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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]

Abstract 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.

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]

This study compares the PM10 (particulate matter of diameter smaller than 10 μm) organic aerosol composition between urban and suburban stations in Heraklion, Crete, during winter 2024 in order to highlight the impact of local anthropogenic activities on urban atmospheric particulate matter pollution. Using an HPLC-ESI-MS Orbitrap analyzer (High Performance Liquid Chromatography-Electrospray Ionization-Mass Spectrometry) in full MS scan mode at a resolution of 140,000, 48 daily aerosol filter extracts were analyzed in both positive and negative modes, resulting in the detection of 2809 and 3823 features, respectively. Features with at least five times higher intensity in the urban environment compared to the suburban, and p < 0.05, were deemed significant. A correlation with black carbon (r > 0.6) was observed for 71% of significant urban features in positive mode. These features showed a predominance of low O:C ratios (<0.2) and the majority were classified as intermediate volatility organic compounds (IVOCs), indicating fresh primary emissions. A clear urban–suburban distinction was shown by PCA of positive mode features, unlike the negative mode features. Regarding the total intensity of the features, urban samples were on average 55% higher than suburban samples in positive mode and 39% higher in negative mode. This study reveals the molecular profile of locally emitted combustion related organics observed in positive mode in an urban environment. [ABSTRACT FROM AUTHOR]

Cotton is used for the production of textiles, hygiene and cosmetic materials. During cultivation and technological processes, various types of substances (surfactants, softeners, lubricants, etc.) penetrate cotton, which can have a harmful effect on both the human body and the environment. The aim of this study was to analyze selected cotton products in order to identify the substances contained and to describe the potential possibilities of inducing textile contact dermatitis (CD). The impact of the identified compounds on the aquatic environment was also taken into account. Nine samples of cotton clothing and seven samples of cotton pads from various manufacturers were tested. Samples after extraction using the FUSLE (Focused Ultrasonic Liquid Extraction) technique were analyzed with GC/MS. Qualitative analysis was based on comparing mass spectra with library spectra using the following mass spectra deconvolution programs: MassHunter (Agilent), AMDIS (NIST), and PARADISE (University of Copenhagen). The parameter confirming the identification of the substance was the retention index. Through the non-target screening process, a total of 36 substances were identified, with an average AMDIS match factor of approximately 900 ("excellent match"). Analyzing the properties of the identified compounds, it can be concluded that most of them have potential properties that can cause CD, also due to the relatively high content in samples. This applies primarily to long-chain alkanes (C25–C31), saturated fatty acids, fatty alcohols (e.g., oleyl alcohol), and fatty acid amides (e.g., oleamide). However, there are not many reports describing cases of cotton CD. Information on the identified groups of compounds may be helpful in the case of unexplained sources of sensitization when the skin comes into contact with cotton materials. Some of the identified compounds are also classified as dangerous for aquatic organisms, especially if they can be released during laundering. [ABSTRACT FROM AUTHOR]

Wine quality and safety is affected by the food contact materials (FCMs) used. These materials are expected to protect the beverage from any chemical, physical, or biological hazard and preserve its composition stable throughout its shelf-life. However, the migration of chemical substances from FCMs is a known phenomenon and requires monitoring. This review distinguishes the migrating chemical substances to those of (i) industrial origin with potential safety effects and those of (ii) natural occurrence, principally in cork (ex. tannins) with organoleptic quality effects. The review focuses on the migration of industrial chemical contaminants. Migration testing has been applied only for cork stoppers and tops, while other materials like polyethylene terephthalate (PET) bottles with aluminum cups, paperboard cartons, stainless steel vats, and oak casks have been examined for the presence of chemical migrating substances only by wine analysis without migration testing. The dominant analytical techniques applied are gas and liquid chromatography coupled to mass spectrometry (MS) for the determination of organic compounds and Inductively Coupled Plasma Atomic Emission Spectroscopy (ICP-AES) and ICP-MS for elemental analysis. Targeted approaches are mostly applied, while limited non-target methodologies are reported. The identified migrating substances include authorized substances like phthalate plasticizers, monomers (bisphenol A), antioxidants (Irganox 1010), known but non-authorized substances (butylparaben), break-down products, oxidation products (nonylphenol), polyurethane adhesive by-products, oligomers, ink photoinitiators, and inorganic elements. A preliminary investigation of microplastics' migration has also been reported. It is proposed that further research on the development of comprehensive workflows of target, suspect, and non-target analysis is required to shed more light on the chemical world of migration for the implementation of an efficient risk assessment and management of wine contact materials. [ABSTRACT FROM AUTHOR]

