Complex mixtures of organic chemicals extracted from representative but not directly related environmental samples (wastewater, surface water, fish), food items (drinking water, fish, milk) and human blood were tested in 22 in vitro bioassays targeting pathways associated with neurodevelopmental and reproductive health. Extraction methods were optimized to extract common chemicals across matrices capturing both persistent and nonpersistent, neutral and charged organic chemicals─albeit with some bias toward more hydrophilic chemicals over highly hydrophobic chemicals. Most bioassay end points─except genotoxicity─were responsive, with strongest effects observed higher up the food chain in fish and humans. Experimental mixture effects of 24 chemicals quantified in these extracts conformed to the mixture prediction model of concentration addition in the six most responsive bioassays, namely neurite outgrowth inhibition, mitochondrial membrane potential inhibition, transthyretin protein binding, sodium-iodide symporter inhibition and androgen receptor antagonism. Designed mixtures explained little of total bioactivity, indicating that many of the thousands of unannotated molecular features detected by nontarget analysis contribute to mixture effects. Preliminary effect-based trigger (EBT) values defined for water and food by extrapolation from safe levels of individual chemicals indicate no immediate health risks at these average contamination levels. The high complexity and multivalent bioactivity of these mixtures on neurodevelopmental and reproductive pathways necessitate further toxicological scrutiny.

Microplastics (MPs) in fish for consumption are considered a potential pathway for human exposure. While MPs have been widely detected in the digestive tracts of various fish species, their translocation to other organs and edible tissues remains poorly understood. The present study aimed to investigate the potential translocation of MPs in the liver, gonads, and fillet of adult Nile tilapia (Oreochromis niloticus) after 7 days of dietary exposure. Adult fish were fed with feed containing a mixture of four polymer types, polyethylene (PE), polypropylene (PP), polyethylene terephthalate (PET), and polyamide 6 (PA6), in irregular shapes and sizes ranging from 10 to 350 mu m. The polymers were quantified in the tissues using pyrolysis gas chromatography coupled with mass spectrometry (Py-GC-MS). Minimal MP accumulation was detected in liver and gonad samples, with MPs detected in fewer than 50 % of samples. No MPs were detected in fillet tissue of either control or exposed fish, suggesting no translocation of MPs to edible muscle within the exposure period. Complementary analysis with micro-Fourier transform infrared spectroscopy (mu-FTIR) and optical microscopy on fecal matter revealed a high abundance of MPs, suggesting efficient excretion of ingested particles. These results demonstrated that short-term dietary exposure to MPs leads to negligible bioaccumulation in tilapia tissues, highlighting excretion as the dominant elimination pathway. This study provides novel evidence on the limited transfer of MPs for the analyzed size range to edible tissues in aquaculture species, with implications for food safety risk assessment.

Biomonitoring of occupational exposure to mixtures of chemicals remains a major challenge, as conventional targeted approaches can only cover a limited number of compounds. Suspect and non-target screening (SS/NTS) using high-resolution mass spectrometry offers a more comprehensive approach, however wider implementation requires robust and comparable analytical strategies with broad chemical coverage. An interlaboratory study was conducted within the European Partnership for the Assessment of Risks from Chemicals (PARC) to evaluate the comparability and complementarity of SS/NTS approaches and to support the development of a standard operating procedure (SOP) for occupational biomonitoring. Urine and plasma samples fortified with 81 occupationally-relevant exposure markers at three concentration levels were distributed to eleven European laboratories from eight Member States and measured via their respective in-house Liquid Chromatography- and Gas Chromatography-High Resolution Mass Spectrometry (LC- and GC-HRMS) workflows. Thirteen different analytical methods were applied: nine to both matrices, three to urine only and one exclusively to plasma samples. Eleven methods enabled detection of more than half of the fortified exposure markers (> 40 compounds) in the standard mixture, whilst eight and seven methods achieved the same for urine and plasma samples, respectively. Despite substantial methodological differences, numerous compounds were shared across Reversed-Phase (RP) and Hydrophilic Interaction Liquid Chromatography (HILIC) methods (57 in urine and 34 in plasma), with RP providing higher overall detection rates (eleven and 29 compounds detected exclusively by RP in urine and plasma, respectively). In addition, four compounds were detected exclusively by GC-HRMS in the biological matrices, demonstrating that combining SS/NTS workflows broadens chemical space coverage. The solvent selected for extraction appears to have an influence on the detection performance, with solvents providing broader polarity coverage, such as mixtures of methanol or acetonitrile with water, generally associated with optimal results, across the different sample preparation techniques employed. Solid phase extraction and deconjugation did not show an improvement in performance in these large-scale SS applications. Based on this interlaboratory study, a minimal SOP is proposed to support SS/NTS implementation in future large-scale human biomonitoring studies, including characterization of occupational cohorts within PARC.

