semen with the extender, were performed. The most interesting migrants in terms of potential reprotoxicity were identified as nonylphenols. The identification in depth demonstrated the presence of 10 isomers of nonylphenol with a total concentration range between 16 to 58 μg/Kg simulant, among other migrants at lower concentration. The influence of these nonylphenols and their maximum tolerable concentration in direct contact with semen from boars was studied. Motility, viability, mitochondrial activity and acrosomes reacted were significantly affected at 10 mg/Kg of nonylphenols in contact with the sperm, but in vitro penetration rate was significantly decreased with only 2 mg/Kg. Insight into the mode of action is also provided. [ABSTRACT FROM AUTHOR]

Certain persistent and polar substances may pose a hazard to drinking water resources. To foster the knowledge exchange in this field the Working Group Environmental Monitoring of the German Chemical Society (GDCh) Division Environmental Chemistry and Ecotoxicology discussed at their meeting in December 2018 the significance and relevance of persistent, mobile and toxic chemicals (PMT substances) in the environment. Five oral contributions highlighted not only various aspects such as the identification of potential PMT substances based on certain properties and their possible regulation under the European REACH regulation, but also current developments in the analysis of PMT substances and results from environmental monitoring. The data presented prove that many persistent and mobile substances can be detected in surface waters. Once detected, it can be complex and costly to identify sources and reduce inputs, as a case study on 1,4-dioxane in Bavarian surface waters shows. The same applies to the removal of polar substances from raw water for drinking water production. Today, scientific advances in analytical methods make it easier to identify and quantify even very polar substances in water samples. In addition to the targeted analysis of critical chemicals, non-target screening is playing an increasingly important role. This opens up the possibility of detecting substances in water samples that have not previously been investigated in routine monitoring and testing their relevance for humans and the environment. However, the list of potentially occurring PM substances that have not yet been investigated is still very long. Further methodological improvements seem necessary here. In view of the evidence for the presence of PMT substances in the environment (e.g., trifluoroacetic acid and 1,4-dioxane) and the potential risks for drinking water abstraction, it seems important under consideration of the precautionary principle to identify and prioritise relevant REACH-registered substances. The assessment should be based on the intrinsic properties and the emission potential of the compounds. The implementation of a detailed proposal made at European level to regulate PMT and very persistent and very mobile (vPvM) substances in the context of REACH would ensure that chemicals identified as being substances of very high concern according to the PMT and vPvM criteria are subject to authorisation in future. [ABSTRACT FROM AUTHOR]

Comprehensive two-dimensional (2D) gas chromatography (GC×GC) coupled to mass spectrometry (MS, GC×GC-MS), which enhances selectivity compared to GC-MS analysis, can be used for non-directed analysis (non-target screening) of environmental samples. Additional tools that aid in identifying unknown compounds are needed to handle the large amount of data generated. These tools include retention indices for characterizing relative retention of compounds and prediction of such. In this study, two quantitative structure-retention relationship (QSRR) approaches for prediction of retention times (1tR and 2tR) and indices (linear retention indices (LRIs) and a new polyethylene glycol-based retention index (PEG-2I)) in GC × GC were explored, and their predictive power compared. In the first method, molecular descriptors combined with partial least squares (PLS) analysis were used to predict times and indices. In the second method, the commercial software package ChromGenius (ACD/Labs), based on a “federation of local models,” was employed. Overall, the PLS approach exhibited better accuracy than the ChromGenius approach. Although average errors for the LRI prediction via ChromGenius were slightly lower, PLS was superior in all other cases. The average deviations between the predicted and the experimental value were 5% and 3% for the 1tR and LRI, and 5% and 12% for the 2tR and PEG-2I, respectively. These results are comparable to or better than those reported in previous studies. Finally, the developed model was successfully applied to an independent dataset and led to the discovery of 12 wrongly assigned compounds. The results of the present work represent the first-ever prediction of the PEG-2I.ᅟ [ABSTRACT FROM AUTHOR]

