Non-targeted Screening Approach Research Articles

Feasibility of organic micropollutant removal from municipal wastewaters by algal treatment vs. activated sludge treatment: Comparison based on non-targeted organic compound analysis

Sustainability and life-cycle concerns about the conventional activated sludge (CAS) process for wastewater treatment have been driving the development of energy-efficient, greener alternatives. Feasibility of an algal-based wastewater treatment (A-WWT) system has been demonstrated recently as a possible alternative, capable of simultaneous nutrient and energy recovery. This study compared capabilities of the A-WWT and CAS systems in removing organic micropollutants (OMP). Initial assessments based on surrogate organic measures and fluorescence excitation-emission matrix (FEEM) scans revealed that the A-WWT system achieved higher removals of organics than the CAS system. However, effluents of both systems contained residual organic matter, necessitating further OMP assessment for a rigorous comparison. A novel ultrahigh-performance liquid chromatography- Fourier transform mass spectrometry (UPLC-FTMS)-based non-targeted screening approach was adopted here for residual OMP analysis. This approach confirmed that the A-WWT system resulted in better OMP removal, eliminating 329 compounds and partially reducing 472 compounds, compared to 206 eliminations and 410 partial reductions by the CAS system. Mass spectra signal corresponding to some OMPs increased with treatment while some transformation products were observed following treatment. Higher OMP reduction in the A-WWT system with concurrent reductions of biodegradable carbon, nutrients, and pathogens in a single-step while producing energy and nutrient rich algal biomass underscore its potential as a greener alternative for wastewater treatment.

Semi-volatile organic compounds in a museum in China: A non-targeted screening approach

Semi-volatile organic compounds in a museum in China: A non-targeted screening approach

Discovering transformation products of pharmaceuticals in domestic wastewaters and receiving rivers by using non-target screening and machine learning approaches

Wastewater treatment plants (WWTPs) are an important source of pharmaceuticals in surface water, but information about their transformation products (TPs) is very limited. Here, we investigated occurrence and transformation of pharmaceuticals and TPs in WWTPs and receiving rivers by using suspect and non-target analysis as well as target analysis. Results showed identification of 113 pharmaceuticals and 399 TPs, including mammalian metabolites (n = 100), environmental microbial degradation products (n = 250), photodegradation products (n = 44) and hydrolysis products (n = 5). The predominant parent pharmaceuticals (n = 37) and transformation products (n = 68) were mainly derived from antimicrobials, accounting for 32.7 % and 17.0 %, respectively. The identified compounds were found in the influent (387–428) and effluent (227–400) of WWTPs, as well as upstream (290–451) and downstream (322–416) of receiving rivers, most predominantly from antimicrobials, followed by analgesic and antipyretic drugs. A total of 399 identified TPs were transformed by 110 pathways, of which the oxidation reaction was predominant (27.0 %), followed by photodegradation reaction (10.7 %). Of the 399 TPs, 49 (with lower PNECs) were predicted to be more toxic than their parents. Compounds with potential high risks (hazard quotient >1 and risk index (RI) > 0.1) were found in the WWTP influent (126), effluent (53) and river (61), and the majority were from the antimicrobial and antihypertensive classes. In particular, the potential risks (RI) of TPs from roxithromycin and irbesartan were found higher than those for their corresponding parents. The findings from this study highlight the need to monitor TPs from pharmaceuticals in the environment.

In vitro biotransformation of 3-methylmethcathinone (3-MMC) through incubation with human liver microsomes and cytosol and application to in vivo samples