Chemical pollution can affect ecosystems and human health, highlighting the need for approaches that identify, evaluate, and prioritize emerging chemical risks before they become established public-health issues requiring regulatory actions. This review and perspective article examines methodological components required for Early Warning Systems (EWSs) for chemical risks, with particular attention to the European policy context. It examines methodological components for chemical EWSs rather than proposing a fully implemented system. It considers how state-of-the-art and emerging methods can support signal generation, signal strengthening, prioritization, uncertainty assessment, communication, and follow-up. The reviewed components include matrices and sampling strategies; chemical monitoring, suspect screening, and non-target screening; effect-based methods, New Approach Methodologies, and effect-directed analysis; exposure and hazard modelling; QSAR, read-across, AI-supported and data-mining tools; expert evaluation; and governance processes that link scientific signals to proportionate follow-up. The conceptual workflow is used as an example of how these components may be organized into a signal-handling process, while EU-level developments provide the broader policy and governance context. The actionable value of a chemical EWS does not depend on any single method, but on structured integration of complementary evidence streams. An effective EWS should combine sensitive weak-signal detection with transparent prioritization, explicit uncertainty assessment, FAIR and interoperable data infrastructures, and clearly assigned responsibilities for communication and follow-up.

Metabolism is critical for neurodevelopment, yet the mechanisms by which endocrine-disrupting chemicals (EDCs) contribute to neurodevelopmental disorders remain poorly defined. Using a rat model, we investigated hippocampal metabolomic responses at postnatal day 6 following maternal exposure to six structurally diverse EDCs (bisphenol F, permethrin, butyl benzyl phthalate, triphenyl phosphate, perfluorooctane sulfonic acid, and DINCH) from pre-mating through lactation. Targeted steroid, thyroid, and neurosteroid hormones, neurotransmitters, and untargeted lipidomics were profiled to map disrupted pathways. The analysis revealed sex-specific, chemical-specific, and shared metabolic signatures of developmental neurotoxicity. Key affected endpoints across chemicals included corticosterone, pregnenolone sulfate, and N-acylethanolamine lipids, confirming hormonal disruption while uncovering novel non-EATS (estrogen, androgen, thyroid, and steroidogenesis) pathways and mechanisms of action. These findings provide new insights into EDC-mediated disruption of hippocampal development and identify potential molecular biomarkers that may support future mechanistic research and chemical risk assessment.

Chemical contaminants are widely dispersed in the environment in all its dimensions, posing significant public health problems. Comprehensive knowledge of these stressors is a prerequisite for assessing the associated risk and implementing public policy measures to reduce the level of population exposure. Nontargeted suspect screening approaches broaden the knowledge of the chemical human exposome. We developed and used a suspect screening method based on large spectral libraries. Chemical profiling was based on a combined LC- and GC-HRMS approach. The methodology was applied to 16 samples spanning the environment, food, and health continuum. Using a combination of matching and scoring data, a total of 547 compounds were likely identified, from which the chemical structure of 63 molecules was confirmed to the highest level of certainty. Wastewater, and more generally environmental samples, had the highest number of chemicals detected, while fish samples had a lower number. Pharmaceuticals, pesticides, and personal care product-related compounds were found to be the most common compounds in and between the extracts, particularly in water and serum samples. Many natural and endogenous compounds were consistently annotated in the samples submitted for analysis, regardless of the compartment investigated.