The forensic investigation of hazardous noxious substances (HNS) is paramount for an effective response to chemical spill emergencies and other accidents. Analyzing unknown emergency samples poses a challenge due to the limited availability of background information, making the selection of appropriate sample preparation and analytical methodologies difficult. The utilization of high-resolution mass spectrometers (HRMS) in screening both target and non-target substances proves instrumental in revealing hazardous substances that may be overlooked alongside the intended analytes. In this study, a gas chromatography-quadruple time-of-flight mass spectrometer (GC-QTOF-MS) was employed to identify numerous organic compounds in an indoor dust sample. The compounds detected encompassed normal alkanes, fatty acids (saturated and unsaturated), alcohols, phenols, sterols, drugs, polycyclic aromatic hydrocarbons (PAHs), pesticides, flame retardants (such as polybrominated biphenyl ethers, PBDEs), plasticizers (such as phthalates and phosphates), among others. Notably, concentrations of n-alkanes, fatty acids, and phthalates were relatively high, while PAHs and pesticides were present at trace levels. The application of GC-QTOF-MS provides a swift and confirmative approach for analyzing target, suspect, and non-target compounds in both routine and emergency scenarios. This methodology proves invaluable in enhancing our capability to comprehensively assess and address chemical incidents, ensuring a more thorough and accurate response.

The safety of drinking water is a significant environmental issue of great concern for human health since numerous contaminants are often detected in drinking water and its sources. Boiling is a common household method used to produce relatively high-quality drinking water in some countries and regions. In this study, with the aid of an integrated approach of in vitro bioassays and non-target analysis based on high-resolution mass spectrometry coupled with liquid chromatography, alterations in endocrine-disrupting activities in tap water samples without and with boiling were revealed, as well as the potential endocrine-disrupting chemicals (EDCs) contributing to these alterations were identified. The organic extracts of tap water had no significant (ant)agonistic activities against an estrogen receptor (ER), progesterone receptor (PR), glucocorticoid receptor (GR), and mineralocorticoid receptor (MR) at enrichment concentrations of ≤10 times, posing no immediate or acute health risk to humans. However, the presence of agonistic activities against PR and MR and antagonistic activities against ER, PR, GR, and MR in OEs of tap water at relatively higher enrichment concentrations still raise potential health concerns. Boiling effectively reduced antagonistic activities against these steroid hormone receptors (SHRs) but increased estrogenic and glucocorticoid activities in drinking water. Four novel potential EDCs, including one UV filter (phenylbenzimidazole sulfonic acid, PBSA) and three natural metabolites of organisms (beta-hydroxymyristic acid, 12-hydroxyoctadecanoic acid, and isorosmanol) were identified in drinking water samples, each of which showed (ant)agonistic activities against different SHRs. Given the widespread use of UV filters in sunscreens to prevent skin cancer, the health risks posed by PBSA as an identified novel EDC are of concern. Although boiling has been thought to reduce the health risk of drinking water contamination, our findings suggest that boiling may have a more complex effect on the endocrine-disrupting activities of drinking water and, therefore, a more comprehensive assessment is needed. [ABSTRACT FROM AUTHOR]

Abstract 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.

