Unraveling the Pollution and Discharge of Aminophenyl Sulfone Compounds, Sulfonamide Antibiotics, and Their Acetylation Products in Municipal Wastewater Treatment Plants.

Aminophenyl sulfone compounds (ASCs) are widely used in various fields, such as the pharmaceutical and textile industries. ASCs and their primary acetylation products are inevitably discharged into the environment. However, the high toxicity of ASCs could be released from the deacetylation of acetylation products. Still, the occurrence and ecological risks of ASCs and their acetylation products remain largely unknown. Here, we integrated all of the existing ASCs based on the core structure, together with their potential acetylation products, to establish a database covering 1105 compounds. By combining the database with R programming, 45 ASCs, sulfonamides, and their acetylation products were identified in the influent and effluent of 19 municipal wastewater treatment plants in 4 cities of China. 13 of them were detected for the first time in the aquatic environment, and 12 acetylation products were newly identified. The cumulative concentrations of 45 compounds in the influent and effluent were in the range of 231-9.96 × 103 and 26-2.70 × 103 ng/L, respectively. The proportion of the unrecognized compounds accounted for 60.6% of the influent and 62.8% of the effluent. Furthermore, nearly half of the ASCs (46.7%), other sulfonamides (49.9%), and their acetylation products (46.2%) were discharged from the effluent, posing a low-to-medium risk to aquatic organisms. The results provide a guideline for future monitoring programs, particularly for sulfadiazine and dronedarone, and emphasize that the ecological risk of ASCs, sulfonamides, and their acetylation products needs to be considered in the aquatic environment.

Biotransformation of Organophosphate Diesters Characterized via In Vitro Metabolism and In Vivo Screening.

Organophosphate diesters (di-OPEs), as additives in industrial applications and/or transformation products of emerging environmental pollutants, such as organophosphate triesters (tri-OPEs), have been found in the environment and biological matrices. The metabolic fate of di-OPEs in biological media is of great significance for tracing the inherent and precursor toxicity variations. This is the first study to investigate the metabolism of a suite of di-OPEs by liver microsomes and to identify any metabolite of metabolizable di-OPEs in in vitro and in vivo samples. Of the 14 di-OPEs, 5 are significantly metabolizable, and their abundant metabolites with hydroxyl, carboxyl, dealkylated, carbonyl, and/or epoxide groups are tentatively identified. More than half of the di-OPEs are detectable in human serum and/or wild fish tissues, and dibenzyl phosphate (DBzP), bis(2,3-dibromopropyl) phosphate (BDBPP), and isopropyl diphenyl phosphate (ip-DPHP) are first reported at a detectable level in humans and wildlife. Using an in vitro assay and a known biotransformation rule-based integrated screening strategy, 2 and 10 suspected metabolite peaks of DEHP are found in human serum and wild fish samples, respectively, and are then identified as phase I and phase II metabolites of DEHP. This study provides a novel insight into fate and persistence of di-OPE and confirms the presence of di-OPE metabolites in humans and wildlife.

Combining Advanced Analytical Methodologies to Uncover Suspect PFAS and Fluorinated Pharmaceutical Contributions to Extractable Organic Fluorine in Human Serum (Tromsø Study).

A growing number of studies have reported that routinely monitored per- and polyfluoroalkyl substances (PFAS) are not sufficient to explain the extractable organic fluorine (EOF) measured in human blood. In this study, we address this gap by screening pooled human serum collected over 3 decades (1986-2015) in Tromsø (Norway) for >5000 PFAS and >300 fluorinated pharmaceuticals. We combined multiple analytical techniques (direct infusion Fourier transform ion cyclotron resonance mass spectrometry, liquid chromatography-Orbitrap-high-resolution mass spectrometry, and total oxidizable precursors assay) in a three-step suspect screening process which aimed at unequivocal suspect identification. This approach uncovered the presence of one PFAS and eight fluorinated pharmaceuticals (including some metabolites) in human serum. While the PFAS suspect only accounted for 2-4% of the EOF, fluorinated pharmaceuticals accounted for 0-63% of the EOF, and their contribution increased in recent years. Although fluorinated pharmaceuticals often contain only 1-3 fluorine atoms, our results indicate that they can contribute significantly to the EOF. Indeed, the contribution from fluorinated pharmaceuticals allowed us to close the organofluorine mass balance in pooled serum from 2015, indicating a good understanding of organofluorine compounds in humans. However, a portion of the EOF in human serum from 1986 and 2007 still remained unexplained.