Thousands of organohalogen compounds, including hazardous chemicals such as polychlorinated biphenyls (PCBs) and other persistent organic pollutants (POPs), were selectively and simultaneously detected and identified with simple, or no, purification from environmental sample extracts by using several advanced methods. The methods used were software extraction from two-dimensional gas chromatography-high-resolution time-of-flight mass spectrometry (GC × GC-HRTofMS) data, measurement by negative chemical ionization with HRTofMS, and neutral loss scanning (NLS) with GC × GC-MS/MS. Global and selective detection of organochlorines and bromines in environmental samples such as sediments and fly ash was achieved by NLS using GC × GC-MS/MS (QQQ), with the expected losses of 35Cl and 79Br. We confirmed that negative chemical ionization was effective for sensitive and selective ionization of organohalogens, even using GC × GC-HRTofMS. The 2D total ion chromatograms obtained by using negative chemical ionization and selective extraction of organohalogens using original software from data measured by electron impact ionization were very similar; the software thus functioned well to extract organohalogens. Combining measurements made by using these different methods will help to detect organohalogens selectively and globally. However, to compare the data obtained by individual measurements, the retention times of the peaks on the 2D chromatograms need to match. [ABSTRACT FROM AUTHOR]

A strategy for non-target analysis of samples with unknown composition by capillary electrophoresis (CE) with ultraviolet (UV) detection is suggested. The strategy is based on the preliminary identification of analytes and further optimization of the conditions for their separation using the developed computational tool set ElphoSeparation. It is shown that, in order to record electrophoretic peaks with the mobilities from the maximum to minimum possible values, the positive and negative voltage polarity and hydrodynamic pressure should be used. To choose the optimal separation conditions, dynamic maps of electrophoretic separation (DMES) are suggested. DMES is a bar chart with theoretical resolutions of adjacent peaks presented in ascending order of the migration time. The resolution is calculated as the division of the difference of the effective electrophoretic mobilities of adjacent analytes by their average peak width in terms of electrophoretic mobility. The suggested strategy is tested by the example of the analysis of herbal medicine (Holosas) on the basis of rose hips. The approach should be used to analyze samples with not very complex composition, such as environmental water and precipitation samples, process liquors, some vegetable extracts, biological fluids, food, and other samples for the determination of widespread compounds capable of forming ionic species. For samples with complex composition, the approach used together with other techniques may produce advantageous information due to specificity of the method, particularly it can be useful for determination of compounds suffering from low volatility or thermal stability, and for analysis of samples with difficult matrices. [ABSTRACT FROM AUTHOR]

Contamination of water resources is one of the major problems to be faced for environment preservation and sustainability. The monitoring of target compounds based on mass spectrometry and selected reaction monitoring mode is often insufficient to definitely assess the quality of surface water. Also potentially harmful non-target pollutants simultaneously present must be taken into account. Liquid chromatography coupled with tandem mass spectrometry is suitable to obtain complete information on water composition. Hybrid mass spectrometers such as triple quadrupole/linear ion trap, hybrid quadrupole/time-of-flight and linear ion trap/orbitrap analyzers should be used. Here, we review ultra-high performance liquid chromatography coupled with mass spectrometry methods developed for post-target and non-target screening analysis of water emerging contaminants, such as pesticides and their degradation products, pharmaceuticals and drug side-reaction products, surfactants and illicit drugs. The major points are the following: (1) the possibility of performing retrospective analysis only by high-resolution mass analyzer; (2) the compatibility of mass analyzer with ultra-high performance liquid chromatography; (3) the use of deconvolution software to detect unknowns; and (4) the limited availability of library database. [ABSTRACT FROM AUTHOR]

Decomposition odour analysis involves the chemical profiling of volatile organic compounds produced by decomposing remains. This is important for areas of forensic science that rely on the detection of decomposition odour such as insect attraction to carrion, positive alerts of cadaver dogs to decomposing remains, and the development of field instrumentation for search and recovery procedures. Traditionally decomposition odour analysis has been performed using gas chromatography-quadrupole mass spectrometry (GC-qMS); however, the use of comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC×GC-TOFMS) is rapidly becoming more prevalent. The objective of this study was to compare GC-qMS and GC×GC-TOFMS for decomposition odour profiling based on inter-year replicate field studies using decomposing porcine remains. The increased peak capacity, sensitivity and selectivity afforded by GC×GC-TOFMS allowed peak co-elutions, chromatographic artefacts, and dynamic range to be more easily addressed and managed. Furthermore, the software associated with GC×GC-TOFMS provided several additional benefits including improved peak alignment between samples and increased consistency of reported results, overall allowing for additional statistical tests to be applied following data processing. Future GC-qMS results could be improved by implementing some of these software-associated procedures, potentially reducing the magnitude of variation observed between GC-qMS and GC×GC-TOFMS studies. One-dimensional GC analysis may also benefit substantially from coupling with TOFMS detection to provide an indirect increase in peak capacity using deconvolution. However, the wealth of information gained by using GC×GC-TOFMS in decomposition odour profiling is undoubtedly an asset in this field of research. [ABSTRACT FROM AUTHOR]