Introduction: Population growth and increasing water demand have exacerbated water resource scarcity. Treated wastewater (TWW) is a valuable alternative resource, but its complex composition, including micropollutants, raises concerns about reuse risks. Reactive barriers (RB) made with natural materials offer a solution to remove TWW contaminants. Evaluating RB process effectiveness and comprehending contaminant fate remain challenging. Recent advances in High-Resolution Mass Spectrometry (HRMS) and non-target analysis (NTA) provide an opportunity to identify contaminants and evaluate RB processes. The study aims to develop an NTA approach to assess RB effectiveness and understand the NTA contribution for broadening perspectives on the impact of reactive barrier treatment.Methods: In a serie of batch experiments, TWW was mixed with a RB under two conditions: TWW in contact with RB (TWW+RB) and TWW alone (TWW). After 1 h of contact, samples were extracted and analyzed using HPLC-HRMS. NTA workflow and statistical comparison between the two sample conditions were applied for data treatment. Additionally, a quantitative method was applied to 28 pharmaceutical residues. Sorption (%) was calculated by comparing concentrations in TWW+RB and TWW experiments. NTA’s applicability for sorption estimation was investigated using intensities from differential analysis.Results: Differential analysis shows significant differences in compounds that decrease or increase after contact with BR. A prioritization workflow identified and annotated 115 compounds. Natural products predominantly increased after RB contact, while compounds exhibited a significant 75% decrease in peak area are mainly pharmaceuticals. Notably, 61% of these molecules were sorbed at more than 50%. The sorption of emerging contaminants (ECs) estimated by NTA correlated satisfactorily with sorption quantified through target analysis, although caution regarding the matrix effect is necessary.Discussion: NTA provides a comprehensive view of RB treatment performance, giving information on the compounds released by the barrier and its sorption capacity. NTA emphasizes the benefits of RB treatment while highlighting the need to study compounds reloaded by RB. It is a powerful tool for understanding the advantages of nature-based reactive barrier treatment in improving the quality of TWW.

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]

Wine quality and safety is affected by the food contact materials (FCMs) used. These materials are expected to protect the beverage from any chemical, physical, or biological hazard and preserve its composition stable throughout its shelf-life. However, the migration of chemical substances from FCMs is a known phenomenon and requires monitoring. This review distinguishes the migrating chemical substances to those of (i) industrial origin with potential safety effects and those of (ii) natural occurrence, principally in cork (ex. tannins) with organoleptic quality effects. The review focuses on the migration of industrial chemical contaminants. Migration testing has been applied only for cork stoppers and tops, while other materials like polyethylene terephthalate (PET) bottles with aluminum cups, paperboard cartons, stainless steel vats, and oak casks have been examined for the presence of chemical migrating substances only by wine analysis without migration testing. The dominant analytical techniques applied are gas and liquid chromatography coupled to mass spectrometry (MS) for the determination of organic compounds and Inductively Coupled Plasma Atomic Emission Spectroscopy (ICP-AES) and ICP-MS for elemental analysis. Targeted approaches are mostly applied, while limited non-target methodologies are reported. The identified migrating substances include authorized substances like phthalate plasticizers, monomers (bisphenol A), antioxidants (Irganox 1010), known but non-authorized substances (butylparaben), break-down products, oxidation products (nonylphenol), polyurethane adhesive by-products, oligomers, ink photoinitiators, and inorganic elements. A preliminary investigation of microplastics’ migration has also been reported. It is proposed that further research on the development of comprehensive workflows of target, suspect, and non-target analysis is required to shed more light on the chemical world of migration for the implementation of an efficient risk assessment and management of wine contact materials.