Synthetic cathinones are the second largest group of new psychoactive substances (NPS) monitored by the European Monitoring Centre for Drugs and Drug Addiction. Although 3-methylmethcathinone (3-MMC, C11H15NO) is legally banned in many countries, it is readily available for purchase online and on the street. Due to the scarcity of information regarding the pharmacokinetic and toxicological profile of 3-MMC, understanding its biotransformation pathways is crucial in determining its potential toxicity in humans and in the development of analytical methods for screening of human matrices. To gain more insight, Phase I and Phase II in vitro biotransformation of 3-MMC was investigated using human liver microsomes and human liver cytosol. Suspect and non-target screening approaches were employed to identify metabolites. To confirm in vitro results in an in vivo setting, human matrices (i.e., plasma, urine, saliva and hair) positive for 3-MMC (n=31) were screened. In total three biotransformation products were identified in vitro: C11H15NO2 (a hydroxylated derivate), C11H17NO (a keto-reduced derivate) and C10H13NO (an N-desmethyl derivate). All three were confirmed as human metabolites in respectively 16 %, 52 % and 42 % of the analysed human samples. In total, 61 % of the analysed samples were positive for at least one of the three metabolites. Interestingly, three urine samples were positive for all three metabolites. The presence of 3-MMC in saliva and hair indicates its potential applicability in specific settings, e.g., roadside testing or chronic consumption analysis. To our knowledge, C11H17NO was not detected before in vivo. Although some of these metabolites have been previously suggested in vitro or in a single post mortem case report, a wide in vivo confirmation including the screening of four different human matrices was performed for the first time. These metabolites could serve as potential human biomarkers to monitor human 3-MMC consumption effectively.

Non-target discovery and risk prediction of per- and polyfluoroalkyl substances (PFAS) and transformation products in wastewater treatment systems

Wastewater treatment plants (WWTPs) serve as the main destination of many wastes containing per- and polyfluoroalkyl substances (PFAS). Here, we investigated the occurrence and transformation of PFAS and their transformation products (TPs) in wastewater treatment systems using high-resolution mass spectrometry-based target, suspect, and non-target screening approaches. The results revealed the presence of 896 PFAS and TPs in aqueous and sludge phases, of which 687 were assigned confidence levels 1–3 (46 PFAS and 641 TPs). Cyp450 metabolism and environmental microbial degradation were found to be the primary metabolic transformation pathways for PFAS within WWTPs. An estimated 52.3 %, 89.5 %, and 13.6 % of TPs were believed to exhibit persistence, bioaccumulation, and toxicity effects, respectively, with a substantial number of TPs posing potential health risks. Notably, the length of the fluorinated carbon chain in PFAS and TPs was likely associated with increased hazard, primarily due to the influence of biodegradability. Ultimately, two high riskcompounds were identified in the effluent, including one PFAS (Perfluorobutane sulfonic acid) and one enzymatically metabolized TP (23-(Perfluorobutyl)tricosanoic acid@BTM0024_cyp450). It is noteworthy that the toxicity of some TPs exceeded that of their parent compounds. The results from this study underscores the importance of PFAS TPs and associated environmental risks.

Emission of volatile organic compounds during open fire cooking with wood biomass: Traditional three-stone open fire vs. gasifier cooking stove in rural Kenya

Cooking with wood biomass fuels releases hazardous air pollutants, including volatile organic compounds (VOCs), that often disproportionally affect women and children. This study, conducted in Kwale and Siaya counties in Kenya, employed thermal desorption gas chromatography – mass spectrometry to analyse VOC emissions from cooking with a wood biomass three-stone open fire vs. top-lit updraft gasifier stove. In kitchens with adequate ventilation, total VOC levels increased from 35–252 μg∙m−3 before cooking to 2235–5371 μg∙m−3 during open fire cooking, whereas use of a gasifier stove resulted in reduced emissions from cooking by 48–77 % (506–2778 μg∙m−3). However, in kitchens with poor ventilation, there was only a moderate difference in total VOC levels between the two methods of cooking (9034–9378 μg∙m−3 vs. 6727–8201 μg∙m−3 for the three-stone open fire vs. gasifier stove, respectively). Using a non-target screening approach revealed significantly increased levels of VOCs, particularly benzenoids, oxygenated and heterocyclic compounds, when cooking with the traditional open fire, especially in closed kitchens, highlighting the effects of poor ventilation. Key hazardous VOCs included benzene, naphthalene, phenols and furans, suggesting potential health risks from cooking. In kitchens with good ventilation, use of the gasifier stove markedly reduced emissions of these priority toxic VOCs compared to cooking with an open fire. Thus, substituting open fires with gasifier stoves could help to improve household air quality and alleviate health risks. The study revealed that VOCs were present prior to cooking, possibly originating from previously cooked food (buildup) or the outside environment. VOC emissions were also exacerbated by reduced air flow in high humidity during rainfall, suggesting an area for further research. The findings underscore the importance of adopting cleaner cooking technologies and enhancing kitchen ventilation to mitigate the impacts of VOCs in developing countries.