This study investigated how the insecticide teflubenzuron disrupts lipid metabolism in the springtail Folsomia candida, revealing significant alterations in lipid profiles. F. candida was exposed to sub-lethal concentrations of teflubenzuron (0, 0.006, 0.014, 0.035 mg a.s. kg-1 soil dry weight). Untargeted lipidomics was used to study the dynamic changes in lipid profiles in the springtail over exposure intervals of 2, 7, and 14 days exposure intervals. Teflubenzuron induced shifts in lipid profiles, affecting lipid pathways crucial for energy storage, membrane integrity, and signaling, which are essential for survival, reproduction, and stress responses in this springtail. Diacylglycerols (DG) and Triacylglycerols (TG), which play crucial roles in energy storage and lipid-mediated signaling, were substantially affected by teflubenzuron. Decreased levels of DG and TG suggest a shift in priorities from reproduction to maintenance functions, implying disruptions in cholesterol homeostasis and vitellogenesis in response to teflubenzuron exposure. Furthermore, increased levels of fatty acids and N-acylethanolamines in response to teflubenzuron exposure indicated increased energy production and potential oxidative stress, highlighting the springtails' response to pesticide exposure. Certain lipid alterations (N-palmitoylethanolamine (NAE 16:0) and N-stearoylethanolamine (NAE 18:0)), known for their anti-inflammatory properties, point towards inflammation and mitochondrial membrane remodeling (alternations in cardiolipin lipids), indicating broader impacts on physiological functions. Ether glycerophospholipids, such as lysophosphatidylethanolamine and phosphatidylethanolamine, linked to peroxisomes and the endoplasmic reticulum, underscore their potential antioxidative role in response to oxidative stress. The study shows the significance of incorporating life cycle events into ecotoxicological assessments to comprehensively understand pesticide impacts on organisms. The integration of lipidomics into environmental risk assessments offers a more informed approach to pesticide regulation and environmental stewardship.

BACKGROUND:Micro-/nanoplastics (MNPs) are ubiquitous environmental contaminants and there has been a growing concern about their potential adverse effects on human health. The present study reports on the development of a novel pyrolysis-gas chromatography x ion mobility mass spectrometry method to identify MNPs in placental blood, while reducing false positive detections from matrix interferences. RESULTS:Base digestion and filtration yielded acceptable recoveries: 90 ± 11 % for polystyrene (PS), 93 ± 16 % for polyethylene (PE), and 53 ± 18 % for polypropylene (PP). Limit of Detections (LODs) ranged from 0.15 to 0.60 μg/mL, depending on the polymer. Placental blood samples were collected from 46 donors and analyzed in triplicate, resulting in measurements for 138 samples. Forty-three samples contained at least one polymer type above the limit of detection, and 10 samples contained at least one polymer type above the limit of quantification. Total plastic concentration in samples with detectable levels (>LOD) of MNPs averaged 0.9 μg/mL and ranged between 0.2 and 3.6 μg/mL. Orthogonal separation by ion mobility revealed that 10/22 PE detections were false positives. SIGNIFICANCE:This study is the first to integrate ion mobility separation to differentiate between genuine and false detection of PE in human blood. Without the aid of ion mobility separation, the concentration of PE in individual samples was overestimated by up to 233 % of the mean MNP concentration, underlining the importance of multidimensional separation for individual exposure analysis.