The contamination characteristics, migration patterns and health risks of per- and polyfluoroalkyl substances (PFAS) were investigated in 66 Chinese paper products by using target and non-target screening methods. Among 57 target PFASs, 5 and 6 PFASs were found in the hygiene paper products (

Water-soluble organic molecules (WSOMs) in inhaled PM2.5 can readily translocate from the lungs into the blood circulation, facilitating their distribution to and health effects on distant organs and tissues in the human body. Human serum albumin (HSA), the most abundant protein carrier in the blood, readily binds exogenous substances to form non-covalent adducts and subsequently transports them throughout the circulatory system, thereby indicating their internal exposure. The direct internal exposure of WSOMs in PM2.5 needs to be understood. In this study, the non-covalent HSA-WSOM adductome was developed as a dosimeter to evaluate the internal exposure potential of WSOMs in urban PM2.5. The WSOM composition was acquired from non-target high-resolution mass spectrometry analysis coupled with multiple ionizations. The binding level of HSA-WSOM non-covalent adducts was obtained from surface plasma resonance. Machine learning combined WSOM composition and the binding level of HSA-WSOM non-covalent adducts to screen bindable (also internalizable) WSOMs. The concentration of WSOM ranged from 4 to 13 μg/m3 during our observation period. Of the 17,513 mass spectral features detected, 9,484 contributed to the non-covalent adductome and possessed the internal exposure potential. 102 major contributors accounted for 90.6 % of the HSA-WSOM binding level. The fraction of internalizable WSOMs in PM2.5 varied from 11.9 % to 61.3 %, averaging 26.2 %. WSOMs that have internal exposure potential were primarily lignin-like and lipid-like substances. The HSA-WSOMs non-covalent adductome represents direct internal exposure potential, which can provide crucial insights into the molecular diagnosis of PM2.5 exposure and precise assessments of PM2.5 health effects.

Brown carbon (BrC) absorption impacts radiative forcing and climate change. Quantifying radiative forcing of BrC requires understanding its molecular composition and absorption characteristics. While organic molecules surrounding BrC may impact its absorption, their effects have not yet been investigated. This research determined matrix effect on BrC absorption by comparing individual BrC molecules and BrC within an organic matrix. Over 20,000 water‐soluble organic molecules constituted the water‐soluble BrC and associated organic matrix. The matrix enhanced aliphatic BrC absorption but suppressed aromatic BrC, especially with higher matrix O/C ratios indicating greater polarity and acidity. By directly measuring and modeling organic matrix effect on BrC, we can improve climate prediction precision and aerosol‐radiation interaction comprehension. Plain Language Summary: In the atmosphere, organic carbon that absorb light are called brown carbon. Brown carbon can impact climate change. It is critical to understand potential factors affecting brown carbon's absorption of light. Our study proposed another potential influencing light absorbing of brown carbon, effect from organic matrix formed by co‐existing organic molecules. The matrix effect on brown carbon absorption was simulated by the absorption properties of individual molecules and the absorption contributions from the same molecules embedded within organic matrix. We found over 20,000 molecules in all samples, separating them into major contributing brown carbon molecules and co‐existing organic molecules. We found CHO and CHON formed the majority of these molecules. The organic matrix showed the different behavior to effect light absorption to different portion for organic molecules, namely aliphatic and aromatic brown carbon molecules. The brown carbon absorption was suppressed during the nighttime, with the high O/C ratio co‐existing organics. Through the direct measurement and modeling of organic matrix effect on brown carbon, the finding could improve the precision of climate predictions and enhance our comprehension of aerosol‐radiation interactions. Key Points: Organic molecules co‐existing around brown carbon constituted the organic matrixThe organic matrix enhanced aliphatic but suppressed aromatic brown carbon absorptionHigher matrix O/C ratios indicating greater polarity and acidity especially suppressed aromatic brown carbon absorption [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]

Abstract 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 $$_i$$ 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 $$_i$$ i values without the need for the exact structure of the chemicals, with an $$R^2$$ R 2 of 0.91 and 0.77 and root mean squared error (RMSE) of 47 and 67 r $$_i$$ i units for the NORMAN ( $$n=3131$$ n = 3131 ) and amide ( $$n=604$$ n = 604 ) test sets, respectively. This fragment based model showed comparable accuracy in r $$_i$$ i prediction compared to conventional descriptor-based models that rely on known chemical structure, which obtained an $$R^2$$ R 2 of 0.85 with an RMSE of 67.