Identification and quantification of per- and polyfluorinated alkyl substances (PFAS) migrating from food contact materials (FCM)

Per- and polyfluorinated alkyl substances (PFAS) can be added to food contact materials (FCM) to increase their water and/or grease repellent properties. Some well-known PFAS are perfluoroalkyl carboxylic acids (PFCA), perfluoroalkyl sulfonic acids (PFSA), and polyfluorinated telomer alcohols (FTOH). Due to the strength of the carbon-fluorine bond, PFAS are chemically very stable and highly resistant to biological degradation, posing a risk to human health and the environment.To examine the presence of PFAS in paper-based FCM, various samples were collected, including popcorn bags, muffin cups, and pizza boxes with high total organic fluorine (TOF) content from the Danish and Spanish markets. The FCM composition was characterised by FTIR. Quantification of some well-known PFAS such as PFCA, PFSA, and FTOH was performed in food simulants using LC-MS/MS, and in addition a non-targeted screening approach was performed by LC-Orbitrap-HRMS.Among analysed samples, the highest concentrations of PFAS were found in a muffin cup made of cellulose (PFCA ∼ 1.41 μg kg−1 food, FTOH ∼ 11.5 μg kg−1 food), and the results were used to estimate dietary exposures to PFAS migrated from this FCM. Compared to measured TOF value in this sample, the fluorine from all quantified PFAS accounted for only 0.6%. Thus, a more powerful analytical approach was used to further investigate PFAS occurrence in this sample. Using non-targeted screening, an additional twenty compounds were identified, among them five with confidence level 1 and ten with confidence level 2. Many of them were either fluorotelomer carboxylic acids or sulfonic acids or ether-containing compounds.

Innovative non-targeted screening approach using High-resolution mass spectrometry for the screening of organic chemicals and identification of specific tracers of soil and dust exposure in children

Environmental contamination through direct contact, ingestion and inhalation are common routes of children’s exposure to chemicals, in which through indoor and outdoor activities associated with common hand-to-mouth, touching objects, and behavioral tendencies, children can be susceptible and vulnerable to organic contaminants in the environment. The objectives of this study were the screening and identification of a wide range of organic contaminants in indoor dust, soil, food, drinking water, and urine matrices (N = 439), prioritizing chemicals to assess children’s environmental exposure, and selection of unique tracers of soil and dust ingestion in young children by non-targeted analysis (NTA) using Q-Exactive Orbitrap followed data processing by the Compound Discoverer (v3.3, SP2). Chemical features were first prioritized based on their predominant abundance (peak area>500,000), detection frequency (in >50% of the samples), available information on their uses and potential toxicological effects. Specific tracers of soil and dust exposure in children were selected in this study including Tripropyl citrate and 4-Dodecylbenzenesulfonic acid. The criteria for selection of the tracers were based on their higher abundance, detection frequency, unique functional uses, measurable amounts in urine (suitable biomarker), and with information on gastrointestinal absorption, metabolism, and excretion, and were further confirmed by authentic standards. We are proposing for the first time suitable unique tracers for dust ingestion by children.

Nontargeted Volatile Metabolite Screening and Microbial Contamination Detection in Fermentation Processes by Headspace GC-IMS.

Gas chromatography combined with ion mobility spectrometry (GC-IMS) is a powerful separation and detection technique for volatile organic compounds (VOC). This combination is characterized by exceptionally low detection limits in the low ppbv range, high 2-dimensional selectivity, and robust operation. These qualities make it an ideal tool for nontarget screening approaches. Fermentation broths contain a substantial number of VOC, either from the medium or produced by microbial metabolism, that are currently not regularly measured for process monitoring. In this study, Escherichia coli, Saccharomyces cerevisiae, Levilactobacillus brevis, and Pseudomonas fluorescens were exemplarily used as model organisms and cultivated, and the headspace was analyzed by GC-IMS. Additionally, mixed cultures for every combination of two of the microorganisms were also characterized. Multivariate data analysis of the GC-IMS data revealed that it is possible to differentiate between the microorganisms using PLS-DA with a prediction accuracy of 0.92. The mixed cultures could be separated from the pure cultures with accuracies between 0.87 and 1.00 depending on the organism. GC-IMS data correlate with the optical density and can be used to follow and model growth curves. The root mean squared errors ranged between 10 and 20% of the maximum value, depending on the organism. Peak identification with reference compounds did not reveal specific marker compounds, rather the pattern was found to be responsible for the model performance.