Mass spectrometry (MS)-based toxicometabolomics requires analytical approaches for obtaining unbiased metabolic profiles. The present work explores the general application of direct infusion MS using a high mass resolution analyzer (a hybrid systems triple quadrupole-time-of-flight) and a complementary gas chromatography-MS analysis to mitochondria extracts from mouse hepatic cells, emphasizing on mitochondria isolation from hepatic cells with a commercial kit, sample treatment after cell lysis, comprehensive metabolomic analysis and pattern recognition from metabolic profiles. Finally, the metabolomic platform was successfully checked on a case-study based on the exposure experiment of mice Mus musculus to inorganic arsenic during 12 days. Endogenous metabolites alterations were recognized by partial least squares-discriminant analysis. Subsequently, metabolites were identified by combining MS/MS analysis and metabolomics databases. This work reports for the first time the effects of As-exposure on hepatic mitochondria metabolic pathways based on MS, and reveals disturbances in Krebs cycle, β-oxidation pathway, amino acids degradation and perturbations in creatine levels. This non-target analysis provides extensive metabolic information from mitochondrial organelle, which could be applied to toxicology, pharmacology and clinical studies. Graphical Abstract: [Figure not available: see fulltext.] [ABSTRACT FROM AUTHOR]

Groundwater samples collected downgradient from a former municipal solid waste landfill near Berlin, Germany, were analyzed by GC-MS, HPLC-MS, and HPLC-NMR hyphenated techniques to comprehensively characterize the xenobiotic organic compounds (XOCs). The focus thereby was on the detection and identification of the polar XOCs which were analyzed in the extract obtained after separation of the unpolar components by pre-extraction. HPLC-NMR and HPLC-MS runs were used to identify polar XOCs on-line or to obtain preliminary structure information on the other XOCs. These compounds were then isolated by HPLC fractionation and their structures elucidated by off-line NMR and MS investigations. A variety of polar XOCs, products of the dye industry, degradation products of polyethylene glycol, and some heterocyclic compounds could be identified. Furthermore, a semi-quantitative estimation of the identified polar compounds is given. [Figure not available: see fulltext.] [ABSTRACT FROM AUTHOR]

In this work, a systematic comprehensive screening procedure has been proposed for the detection of multiclass flavonoid derivatives by liquid chromatography high-resolution mass spectrometry (LC-HRMS). The procedure is based on the combined use of accurate mass measurements and in-source fragmentation obtained with a liquid chromatography time-of-flight mass spectrometry instrument. The method relies on automated screening of selected diagnostic ions based on an exact mass database. The included diagnostic ions represent theoretical combinations of aglycones and typical glycan part constituents of flavonoid derivatives (i.e., various saccharide units and acyl moieties). The proposed identification protocol is following a systematic evaluation of the obtained positive hits from the diagnostic ions database according to a 'bottom-up' approach that is thoroughly discussed. The main benefit of the proposed bottom-up protocol resides in the fact that untargeted flavonoid derivatives can be detected and tentatively identified without the need for any preliminary knowledge on the sought compound. In addition to information on the nature of the (1) aglycone and the (2) glycan part, further indication of (3) sugar unit distribution and information on (4) the type of the glycosidic bonds can also be attained. Selected examples of plant extracts demonstrate the potential of the proposed LC-HRMS approach for the systematic screening of flavonoids. A broad variety of compounds were tentatively identified including both anthocyanins and non-anthocyanin flavonoids having various glycan moieties such as mono-, di-, and triglycosides with varying distributions and linkage types of carbohydrate moieties ( O-glycosides, C-glycosides, O,C-glycosides). [ABSTRACT FROM AUTHOR]