Widespread use of spray-type consumer products can raise significant concerns regarding their effects on indoor air quality and human health. In this study, we conducted non-target screening using gas chromatography-mass spectrometry (GC-MS) to analyze VOCs in 48 different spray-type consumer products. Using this approach, we tentatively identified a total of 254 VOCs from the spray-type products. Notably, more VOCs were detected in propellant-type products which are mostly solvent-based than in trigger-type ones which are mostly water-based. The VOCs identified encompass various chemical classes including alkanes, cycloalkanes, monoterpenoids, carboxylic acid derivatives, and carbonyl compounds, some of which arouse concerns due to their potential health effects. Alkanes and cycloalkanes are frequently detected in propellant-type products, whereas perfumed monoterpenoids are ubiquitous across all product categories. Among the identified VOCs, 12 compounds were classified into high-risk groups according to detection frequency and signal-to-noise (S/N) ratio, and their concentrations were confirmed using reference standards. Among the identified VOCs, D-limonene was the most frequently detected compound (freq. 21/48), with the highest concentration of 1.80 mg/g. The risk assessment was performed to evaluate the potential health risks associated with exposure to these VOCs. The non-carcinogenic and carcinogenic risks associated with the assessed VOC compounds were relatively low. However, it is important not to overlook the risk faced by occupational exposure to these VOCs, and the risk from simultaneous exposure to various VOCs contained in the products. This study serves as a valuable resource for the identification of unknown compounds in the consumer products, facilitating the evaluation of potential health risks to consumers.

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]

Of the different quality parameters of any food commodity or beverage, color is the most important, attractive and choice-affecting sensory factor to consumers and customers. Nowadays, food industries are interested in making the appearance of their food products attractive and interesting in order to appeal to consumers/customers. Natural green colorants have been accepted universally due to their natural appeal as well as their nontoxic nature to consumers. In addition, several food safety issues mean that natural green colorants are preferable to synthetic food colorants, which are mostly unsafe to the consumers but are less costly, more stable, and create more attractive color hues in food processing. Natural colorants are prone to degradation into numerous fragments during food processing, and thereafter, in storage. Although different hyphenated techniques (especially high-performance liquid chromatography (HPLC), LC-MS/HRMS, and LC/MS-MS are extensively used to characterize all these degradants and fragments, some of them are not responsive to any of these techniques, and some substituents in the tetrapyrrole skeleton are insensitive to these characterization tools. Such circumstances warrant an alternative tool to characterize them accurately for risk assessment and legislation purposes. This review summarizes the different degradants of chlorophylls and chlorophyllins under different conditions, their separation and identification using various hyphenated techniques, national legislation regarding them, and the challenges involved in their analysis. Finally, this review proposes that a non-targeted analysis method that combines HPLC and HR-MS assisted by powerful software tools and a large database could be an effective tool to analyze all possible chlorophyll and chlorophyllin-based colorants and degradants in food products in the future. [ABSTRACT FROM AUTHOR]

Unsymmetrical dimethylhydrazine (UDMH) is a widely used rocket propellant. Entering the environment or being stored in uncontrolled conditions, UDMH easily forms an enormous variety (at least many dozens) of transformation products. Environmental pollution by UDMH and its transformation products is a major problem in many countries and across the Arctic region. Unfortunately, previous works often use only electron ionization mass spectrometry with a library search, or they consider only the molecular formula to propose the structures of new products. This is quite an unreliable approach. It was demonstrated that a newly proposed artificial intelligence-based workflow allows for the proposal of structures of UDMH transformation products with a greater degree of certainty. The presented free and open-source software with a convenient graphical user interface facilitates the non-target analysis of industrial samples. It has bundled machine learning models for the prediction of retention indices and mass spectra. A critical analysis of whether a combination of several methods of chromatography and mass spectrometry allows us to elucidate the structure of an unknown UDMH transformation product was provided. It was demonstrated that the use of gas chromatographic retention indices for two stationary phases (polar and non-polar) allows for the rejection of false candidates in many cases when only one retention index is not enough. The structures of five previously unknown UDMH transformation products were proposed, and four previously proposed structures were refined. [ABSTRACT FROM AUTHOR]