Acesulfame degradation by thermally activated persulfate: Kinetics, transformation products and estimated toxicity

The existence of the artificial sweetener acesulfame (ACE) in quantities of significance can negatively impact water quality, and its consumption has been associated with deleterious health effects. The present investigation explores the efficacy of heat-activated sodium persulfate (SPS) for eliminating ACE. The complete degradation of 0.50 mg L−1 of ACE was achieved within 45 min under a reaction temperature of 50 °C and 100 mg L−1 of SPS. The impact of thermal decomposition on ACE at a temperature of 60 °C was negligible. This study considers several factors, such as the SPS and ACE loading, the reaction temperature, the initial pH, and the water matrix of the reactor. The results indicate that the method's efficiency is positively correlated with higher initial concentrations of SPS, whereas it is inversely associated with the initial concentration of ACE. Furthermore, higher reaction temperatures and acidic initial pH levels promote the degradation of acesulfame. At the same time, certain constituents of the water matrix, such as humic acid, chlorides, and bicarbonates, can hinder the degradation process. Additionally, the data from LC-QToF-MS analysis of the samples were used to investigate transformation through suspect and non-target screening approaches. Overall, ACE's eight transformation products (TPs) were detected, and a potential ACE decomposition pathway was proposed. The concentration of TPs followed a volcano curve, decreasing in long treatment times. The ecotoxicity of ACE and its identified TPs was predicted using the ECOSAR software. The majority of TPs exhibited not harmful values.

A targeted and non-targeted discovery screening approach for poly-and per-fluoroalkyl substances in model environmental biota samples

A comprehensive analytical approach for targeted and non-targeted discovery screening of per- and polyfluoroalkyl substances (PFAS) was developed and applied to model complex environmental biotic samples. Samples were extracted by formic acid-acetonitrile solution and cleaned up and fractionated by SPE (WAX). Target PFAS quantification was performed by ultra-high performance liquid chromatography interfaced with a triple quadrupole mass spectrometer (UPLC-QqQ-MS/MS). Non-targeted analysis (NTA) PFAS screening was performed with UPLC coupled with a quadrupole-Exactive orbitrap high resolution mass spectrometer (UPLC-Q-Exactive-HRMS). An iterative exclusion (IE) approach was applied to data acquisition for NTA suspect screening to increase the potential for unknown PFAS discovery with MS/MS. A complex workflow in Compound Discoverer was set up to automate data processing of the PFAS suspects search. New mass lists and MS/MS databases, which included a large number of PFAS, were set up and introduced into the search for high-throughput structure identification using HRMS techniques. The integrated targeted-NTA method successfully analyzed for legacy and alternative PFAS in model environmental biota samples, namely polar bear liver and bird egg samples. Targeted analysis provided unequivocal identification of well known/established PFAS (mainly perfluoroalkyl acids) with quantification at very low levels. The NTA suspect screening was able to determine a broader range of PFAS. The data analysis method offered high-confidence annotations for PFAS despite lacking available authentic standards. Overall, the analytical coverage of PFAS was greater and elucidated other PFAS present in these model apex predators.

Decoding the chemical clues: The role of advancements in forensic toxicology

Forensic toxicology, a crucial discipline in criminal investigations, has undergone significant advancements in recent years. This article delves into the realm of emerging techniques, analytical methods, and innovative applications that are revolutionizing the field. Advanced analytical techniques, such as high-resolution mass spectrometry, have enhanced the sensitivity and specificity of drug detection, enabling the identification of trace-level substances, including novel psychoactive substances (NPS). Emerging analytical methods, such as non-targeted screening approaches and biosensors, offer rapid and portable solutions for on-site drug detection. The article highlights the innovative applications of forensic toxicology, extending beyond traditional analyses. In postmortem toxicology, improved techniques aid in determining cause of death and assessing time of drug administration. In driving under the influence evaluation, roadside screening devices and pharmacodynamic models provide valuable insights into drug impairment. And in drug abuse monitoring and treatment, toxicological data informs public health interventions and treatment strategies. The article concludes by emphasizing the importance of continuous advancements in forensic toxicology to stay ahead of the growing complexity of toxicological challenges and address the ethical considerations surrounding advanced techniques. It underscores the significance of collaboration between forensic toxicologists, analytical chemists, pharmacologists, and clinicians to foster knowledge sharing and accelerate progress in this vital field.