Occurrence and Prioritization of Human Androgen Receptor Disruptors in Sewage Sludges Across China.

The global practice of reusing sewage sludge in agriculture and its landfill disposal reintroduces environmental contaminants, posing risks to human and ecological health. This study screened sewage sludge from 30 Chinese cities for androgen receptor (AR) disruptors, utilizing a disruptor list from the Toxicology in the 21st Century program (Tox21), and identified 25 agonists and 33 antagonists across diverse use categories. Predominantly, natural products 5α-dihydrotestosterone and thymidine emerged as agonists, whereas the industrial intermediate caprolactam was the principal antagonist. In-house bioassays for identified disruptors displayed good alignment with Tox21 potency data, validating employing Tox21 toxicity data for theoretical toxicity estimations. Potency calculations revealed 5α-dihydrotestosterone and two pharmaceuticals (17ß-trenbolone and testosterone isocaproate) as the most potent AR agonists and three dyes (rhodamine 6G, Victoria blue BO, and gentian violet) as antagonists. Theoretical effect contribution evaluations prioritized 5α-dihydrotestosterone and testosterone isocaproate as high-risk AR agonists and caprolactam, rhodamine 6G, and 8-hydroxyquinoline (as a biocide and a preservative) as key antagonists. Notably, 16 agonists and 20 antagonists were newly reported in the sludge, many exhibiting significant detection frequencies, concentrations, and/or toxicities, demanding future scrutiny. Our study presents an efficient strategy for estimating environmental sample toxicity and identifying key toxicants, thereby supporting the development of appropriate sludge management strategies.

Suspect Screening Analysis of Pooled Human Serum Samples Using GC × GC/TOF-MS.

Humans interact with thousands of chemicals. This study aims to identify substances of emerging concern and in need of human health risk evaluations. Sixteen pooled human serum samples were constructed from 25 individual samples each from the National Institute of Environmental Health Sciences' Clinical Research Unit. Samples were analyzed using gas chromatography (GC) × GC/time-of-flight (TOF)-mass spectrometry (MS) in a suspect screening analysis, with follow-up confirmation analysis of 19 substances. A standard reference material blood sample was also analyzed through the confirmation process for comparison. The pools were stratified by sex (female and male) and by age (≤45 and >45). Publicly available information on potential exposure sources was aggregated to annotate presence in serum as either endogenous, food/nutrient, drug, commerce, or contaminant. Of the 544 unique substances tentatively identified by spectral matching, 472 were identified in females, while only 271 were identified in males. Surprisingly, 273 of the identified substances were found only in females. It is known that behavior and near-field environments can drive exposures, and this work demonstrates the existence of exposure sources uniquely relevant to females.

How Wastewater Reflects Human Metabolism─Suspect Screening of Pharmaceutical Metabolites in Wastewater Influent.

Pharmaceuticals and their human metabolites are contaminants of emerging concern in the aquatic environment. Most monitoring studies focus on a limited set of parent compounds and even fewer metabolites. However, more than 50% of the most consumed pharmaceuticals are excreted in higher amounts as metabolites than as parents, as confirmed by a literature analysis within this study. Hence, we applied a wide-scope suspect screening approach to identify human pharmaceutical metabolites in wastewater influent from three Swiss treatment plants. Based on consumption amounts and human metabolism data, a suspect list comprising 268 parent compounds and over 1500 metabolites was compiled. Online solid phase extraction combined with liquid chromatography coupled to high-resolution tandem mass spectrometry was used to analyze the samples. Data processing, annotation, and structure elucidation were achieved with various tools, including molecular networking as well as SIRIUS/CSI:FingerID and MetFrag for MS2 spectra rationalization. We confirmed 37 metabolites with reference standards and 16 by human liver S9 incubation experiments. More than 25 metabolites were detected for the first time in influent wastewater. Semiquantification with MS2Quant showed that metabolite to parent concentration ratios were generally lower compared to literature expectations, probably due to further metabolite transformation in the sewer system or limitations in the metabolite detection. Nonetheless, metabolites pose a large fraction to the total pharmaceutical contribution in wastewater, highlighting the need for metabolite inclusion in chemical risk assessment.

Closing the Organofluorine Mass Balance in Marine Mammals Using Suspect Screening and Machine Learning-Based Quantification.