The safety of drinking water is a significant environmental issue of great concern for human health since numerous contaminants are often detected in drinking water and its sources. Boiling is a common household method used to produce relatively high-quality drinking water in some countries and regions. In this study, with the aid of an integrated approach of in vitro bioassays and non-target analysis based on high-resolution mass spectrometry coupled with liquid chromatography, alterations in endocrine-disrupting activities in tap water samples without and with boiling were revealed, as well as the potential endocrine-disrupting chemicals (EDCs) contributing to these alterations were identified. The organic extracts of tap water had no significant (ant)agonistic activities against an estrogen receptor (ER), progesterone receptor (PR), glucocorticoid receptor (GR), and mineralocorticoid receptor (MR) at enrichment concentrations of ≤10 times, posing no immediate or acute health risk to humans. However, the presence of agonistic activities against PR and MR and antagonistic activities against ER, PR, GR, and MR in OEs of tap water at relatively higher enrichment concentrations still raise potential health concerns. Boiling effectively reduced antagonistic activities against these steroid hormone receptors (SHRs) but increased estrogenic and glucocorticoid activities in drinking water. Four novel potential EDCs, including one UV filter (phenylbenzimidazole sulfonic acid, PBSA) and three natural metabolites of organisms (beta-hydroxymyristic acid, 12-hydroxyoctadecanoic acid, and isorosmanol) were identified in drinking water samples, each of which showed (ant)agonistic activities against different SHRs. Given the widespread use of UV filters in sunscreens to prevent skin cancer, the health risks posed by PBSA as an identified novel EDC are of concern. Although boiling has been thought to reduce the health risk of drinking water contamination, our findings suggest that boiling may have a more complex effect on the endocrine-disrupting activities of drinking water and, therefore, a more comprehensive assessment is needed.

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]

This study utilized liquid chromatography (LC) alongside Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR MS) to explore the dyes and chemical contaminants in Loji River, Indonesia. We tentatively identified a total of 655 contaminants at various confidence level, subsequently classifying them into 22 distinct categories. Of the 54 dyes we detected, 12 corresponded with entries in our specialized in-house database. These 12 dyes were further confirmed by reference standards, matching both retention time (RT) and MS/MS spectra. LC-FT-ICR MS data showed that dyes from printing batik and textile industries are key contributors to river pollution. Particularly noteworthy were two sample locations that displayed substantial contamination, predominantly from azoic and reactive dyes. Additionally, pharmaceuticals were identified as one of the most frequently occurring contaminants, underscoring the inadequacies in the area's sewage management. To corroborate these findings, we conducted physicochemical, phytotoxicity, and acute toxicity tests, all of which verified the harmful effects of the Loji River's water on both the local flora and human populations. Notably, water samples that tested positive for dye contamination exhibited elevated toxicity levels. To the best of our knowledge, this study is pioneering in its molecular-level investigation of dye contamination in Southeast Asian rivers. Our results accentuate the pressing need for both targeted and non-targeted screening methods to identify contaminants in the surface waters of developing nations. [Display omitted] • Screening of dyes and potential contaminants in the Loji River with LC-FT-ICR MS. • A total of 655 contaminants were tentatively identified and classified into 22 categories. • Out of 54 dyes, with 12 of them matching entries in an in-house dye database. • Batik textile industries were major contributors to the river's dye pollution. • Toxicity tests confirmed the detrimental effects of Loji River surface water. [ABSTRACT FROM AUTHOR]