PFΔScreen - an open-source tool for automated PFAS feature prioritization in non-target HRMS data.

Per- and polyfluoroalkyl substances (PFAS) are a huge group of anthropogenic chemicals with unique properties that are used in countless products and applications. Due to the high stability of their C-F bonds, PFAS or their transformation products (TPs) are persistent in the environment, leading to ubiquitous detection in various samples worldwide. Since PFAS are industrial chemicals, the availability of authentic PFAS reference standards is limited, making non-target screening (NTS) approaches based on high-resolution mass spectrometry (HRMS) necessary for a more comprehensive characterization. NTS usually is a time-consuming process, since only a small fraction of the detected chemicals can be identified. Therefore, efficient prioritization of relevant HRMS signals is one of the most crucial steps. We developed PFΔScreen, a Python-based open-source tool with a simple graphical user interface (GUI) to perform efficient feature prioritization using several PFAS-specific techniques such as the highly promising MD/C-m/C approach, Kendrick mass defect analysis, diagnostic fragments (MS2), fragment mass differences (MS2), and suspect screening. Feature detection from vendor-independent MS raw data (mzML, data-dependent acquisition) is performed via pyOpenMS (or custom feature lists) with subsequent calculations for prioritization and identification of PFAS in both HPLC- and GC-HRMS data. The PFΔScreen workflow is presented on four PFAS-contaminated agricultural soil samples from south-western Germany. Over 15 classes of PFAS (more than 80 single compounds with several isomers) could be identified, including four novel classes, potentially TPs of the precursors fluorotelomer mercapto alkyl phosphates (FTMAPs). PFΔScreen can be used within the Python environment and is easily automatically installable and executable on Windows. Its source code is freely available on GitHub ( https://github.com/JonZwe/PFAScreen ).

What is in the fish? Collaborative trial in suspect and non-target screening of organic micropollutants using LC- and GC-HRMS

A collaborative trial involving 16 participants from nine European countries was conducted within the NORMAN network in efforts to harmonise suspect and non-target screening of environmental contaminants in whole fish samples of bream (Abramis brama). Participants were provided with freeze-dried, homogenised fish samples from a contaminated and a reference site, extracts (spiked and non-spiked) and reference sample preparation protocols for liquid chromatography (LC) and gas chromatography (GC) coupled to high resolution mass spectrometry (HRMS). Participants extracted fish samples using their in-house sample preparation method and/or the protocol provided. Participants correctly identified 9–69 % of spiked compounds using LC-HRMS and 20–60 % of spiked compounds using GC-HRMS. From the contaminated site, suspect screening with participants’ own suspect lists led to putative identification of on average ∼145 and ∼20 unique features per participant using LC-HRMS and GC-HRMS, respectively, while non-target screening identified on average ∼42 and ∼56 unique features per participant using LC-HRMS and GC-HRMS, respectively. Within the same sub-group of sample preparation method, only a few features were identified by at least two participants in suspect screening (16 features using LC-HRMS, 0 features using GC-HRMS) and non-target screening (0 features using LC-HRMS, 2 features using GC-HRMS). The compounds identified had log octanol/water partition coefficient (KOW) values from −9.9 to 16 and mass-to-charge ratios (m/z) of 68 to 761 (LC-HRMS and GC-HRMS). A significant linear trend was found between log KOW and m/z for the GC-HRMS data. Overall, these findings indicate that differences in screening results are mainly due to the data analysis workflows used by different participants. Further work is needed to harmonise the results obtained when applying suspect and non-target screening approaches to environmental biota samples.