High-resolution mass spectrometry (HRMS)-based suspect and nontarget screening has identified a growing number of novel per- and polyfluoroalkyl substances (PFASs) in the environment. However, without analytical standards, the fraction of overall PFAS exposure accounted for by these suspects remains ambiguous. Fortunately, recent developments in ionization efficiency (IE) prediction using machine learning offer the possibility to quantify suspects lacking analytical standards. In the present work, a gradient boosted tree-based model for predicting log IE in negative mode was trained and then validated using 33 PFAS standards. The root-mean-square errors were 0.79 (for the entire test set) and 0.29 (for the 7 PFASs in the test set) log IE units. Thereafter, the model was applied to samples of liver from pilot whales (n = 5; East Greenland) and white beaked dolphins (n = 5, West Greenland; n = 3, Sweden) which contained a significant fraction (up to 70%) of unidentified organofluorine and 35 unquantified suspect PFASs (confidence level 2-4). IE-based quantification reduced the fraction of unidentified extractable organofluorine to 0-27%, demonstrating the utility of the method for closing the fluorine mass balance in the absence of analytical standards.

Comprehensive Characterization of Organic Light-Emitting Materials in Breast Milk by Target and Suspect Screening.

Organic light-emitting materials (OLEMs) are emerging contaminants in the environment and have been detected in various environment samples. However, limited information is available regarding their contamination within the human body. Here, we developed a novel QuEChERS (quick, easy, cheap, effective, rugged, and safe) method coupled with triple quadrupole/high-resolution mass spectrometry to determine OLEMs in breast milk samples, employing both target and suspect screening strategies. Our analysis uncovered the presence of seven out of the 39 targeted OLEMs in breast milk samples, comprising five liquid crystal monomers and two OLEMs commonly used in organic light-emitting diode displays. The cumulative concentrations of the seven OLEMs in each breast milk sample ranged from ND to 1.67 × 103 ng/g lipid weight, with a mean and median concentration of 78.76 and 0.71 ng/g lipid weight, respectively, which were higher compared to that of typical organic pollutants such as polychlorinated biphenyls and polybrominated diphenyl ethers. We calculated the estimated daily intake (EDI) rates of OLEMs for infants aged 0-12 months, and the mean EDI rates during lactation were estimated to range from 30.37 to 54.89 ng/kg bw/day. Employing a suspect screening approach, we additionally identified 66 potential OLEMs, and two of them, cholesteryl hydrogen phthalate and cholesteryl benzoate, were further confirmed using pure reference standards. These two substances belong to cholesteric liquid crystal materials and raise concerns about potential endocrine-disrupting effects, as indicated by in silico predictive models. Overall, our present study established a robust method for the identification of OLEMs in breast milk samples, shedding light on their presence in the human body. These findings indicate human exposure to OLEMs that should be further investigated, including their health risks.

Suspect screening for chemical residues in aquacultured shrimp and fish using liquid chromatography-high resolution mass spectrometry: comparison of data evaluation approaches.

High-resolution mass spectrometry (HRMS) has become an important tool for monitoring chemical residues in food, but the time and effort required to evaluate the large amount of data generated by HRMS can be a limiting factor in the widespread application of this tool. Suspect screening, i.e., searching HRMS data against large compound databases or mass lists, represents a practical compromise between using HRMS data to only look for target compounds and performing full non-target analysis. Several different approaches for suspect screening using HRMS data were tested using data from shrimp and eel spiked with veterinary drugs and pesticides as well as from imported aquaculture samples. Most of the analytes (>70%) in the spiked samples were detected and identified by searching against compound databases. To query larger databases and on-line resources such as mzCloud, it was necessary to use software capable of differential analysis and selective filtering, such as Compound Discoverer. Using selective filtering, the number of compounds detected in fish sample extracts could be reduced from tens of thousands to a few hundred by subtracting method blanks and comparing to matrix blank extracts. This smaller list of potential compounds could be further evaluated and compared to available databases and libraries. Analysis of imported aquaculture samples resulted in detection of unexpected contaminants including the dewormer levamisole, the insecticide buprofezin, and potentially the plant alkaloid ricinine.

GC × GC-HRMS with complementary ionization methods in the suspect screening analysis of fragrance allergens: overwhelming or justified?