Various industries produce a myriad of synthetic molecules used to satisfy our needs, but all these molecules are likely to reach aquatic environments. The number of organic contaminants found in rivers and lakes continues to rise, and part of this contamination gets transferred into sediments. Analytical methods to detect problematic substances in the environment often use mass spectrometry coupled with chromatography. Here we reviewed a set of 163 articles and compiled the relevant information into a comprehensive database for analysing organic contaminants in continental sediments including suspended particulate matter and surface and bottom sediments in lakes, rivers and estuaries. We found 1204 compounds detected at least once in sediments, and classified them into 11 categories, i.e. hydrocarbons, flame retardants, polychlorinated biphenyls (PCB), plasticizers, per- and poly-fluoroalkyl substances (PFAS), organochlorines (OCP) and other pesticides, pharmaceuticals, hormones, personal care products (PCP), and other contaminants. Concentrations of these compounds varied from a few ng to several mg/kg of dry sediment. Even hydrophilic compounds were detected in high concentrations. Well-known hydrophobic and persistent contaminants tend to be analysed with mass spectrometry coupled to gas chromatography (GC-MS) whereas contaminants of emerging concern (CEC) are usually analysed with liquid chromatography– mass spectrometry (LC-MS). Suspect screening and non-target analysis (NTA), which use high-resolution mass spectrometry, are still scarcely used on sediment but hold promise for gaining deeper knowledge of organic contamination in aquatic environments. [Display omitted] • Continental sediments store a wide array of organic contaminants. • Even highly hydrophilic compounds have been detected at high concentrations. • LC-HRMS is the method of choice to explore contaminants of emerging concerns. • Non-target analysis can help gain deeper knowledge of aquatic contaminants. [ABSTRACT FROM AUTHOR]

Producers of drinking water (DW) occasionally require chemical identification of new or unexpected contamination, e.g., caused by an incident. The state-of-the-art technique for the identification of organic compounds is High-Resolution Mass Spectrometry (HRMS). The ability to discover unexpected compounds at low concentrations in any sample by HRMS is facilitated by comparison to non-contaminated reference samples. Samples of raw and drinking water were collected regularly over one whole year from six Swedish drinking water treatment plants (DWTPs). The samples were analyzed by LC-HRMS together with spiked samples mimicking an incident. This setup enabled evaluation of the significance of having access to a collection of matrix-matched reference samples. The main variation in the organic compound profile in the data set was explained by the uniqueness of the raw water and purification steps in the individual DWTPs. Seasonal variations were also significant but subordinate. This subject was further explored by the analysis of drinking water sampled once from 90 of the 1750 Swedish DWTPs, where a similarity between DW originating from rock aquifers was observed. No other significant correlation between samples was observed—e.g., other types of raw water, which types of purification steps were involved, or which additives or process chemicals were added—which could aid in the selection of relevant reference samples. The conclusion from the study is that it would be imperative for the DWTPs to have access to their individual reference samples for use in the investigation of an incident. A library of such reference samples, e.g., collected monthly and covering the last 12 months, could be stored and used together with a fresh "suspected sample" for non-target HRMS investigations as described. [ABSTRACT FROM AUTHOR]

High resolution mass spectrometry (HR-MS) offers the opportunity to track large numbers of non-target analytes through water treatment processes, providing a more comprehensive view of reactor performance than targeted evaluation. Both approaches were used to evaluate the performance of a pilot scale advanced oxidation process (AOP) employing ultraviolet light and hydrogen peroxide (UV/H2O2) to treat municipal wastewater effluent. Twelve pharmaceuticals and personal care products were selected as target compounds and added to reactor influent. Target compound removal over a range of flow rates and hydrogen peroxide addition levels was assessed using a liquid chromatograph combined with a quadrupole time-of-flight mass spectrometer (LC-qTOF-MS). Target compound removals were used to determine hydroxyl radical concentrations and UV fluence under pilot scale conditions. The experiments were also analyzed using a nontarget approach, which identified "molecular features" in either reactor influent or effluent. Strong correlation (r = 0.94) was observed between target compound removals calculated using the targeted and non-targeted approaches across the range of reactor conditions tested. The two approaches also produced consistent rankings of the performance of the various reactor operating conditions, although the distribution of compound removal efficiencies was usually less favorable with the broader, nontarget approach. For example, in the UV only treatment 8.3% of target compounds and 2.2% of non-target compounds exhibited removals above 50%, while 100% of target compounds and 74% of non-target compounds exhibited removals above 50% in the best condition tested. These results suggest that HR-MS methods can provide more holistic evaluation of reactor performance, and may reduce biases caused by selection of a limited number of target compounds. HR-MS methods also offer insights into the composition of poorly removed compounds and the formation of transformation products, which were widely detected.