Micro- and nanoplastics (MNPs) are abundant in the environment, with traffic-related tyre-wear contributing substantially to atmospheric levels. MNPs have been detected in human tissues, however, their health effects remain poorly known. Therefore, we assessed immunological and respiratory health changes associated with short-term exposure to traffic-related MNPs in healthy, young adults. In a semi-controlled study design, 23 healthy subjects participated in four-hour exposure sessions at three different sites: a highway, a stop-and-go high-traffic location and an urban park. Directly before and after, and the following morning, we collected venous blood samples to assess changes in total and differential white blood cell (WBC) counts. Before and directly after each visit we measured lung function and respiratory symptoms. During each exposure session, atmospheric synthetic and natural rubber particles were collected and measured using pyrolysis gas-chromatography coupled to mass-spectrometry, within particles smaller than 10 µm (PM10). Additionally, traffic-related combustion and brake wear-related pollutants were measured including PM10, ultrafine particles, black carbon, trace metals and polycyclic aromatic hydrocarbons. Mixed model analyses were used to assess changes in WBC counts and lung function from baseline to post-exposure (pairwise differences), adjusting for time-varying and subject-dependent covariates. We observed significant associations between an interquartile range increase in multiple tyre-wear rubber markers and a 7.1-9.3 % elevation in monocytes in blood obtained immediately after exposure. Moreover, in blood obtained the following morning, these associations not only persisted but increased for monocytes (9.3-17.7 %) and were additionally found for neutrophils (7.4-14.0 %). The associations remained consistent after adjusting for other traffic-related air pollutants. Null associations were found with lung function and symptoms. Short-term exposure to traffic-related MNPs was associated with an increase in total and differential WBCs. Associations might be indicative of pro-inflammatory effects in healthy people, which could lead to clinically relevant responses in vulnerable populations.

Effective environmental risk assessments of chemical plant protection products, such as benzoylurea pesticides, are crucial for safeguarding ecosystems. These pesticides, including teflubenzuron, target chitin synthesis in arthropods but also pose risks to non-target soil fauna like Collembola, which play essential roles in decomposition and nutrient cycling. This study combines traditional toxicity tests with a metabolomic approach to examine the interspecies specific sensitivity of three Collembola species - Sinella curviseta, Ceratophysella denticulata, and Folsomia candida - to teflubenzuron. The investigation focused on reproduction, bioaccumulation, and changes in chitin-related metabolites as indicators of pesticide impacts. Results revealed significant interspecies specific variability in sensitivity, with F. candida showing higher susceptibility towards teflubenzuron, possibly due to greater bioaccumulation factors. Metabolomic analysis highlighted distinct patterns in chitin metabolite alterations among the species, correlating with their differential sensitivity. Notably, metabolites like trehalose and glucose, crucial for chitin synthesis, were significantly affected by teflubenzuron within seven days of exposure. Despite high soil concentrations of the pesticide, S. curviseta demonstrated resilience in traditional life-history endpoints, such as reproduction and survival. However, metabolomics indicated a biochemical response to even low internal concentrations of teflubenzuron, underscoring the complexity of their interactions with environmental stressors. This study emphasizes the importance of incorporating metabolomics to understand the differential responses of non-target organisms to pesticides and advocates for species-specific risk assessments in pesticide regulation. The distinct metabolic responses among Collembola species to chitin synthesis inhibitors provide critical insights into their ecological resilience or vulnerability, enhancing our understanding of ecosystem dynamics and the potential ramifications of chemical exposure.

Pharmaceuticals such as selective serotonin reuptake inhibitors (SSRIs), are increasingly detected in aquatic environments, posing potential risks to non-target organisms, because many of those substances are widely shared neuromodulator. In this study, we investigated the effects of SSRI antidepressant, namely, fluoxetine, exposure on the freshwater snail L. stagnalis, focusing on egg development, neurochemical pathways, and lipid metabolism. Snails were exposed to a range of 51–434 µg fluoxetine L⁻1 for 7 days, followed by analysis of survival, feeding behaviour, reproduction, and metabolomic changes in the central nervous system (CNS), albumen gland, and eggs. Although no significant effects were observed on survival or fecundity, fluoxetine exposure significantly impaired egg development in a dose-dependent manner, reducing hatching rates with an EC50 of 126 µg fluoxetine L⁻1. Removal of eggs from the contaminated environment partially reversed these developmental effects, suggesting potential recovery if fluoxetine levels decrease. Molecular analysis revealed several neurochemical and lipidomic alterations. In the CNS, elevated levels of catecholamines, phosphatidylcholines (PC), and ceramides were linked to disruptions in neurotransmission, membrane integrity, and impaired embryo development. In the albumen gland, we detected a decrease of key lipid classes, including sphingomyelins and fatty acids, which can be linked with impaired egg quality. Additionally, a decrease in histamine in both the albumen gland and eggs suggested further disruption of egg development, potentially affecting metamorphosis success. Moreover, the dose-dependent increase in choline, along with PC and oxidized PC, indicated oxidative stress and lipid peroxidation in the CNS and exposed eggs of Lymnaea stagnalis. Our findings highlight the benefits of combining behavioral assessments with metabolomic profiling to better understand the mechanistic pathways underlying fluoxetine’s adverse effects.