Exploring the efficacy of metabarcoding and non-target screening for detecting treated wastewater

Wastewater treatment processes can eliminate many pollutants, yet remainder pollutants contain organic compounds and microorganisms released into ecosystems. These remainder pollutants have the potential to adversely impact downstream ecosystem processes, but their presence is currently not being monitored. This study was set out with the aim of investigating the effectiveness and sensitivity of non-target screening of chemical compounds, 18S V9 rRNA gene, and full-length 16S rRNA gene metabarcoding techniques for detecting treated wastewater in receiving waters. We aimed at assessing the impact of introducing 33 % treated wastewater into a triplicated large-scale mesocosm setup during a 10-day exposure period. Discharge of treated wastewater significantly altered the chemical signature as well as the microeukaryotic and prokaryotic diversity of the mesocosms. Non-target screening, 18S V9 rRNA gene, and full-length 16S rRNA gene metabarcoding detected these changes with significant covariation of the detected pattern between methods.The 18S V9 rRNA gene metabarcoding exhibited superior sensitivity immediately following the introduction of treated wastewater and remained one of the top-performing methods throughout the study. Full-length 16S rRNA gene metabarcoding demonstrated sensitivity only in the initial hour, but became insignificant thereafter. The non-target screening approach was effective throughout the experiment and in contrast to the metabarcoding methods the signal to noise ratio remained similar during the experiment resulting in an increasing relative strength of this method. Based on our findings, we conclude that all methods employed for monitoring environmental disturbances from various sources are suitable. The distinguishing factor of these methods is their ability to detect unknown pollutants and organisms, which sets them apart from previously utilized approaches and allows for a more comprehensive perspective. Given their diverse strengths, particularly in terms of temporal resolution, these methods are best suited as complementary approaches.

Interlaboratory Study to Evaluate a Testing Protocol for the Safety of Food Packaging Coatings.

According to European regulations, migration from food packaging must be safe. However, currently, there is no consensus on how to evaluate its safety, especially for non-intentionally added substances (NIAS). The intensive and laborious approach, involving identification and then quantification of all migrating substances followed by a toxicological evaluation, is not practical or feasible. In alignment with the International Life Sciences Institute (ILSI) and the European Union (EU) guidelines on packaging materials, efforts are focused on combining data from analytics, bioassays and in silico toxicology approaches for the risk assessment of packaging materials. Advancement of non-targeted screening approaches using both analytical methods and in vitro bioassays is key. A protocol was developed for the chemical and biological screening of migrants from coated metal packaging materials. This protocol includes guidance on sample preparation, migrant simulation, chemical analysis using liquid chromatography (LC-MS) and validated bioassays covering endocrine activity, genotoxicity and metabolism-related targets. An inter-laboratory study was set-up to evaluate the consistency in biological activity and analytical results generated between three independent laboratories applying the developed protocol and guidance. Coated packaging metal panels were used in this case study. In general, the inter-laboratory chemical analysis and bioassay results displayed acceptable consistency between laboratories, but technical differences led to different data interpretations (e.g., cytotoxicity, cell passages, chemical analysis). The study observations with the greatest impact on the quality of the data and ultimately resulting in discrepancies in the results are given and suggestions for improvement of the protocol are made (e.g., sample preparation, chemical analysis approaches). Finally, there was agreement on the need for an aligned protocol to be utilized by qualified laboratories for chemical and biological analyses, following best practices and guidance for packaging safety assessment of intentionally added substances (IAS) and NIAS to avoid inconsistency in data and the final interpretation.

Suspect Screening of Chemicals in Hospital Wastewaters Using Effect-Directed Analysis Approach as Prioritization Strategy.

The increasing number of contaminants in the environment has pushed water monitoring programs to find out the most hazardous known and unknown chemicals in the environment. Sample treatment-simplification methods and non-target screening approaches can help researchers to not overlook potential chemicals present in complex aqueous samples. In this work, an effect-directed analysis (EDA) protocol using the sea urchin embryo test (SET) as a toxicological in vivo bioassay was used as simplified strategy to identify potential unknown chemicals present in a very complex aqueous matrix such as hospital effluent. The SET bioassay was used for the first time here to evaluate potential toxic fractions in hospital effluent, which were obtained after a two-step fractionation using C18 and aminopropyl chromatographic semi-preparative columns. The unknown compounds present in the toxic fractions were identified by means of liquid chromatography coupled to a Q Exactive Orbitrap high-resolution mass spectrometer (LC-HRMS) and using a suspect analysis approach. The results were complemented by gas chromatography-mass spectrometry analysis (GC-MS) in order to identify the widest range of chemical compounds present in the sample and the toxic fractions. Using EDA as sample treatment simplification method, the number of unknown chemicals (>446 features) detected in the raw sample was narrowed down to 94 potential toxic candidates identified in the significantly toxic fractions. Among them, the presence of 25 compounds was confirmed with available chemical standards including 14 pharmaceuticals, a personal care product, six pesticides and four industrial products. The observations found in this work emphasize the difficulties in identifying potential toxicity drivers in complex water samples, as in the case of hospital wastewater.