Modern gas chromatography-mass spectrometry (GC-MS) allows for the analysis of complex samples, such as fragrances. However, identifying all the constituents in natural fragrance mixtures, especially allergens that need to be listed on product labels, is a significant challenge. This is primarily due to the high complexity of the sample and the fact that electron ionization, the most commonly used ionization method in GC-MS, produces numerous nonspecific fragment ions, often resulting in the absence or very low abundance of the molecular ion. These factors affect confidence in assigning the analyte. In this study, we demonstrate that the combination of GC × GC separation, with high mass resolution and accurate mass measurements, as well as chemical ionization in addition to traditional electron ionization, becomes an efficient tool for reliable qualitative analysis of a mixture containing 100 fragrance allergens, even when many of them are closely related species or isomers. The proposed approach expands the applicability of the comprehensive GC × GC-HRMS method, which includes complementary ionization techniques, from studies on anthropogenic priority pollutants and emerging contaminants to the analysis of natural products. Although targeted qualitative and quantitative analysis of allergens in the modern laboratories is well organized, GC × GC-HRMS, being a useful complement to routine quality control of volatile allergens in fragrances, definitely gives an additional contribution to the analytical cases when conventional 1D-GC-MS faces some problems or uncertainties.

Improving predictions of compound amenability for liquid chromatography-mass spectrometry to enhance non-targeted analysis.

Mass-spectrometry-based non-targeted analysis (NTA), in which mass spectrometric signals are assigned chemical identities based on a systematic collation of evidence, is a growing area of interest for toxicological risk assessment. Successful NTA results in better identification of potentially hazardous pollutants within the environment, facilitating the development of targeted analytical strategies to best characterize risks to human and ecological health. A supporting component of the NTA process involves assessing whether suspected chemicals are amenable to the mass spectrometric method, which is necessary in order to assign an observed signal to the chemical structure. Prior work from this group involved the development of a random forest model for predicting the amenability of 5517 unique chemical structures to liquid chromatography-mass spectrometry (LC-MS). This work improves the interpretability of the group's prior model of the same endpoint, as well as integrating 1348 more data points across negative and positive ionization modes. We enhance interpretability by feature engineering, a machine learning practice that reduces the input dimensionality while attempting to preserve performance statistics. We emphasize the importance of interpretable machine learning models within the context of building confidence in NTA identification. The novel data were curated by the labeling of compounds as amenable or unamenable by expert curators, resulting in an enhanced set of chemical compounds to expand the applicability domain of the prior model. The balanced accuracy benchmark of the newly developed model is comparable to performance previously reported (mean CV BA is 0.84 vs. 0.82 in positive mode, and 0.85 vs. 0.82 in negative mode), while on a novel external set, derived from this work's data, the Matthews correlation coefficients (MCC) for the novel models are 0.66 and 0.68 for positive and negative mode, respectively. Our group's prior published models scored MCC of 0.55 and 0.54 on the same external sets. This demonstrates appreciable improvement over the chemical space captured by the expanded dataset. This work forms part of our ongoing efforts to develop models with higher interpretability and higher performance to support NTA efforts.

An automated and high-throughput data processing workflow for PFAS identification in biota by direct infusion ultra-high resolution mass spectrometry.

The increasing recognition of the health impacts from human exposure to per- and polyfluorinated alkyl substances (PFAS) has surged the need for sophisticated analytical techniques and advanced data analyses, especially for assessing exposure by food of animal origin. Despite the existence of nearly 15,000 PFAS listed in the CompTox chemicals dashboard by the US Environmental Protection Agency, conventional monitoring and suspect screening methods often fall short, covering only a fraction of these substances. This study introduces an innovative automated data processing workflow, named PFlow, for identifying PFAS in environmental samples using direct infusion Fourier transform ion cyclotron resonance mass spectrometry (DI-FT-ICR MS). PFlow's validation on a bream liver sample, representative of low-concentration biota, involves data pre-processing, annotation of PFAS based on their precursor masses, and verification through isotopologues. Notably, PFlow annotated 17 PFAS absent in the comprehensive targeted approach and tentatively identified an additional 53 compounds, thereby demonstrating its efficiency in enhancing PFAS detection coverage. From an initial dataset of 30,332 distinct m/z values, PFlow thoroughly narrowed down the candidates to 84 potential PFAS compounds, utilizing precise mass measurements and chemical logic criteria, underscoring its potential in advancing our understanding of PFAS prevalence and of human exposure.