As evidence demonstrating the presence of micro- and nanoplastics (MNPs) in the human body accumulates, so do concerns about their potential health impacts. Multiple factors determine the properties and behavior of MNPs-including polymer type, size, shape and the presence of a biocorona, among others-which place high demands on analytical methodology and tools for assessment of potential adverse health effects. Experimental models have shown that MNPs can cross cell barriers in the human lung and intestine and reach systemic circulation and subsequently tissues such as reproductive organs, placenta and brain. Early clinical findings indicate that MNPs may be associated with adverse health outcomes, including immune modulation, reproductive effects and cardiovascular effects. However, these studies typically suffer from low patient numbers and inadequate MNP exposure assessment, which precludes adequate risk assessment. Still, outcomes from animal and cell-based analyses generally support the preliminary clinical findings. To conduct more robust human studies, maturation of methods for exposure and effect assessment are crucial. Addressing these challenges will improve scientific research on the health impact of MNPs, which is urgently needed.

Accurate analytical methods are crucial to assess human exposure to micro- and nanoplastics (MNPs). Quantitative pyrolysis-gas chromatography coupled with mass spectrometry (Py-GC-MS) has recently been used for quantifying MNPs in human blood. However, pyrolysis introduces complex effects such as secondary reactions between matrix compounds and polymers. This work introduces a non-targeted and multivariate approach to improve the identification and quantification of polyethylene (PE), poly(vinyl chloride) (PVC) and polyethylene terephthalate (PET). After spiking of extracted blood samples, PARADISe was used for componentization and integration of 417 features detected with Py-GC-MS. Quantification based on multivariate calibration models demonstrated a superior performance when compared to univariate regression. Feature selection approaches were used to identify optimal feature subsets, which reduced quantification errors by 30 % for PE, 10 % for PVC and 38 % for PET. In addition, chemical insight into pyrolysis processes was obtained by studying the matrix effects (MEs) of blood. The pyrolysis of PE and PVC appeared to be minimally affected (MEs = 81-154 %), while PET exhibited complex interactions with the matrix (MEs = 40-9031 %), impacting its quantification accuracy. In conclusion, this research highlights the importance of accounting for secondary effects during pyrolysis and introduces a multivariate approach for more accurate and robust quantification of MNPs in blood.

Bioassays are increasingly applied in the monitoring of chemical water quality. To determine whether elevated bioassay activities indicate a risk, identification of the active substances is needed. This study investigated the presence and fate of 10 biological activities detected by CALUX bioassays and chemical contaminants detected by targeted screening in sources and treatments of drinking water companies in the Dutch parts of the Rhine and Meuse catchments. This was reported in the accompanying article. As the correlations elucidated by the hierarchical cluster analysis approach did not in all cases reveal the causative compounds, effect directed analysis (EDA) was performed and reported in this article. By embedding the p53 and the Nrf2 CALUX bioassays (for genotoxicity and oxidative stress, respectively) in an earlier developed high throughput EDA platform, the identification of contributors to multiple different endpoints was achieved. The platform combined microfractionation, miniaturised bioassays and targeted screening using high resolution mass spectrometry, and was applied to eight samples. Natural and synthetic steroid hormones and their metabolites were identified as contributors to androgenic, estrogenic, glucocorticoid and progestogenic activities. Fourteen pesticides were found to contribute to anti-androgenic, anti-progestogenic and/or cytotoxic activities, underlining the increasing public concern of pesticide use. Two pharmaceuticals contributed to oxidative stress in the WWTP effluent sample. Although the p53 CALUX assay was successfully integrated in the EDA platform, is was not applied to water samples due to lack of detectable activity. The applied EDA platform proved to be powerful to identify bioactive compounds in water with a high endpoint coverage in a high throughput format. EDA creates an integrated and risk-based view on those contaminants that deteriorate chemical water quality.