Degradation of Kresoxim-Methyl in Different Soils: Kinetics, Identification of Transformation Products, and Pathways Using High-Resolution-Mass-Spectrometry-Based Suspect and Non-Target Screening Approaches

This study investigated the degradation of strobilurin fungicide kresoxim-methyl (KM) in three typical agricultural soils from China by aerobic and anaerobic degradation experiments, focusing on degradation kinetics of KM, identification of transformation products (TPs), and prediction of toxicity end points via in silico approaches. KM showed a pronounced biphasic degradation in different soils and could rapidly degrade, with DT50 of <3 days. Four TPs were identified by high-resolution mass spectrometry (HRMS), and three of them have never been reported before. Possible degradation pathways of KM in soil were proposed, including hydrolysis, oxidation, and reduction, and the main mechanism involved in the biodegradation of KM was the hydrolysis of methyl ester regardless of aerobic or anaerobic conditions. The results of toxicity evaluation indicated that some TPs are more toxic than KM and may have a developmental toxicity and mutagenicity, and further risk assessment should be carried out.

Nontargeted Screening for the Verification of Allergenic Ingredients and Perfume Authenticity by GC-ecTOF-MS

Fraudulent products are ubiquitous in all markets. Besides the financial aspect, a major issue regarding products adulteration for society and the environment is the missing regulation and control of these goods. Therefore, harmful and toxic compounds in fraudulent products may become a risk for human health and the environment. Even small amounts of toxic substances can still have damaging effects. Thus, a sensitive and reliable identification of compounds is needed. Novel technologies are necessary to use identifying and preventing fraud and related risks. Goods from the food, flavor, and fragrance markets often contain volatile organic compounds (VOCs), which include most allergenic fragrances. For the detection and identification of these substances, gas chromatographic separation hyphenated with high resolution mass spectrometry (GC–HRMS) is an ideal instrumental technique. GC–simultaneous electron and chemical ionization (ec) time-of-flight (TOF)-MS generates various types of information via simultaneous ec–HRMS. Advantages are given for target, known unknown, and unknown unknown data analysis by generating various types of ions within one single experimental GC–MS run. In this study, the experimental nontargeted screening approach and corresponding data analysis workflows—simultaneously using molecular ion information and structural information—are presented for the molecular identification and authenticity verification process from a brand perfume using GC–ecTOF-MS.

Finding features - variable extraction strategies for dimensionality reduction and marker compounds identification in GC-IMS data

Gas chromatography hyphenated to ion mobility spectrometry (GC-IMS) is a powerful, two-dimensional separation and detection technique for volatile organic compounds (VOC). Low detection limits, high selectivity and robust operation characterize it as an ideal tool for non-target screening (NTS) approaches. Combined with multivariate data analysis, it has been successfully applied to several areas in food science, such as authenticity control and flavor profiling. The recorded raw data feature high numbers of variables due to the high scan speeds of the instrument. Additionally, NTS approaches - by design - record more data than required. Therefore, reducing the number of variables is a key step in any machine learning pipeline to reduce overfitting, overlong training times and model complexity. The aim of the study is a comparison between the two most used dimensionality reduction techniques, PCA and PLS, regarding interpretability, as a tool to find marker compounds, and performance as a preprocessing step for supervised learning. Both feature per variable visualizations, which allows easy interpretation of results and retains a connection to the input data, which can lead to the discovery of marker compounds. A GC-IMS dataset about the botanical origin of honey is used, and all formatting steps necessary to apply PCA and PLS to higher dimensional data and obtain intuitive figures are explained. To evaluate effectiveness as a preprocessing step in a supervised pipeline four supervised algorithms were fitted with PCA or PLS variable reduction. PLS proved to be a more effective step in a supervised workflow in terms of accuracy, while PCA is highly effective for revealing preprocessing weaknesses such as misalignments.