Critical review on in silico methods for structural annotation of chemicals detected with LC/HRMS non-targeted screening.

Non-targeted screening with liquid chromatography coupled to high-resolution mass spectrometry (LC/HRMS) is increasingly leveraging in silico methods, including machine learning, to obtain candidate structures for structural annotation of LC/HRMS features and their further prioritization. Candidate structures are commonly retrieved based on the tandem mass spectral information either from spectral or structural databases; however, the vast majority of the detected LC/HRMS features remain unannotated, constituting what we refer to as a part of the unknown chemical space. Recently, the exploration of this chemical space has become accessible through generative models. Furthermore, the evaluation of the candidate structures benefits from the complementary empirical analytical information such as retention time, collision cross section values, and ionization type. In this critical review, we provide an overview of the current approaches for retrieving and prioritizing candidate structures. These approaches come with their own set of advantages and limitations, as we showcase in the example of structural annotation of ten known and ten unknown LC/HRMS features. We emphasize that these limitations stem from both experimental and computational considerations. Finally, we highlight three key considerations for the future development of in silico methods.

Comparison of high-resolution mass spectrometry acquisition methods for the simultaneous quantification and identification of per- and polyfluoroalkyl substances (PFAS).

Simultaneous identification and quantification of per- and polyfluoroalkyl substances (PFAS) were evaluated for three quadrupole time-of-flight mass spectrometry (QTOF) acquisition methods. The acquisition methods investigated were MS-Only, all ion fragmentation (All-Ions), and automated tandem mass spectrometry (Auto-MS/MS). Target analytes were the 25 PFAS of US EPA Method 533 and the acquisition methods were evaluated by analyte response, limit of quantification (LOQ), accuracy, precision, and target-suspect screening identification limit (IL). PFAS LOQs were consistent across acquisition methods, with individual PFAS LOQs within an order of magnitude. The mean and range for MS-Only, All-Ions, and Auto-MS/MS are 1.3 (0.34-5.1), 2.1 (0.49-5.1), and 1.5 (0.20-5.1) pg on column. For fast data processing and tentative identification with lower confidence, MS-Only is recommended; however, this can lead to false-positives. Where high-confidence identification, structural characterisation, and quantification are desired, Auto-MS/MS is recommended; however, cycle time should be considered where many compounds are anticipated to be present. For comprehensive screening workflows and sample archiving, All-Ions is recommended, facilitating both quantification and retrospective analysis. This study validated HRMS acquisition approaches for quantification (based upon precursor data) and exploration of identification workflows for a range of PFAS compounds.

Exploring the hidden chemical landscape: Non-target and suspect screening analysis for investigating solid waste-associated environments.

Solid waste is an inevitable consequence of urbanization. It can be safely managed in municipal landfills and processing plants for volume reduction or material reuse, including organic solid waste. However, solid waste can also be discarded in (un-)authorized dumping sites or inadvertently released into the environment. Legacy and emerging contaminants have the potential to leach from solid waste, making it a significant pathway to the environment. Non-target screening (NTS) and suspect screening analysis (SSA) have become helpful tools in environmental science for the simultaneous analysis of a wide range of chemical compounds. However, the application of these analytical approaches to environmental samples related to Raw or Processed Solid Waste (RPSW) has been largely neglected so far. This perspective review examines the potential and policy relevance of NTS and SSA applied to waste-related samples (liquid, gaseous and solid). It addresses the hurdles associated with the chemical safety of solid waste accumulation, processing, and reuse, and the need for landfill traceability, as well as effectiveness of leachate treatments. We reviewed the current applications of NTS and SSA to environmental samples of RPSW, as well as the potential adaptation of NTS and SSA techniques from related fields, such as oilfield and metabolomics, to the solid waste domain. Despite the ongoing technical challenges, this review highlights the significant potential for the implementation of NTS and SSA approaches in solid waste management and related scientific fields and provides support and guidance to the regulatory authorities.

Target and suspect screening approaches for the identification of emerging and other contaminants in fish feeds using high resolution mass spectrometry.