Non-intentionally added substances (NIASs) are usually detected by acquiring mass spectra in full scan mode and then identifying the compounds corresponding to the unexpected peaks. High-resolution mass spectrometry detectors are frequently used, but this does not solve the problem that an NIAS can contribute to the abundance at m/z ratios that correspond to the fragmentation of other molecules. This problem leads to false negatives when identifying compounds, even in target analysis when the maximum permitted tolerances for relative ion abundances (SANCO/10684/2009) are taken into account. In this work, the introduction of different volumes of a test sample onto a GC/MS system that has a programmed temperature vaporizer inlet and is operating in full scan mode provides a data tensor. The proposed approach consists of considering the structure of the matrix of abundances of K m/z ratios acquired at J elution times for each chromatographic peak. Upon concatenating I of such matrices, a three-way tensor X is obtained, which is then decomposed using parallel factor analysis into as many factors as there are substances coeluting, thus providing the mass spectrum and the chromatographic profile for each of them. If the amount of an analyte changes significantly during the I injections, then it can be unequivocally identified. This procedure thus identifies coeluting NIASs, provides information about their mass spectra, and guarantees the identification and quantification of target compounds. In this work, it is used to determine five triazines in the presence of NIASs which match some of the m/z ratios of the triazines and coelute with them. Decision limits (CC α) of between 7.5 and 25.0 μg L were obtained. [Figure not available: see fulltext.] [ABSTRACT FROM AUTHOR]

Challenging tasks, increasing demands, and new generations of powerful analytical instruments initiated considerable progress in aquatic environmental analysis and led to a considerable improvement of analytical performance during the last few years. The ever growing number of emerging pollutants is tackled by specific and highly sensitive analytical methods with detection limits of a few nanogram per liter and even lower. Wide-scope monitoring techniques and multiclass and multiresidue analysis allow for the simultaneous determination of hundreds of compounds. The high mass resolution capability and mass accuracy of advanced mass spectrometric instruments, i.e., time-of-flight (TOF) MS or Fourier transform (FT)-Orbitrap MS, enable combined target and non-target analysis, including the identification of metabolites and abiotic degradation products. This minireview highlights some of the most recent developments in the trace analysis of important organic water pollutants and focuses on some specific groups of emerging contaminants, i.e., pharmaceuticals, flame retardants, disinfection by-products, surfactants, per- and polyfluorinated compounds, benzotriazoles, and benzothiazoles, as well as on the identification of transformation products and on non-target analysis. References were selected according to their exemplary and innovative character and to their practical relevance. [ABSTRACT FROM AUTHOR]

Effect-directed analysis has been applied to a river sediment sample of concern to identify the compounds responsible for the observed effects in an in vitro (anti-)androgenicity assay. For identification after non-target analysis performed on a high-resolution LTQ-Orbitrap, we developed a de novo identification strategy including physico-chemical parameters derived from the effect-directed analysis approach. With this identification strategy, we were able to handle the immense amount of data produced by non-target accurate mass analysis. The effect-directed analysis approach, together with the identification strategy, led to the successful identification of eight androgen-disrupting compounds belonging to very diverse compound classes: an oxygenated polyaromatic hydrocarbon, organophosphates, musks, and steroids. This is one of the first studies in the field of environmental analysis dealing with the difficult task of handling the large amount of data produced from non-target analysis. The combination of bioassay activity assessment, accurate mass measurement, and the identification and confirmation strategy is a promising approach for future identification of environmental key toxicants that are not included as priority pollutants in monitoring programs. [ABSTRACT FROM AUTHOR]

Aquatic system contamination is a subject of concern due to the high number of contaminants with the potential to be hazardous for plant and animal species, including humans. A large number of analytical methods have been developed to evaluate the extension of water resource pollution, most of them focused on target residue analysis. Screening methods for potential target and non-target compounds are a potential alternative and could be used for a comprehensive evaluation of samples composition. Liquid chromatography coupled to time of flight mass spectrometry (LC-qTOF-MS/MS) was developed to provide full-spectrum data and high mass resolution with appropriate selectivity and sensitivity for monitoring of 300 pharmaceuticals and pesticides in environmental water samples. The validation was based on anti-doping analysis validation protocols, using three different concentration levels (0.01, 0.1, and 1.0 μg L−1). Confirmation analysis was achieved using two fragment ions monitoring for each analyte. Samples were extracted by solid-phase extraction and analyzed by LC-qTOF-MS/MS. The final method was able to detect 170 chemicals in wastewater treatment plant effluent and 198 chemicals in surface water. The advantage of using post-acquisition data processing provided by a qTOF-MS/MS system allowed for non-target analysis for an illicit drug metabolite determination. The method was successfully applied to real samples of wastewater and surface water. [ABSTRACT FROM AUTHOR]