Effect-Directed Analysis (EDA) was used to identify bioactive compounds in surface and well water from the Upper Rhine, and to evaluate their properties against the criteria set for Persistent, Mobile and Toxic (PMT) and very persistent and very mobile (vPvM) substances. A multi-layered solid-phase extraction was implemented to enrich a broad range of polar substances from the collected samples. The extracts were fractionated into 108 fractions and tested in the transthyretin (TTR)-binding assay measuring displacement of fluorescently labeled thyroxine (FITC-T4 TTR-binding assay) and the Aliivibrio fischeri bioluminescence (AFB) bioassay. Bioactive fractions guided the identification strategy using high-resolution mass spectrometry. Chemical features were systematically annotated using library databases and suspect lists, incorporating an automated assessment of the quality of each annotation. Based on this assessment, each chemical feature was assigned a specific identification confidence level. Identification of bioactive compounds was facilitated by using bioassay specific suspect lists that were extracted from an in-house developed database of positive and negative TTR-binding compounds and from a recently published database of active inhibitors of AFB. This resulted in the identification and confirmation of ten bioactive substances, including four evaluated as PMT and vPvM substances (diclofenac, trifloxystrobin acid, 6:2 FTSA and PFOA), and one as a potential PMT substance (4-aminoazobenzene). This study demonstrates the effectiveness of EDA in the identification of PMT/vPvM substances in the aquatic environment, facilitating their prioritization for comprehensive environmental risk assessment and possible regulation.

Nontarget screening (NTS) with liquid chromatography high-resolution mass spectrometry (LC-HRMS) is commonly used to detect unknown organic micropollutants in the environment. One of the main challenges in NTS is the prioritization of relevant LC-HRMS features. A novel prioritization strategy based on structural alerts to select NTS features that correspond to potentially hazardous chemicals is presented here. This strategy leverages raw tandem mass spectra (MS2) and machine learning models to predict the probability that NTS features correspond to chemicals with structural alerts. The models were trained on fragments and neutral losses from the experimental MS2 data. The feasibility of this approach is evaluated for two groups: aromatic amines and organophosphorus structural alerts. The neural network classification model for organophosphorus structural alerts achieved an Area Under the Curve of the Receiver Operating Characteristics (AUC-ROC) of 0.97 and a true positive rate of 0.65 on the test set. The random forest model for the classification of aromatic amines achieved an AUC-ROC value of 0.82 and a true positive rate of 0.58 on the test set. The models were successfully applied to prioritize LC-HRMS features in surface water samples, showcasing the high potential to develop and implement this approach further.

Existing regulatory frameworks often prove inadequate in identifying contaminants of emerging concern (CECs) and determining their impacts on biological systems at an early stage. The establishment of Early Warning Systems (EWSs) for CECs is becoming increasingly relevant for policy-making, aiming to proactively detect chemical hazards and implement effective mitigation measures. Effect-based methodologies, including bioassays and effect-directed analysis (EDA), offer valuable input to EWSs with a view to pinpointing the relevant toxicity drivers and prioritizing the associated risks. This review evaluates the analytical techniques currently available to assess biological effects, and provides a structured plan for their systematic integration into an EWS for hazardous chemicals in the environment. Key scientific advancements in effect-based approaches and EDA are discussed, underscoring their potential for early detection and management of chemical hazards. Additionally, critical challenges such as data integration and regulatory alignment are addressed, emphasizing the need for continuous improvement of the EWS and the incorporation of analytical advancements to safeguard environmental and public health from emerging chemical threats.