The fate of malachite green and its main metabolite leucomalachite green during thermal treatment was examined in seafood (brook trout and white shrimp) using non-target analysis. Samples were extracted using QuEChERS and analyzed using liquid chromatography coupled with quadruple time of flight mass spectrometry. Malachite green levels were reduced in meat during boiling (∼40%), microwaving (64%), and canning (96%). Only microwaving was successful in significantly decreasing leucomalachite green levels in brook trout. The reduction percentages of the two target analytes were not significantly different in shrimp (mean fat content = 0.8 ± 0.3%) and in brook trout (mean fat content = 3.5 ± 1.7%), suggesting that a higher fat content may not affect the reduction of the more lipophilic leucomalachite green in these two matrices. Three transformation products were tentatively identified in the cooked tissues, resulting from the cleavage of the conjugated structure or through demethylation. Further research is needed to determine possible adverse health effects. The findings of this study show how non-target analysis can complement targeted methodologies in identifying and evaluating risks to human health.

Abstract 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.

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]

In an attempt to discover and characterize the plethora of xenobiotic substances, this study investigates chemical compounds released into the environment with wastewater effluents. A novel non-targeted screening methodology based on ultra-high resolution Orbitrap mass spectrometry and nanoflow ultra-high performance liquid chromatography together with a newly optimized data-processing pipeline were applied to effluent samples from two state-of-the-art and one small wastewater treatment facility. In total, 785 molecular structures were obtained, of which 38 were identified as single compounds, while 480 structures were identified at a putative level. Most of these substances were therapeutics and drugs, present as parent compounds and metabolites. Using R packages Phyloseq and MetacodeR, originally developed for bioinformatics, significant differences in xenobiotic presence in the wastewater effluents between the three sites were demonstrated. • The study characterizes a wide spectrum of xenobiotics detected in Danish effluents. • An optimized data-processing pipeline, previously used in microbial ecology, was employed for analysis of chemical data. • 785 chemical structures were identified in the analysis, with the majority classified as therapeutics and drugs. • Several compounds identified are known or suspected endocrine disruptors. • The data reveals significant difference in compound diversity between wastewater effluent at the three sites. [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]

LC/ESI/HRMS is increasingly employed for monitoring chemical pollutants in water samples, with non-targeted analysis becoming more common. Unfortunately, due to the lack of analytical standards, non-targeted analysis is mostly qualitative. To remedy this, models have been developed to evaluate the response of compounds from their structure, which can then be used for quantification in non-targeted analysis. Still, these models rely on tentatively known structures while for most detected compounds, a list of structural candidates, or sometimes only exact mass and retention time are identified. In this study, a quantification approach was developed, where LC/ESI/HRMS descriptors are used for quantification of compounds even if the structure is unknown. The approach was developed based on 92 compounds analyzed in parallel in both positive and negative ESI mode with mobile phases at pH 2.7, 8.0, and 10.0. The developed approach was compared with two baseline approaches— one assuming equal response factors for all compounds and one using the response factor of the closest eluting standard. The former gave a mean prediction error of a factor of 29, while the latter gave a mean prediction error of a factor of 1300. In the machine learning-based quantification approach developed here, the corresponding prediction error was a factor of 10. Furthermore, the approach was validated by analyzing two blind samples containing 48 compounds spiked into tap water and ultrapure water. The obtained mean prediction error was lower than a factor of 6.0 for both samples. The errors were found to be comparable to approaches using structural information.