Fish feed is essential in aquaculture fish production because, along with beneficial nutrients and components, many suspected compounds can be transferred to fish and ultimately to humans. In this context, a comprehensive analysis was conducted to monitor various pesticides and pharmaceutical compounds in aquaculture fish feed through target analysis and many other groups of chemicals via suspect screening approaches. In this study, the QuEChERS extraction method was optimized, validated, and applied to fifty-four fish feed samples collected from different production batches. This was followed by liquid chromatography-high-resolution linear ion trap/Orbitrap mass spectrometry (LC-HR-IT/Orbitrap-MS) for targeted and suspect screening purposes. In general, pesticides provided satisfactory recoveries (70-105.5 %), with quantification limits lower than 5 ng g-1, whereas pharmaceuticals displayed recoveries ranging from 70.5 to 120.2 %, with quantification limits below 25 ng g-1. In addition, the matrix effects and measurement uncertainty were assessed to provide more accurate and high-confidence results. Pirimiphos-methyl was detected and quantified in 20 of 54 fish feed samples (37 %) at concentrations <77 ng g-1. Finally, suspect screening revealed the occurrence of 10 mycotoxins (e.g., citrinin, aflatoxin G2, zearalenone, and alternariol), two pesticides excluding the target pesticides (tebuconazole and fenazaquin), perfluorooctane sulfonic acid (PFOS) in almost 2 % of the samples, and ethoxyquin (antioxidant), with 12 of its Transformation Products (TPs). Finally, suspect analysis incorporated in routine analyses have proven to have great potential for complete monitoring.

Non-target analysis of Danish wastewater treatment plant effluent: Statistical analysis of chemical fingerprinting as a step toward a future monitoring tool.

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.

First Insight into the Formation of In Vivo Transformation Products of 2-Ethylhexyl diphenyl phosphate in Zebrafish and Prediction of Their Potential Toxicities.

As a frequently detected organophosphorus flame retardant in the environment, 2-ethylhexyl diphenyl phosphate (EHDPHP) is vulnerable to biotransformation, while the transformation mechanisms and potential toxicities of its transformation products remain unclear. In the present study, in vivo transformation products of EHDPHP in exposed zebrafish for 21d were analyzed by suspect screening and identified by mass spectrometry. Fifteen metabolites were identified, including 10 phase I and 5 phase II products with monohydroxylated products being primary, among which 5-OH-EHDPHP was the most predominant. Two sulfation products and one terminal desaturation metabolite of EHDPHP were reported for the first time. A density functional calculation coupled with molecular docking disclosed that the specific conformation of EHDPHP docked in the protein pockets favored the primary formation of 5-OH-EHDPHP, which was fortified to be a more suitable biomarker of EHDPHP exposure. The in vitro tests suggested that EHDPHP transformation took place not only in liver but also in intestine, where gut microbes played an important role. Due to lack of standards, in silico toxicity prediction combined with molecular docking indicated that several metabolites potentially cause higher toxicities than EHDPHP. The results provide deep insight into the potential health risks due to specific in vivo transformation of EHDPHP.

Enantiospecific Uptake and Depuration Kinetics of Chiral Metoprolol and Venlafaxine in Marine Medaka (Oryzias melastigma): Tissue Distribution and Metabolite Formation.

The increasing use of chiral pharmaceuticals has led to their widespread presence in the environment. However, their toxicokinetics have rarely been reported. Therefore, the tissue-specific uptake and depuration kinetics of two pairs of pharmaceutical enantiomers, S-(-)-metoprolol versus R-(+)-metoprolol and S-(+)-venlafaxine versus R-(-)-venlafaxine, were studied in marine medaka (Oryzias melastigma) during a 28-day exposure and 14-day clearance period. The toxicokinetics of the studied pharmaceuticals, including uptake and depuration rate constants, depuration half-life (t1/2), and bioconcentration factor (BCF), were reported for the first time. The whole-fish results demonstrated a higher S- than R-venlafaxine bioaccumulation potential, whereas no significant difference was observed between S- and R-metoprolol. O-desmethyl-metoprolol (ODM) and α-hydroxy-metoprolol (AHM) were the main metoprolol metabolites identified by suspect screening, and the ratios of ODM to AHM were 3.08 and 1.35 for S- and R-metoprolol, respectively. N,O-Didesmethyl-venlafaxine (NODDV) and N-desmethyl-venlafaxine (NDV) were the main venlafaxine metabolites, and the ratios of NODDV to NDV were 1.55 and 0.73 for S- and R-venlafaxine, respectively. The highest tissue-specific BCFs of the four enantiomers were all found in the eyes, meriting in-depth investigation.

A Critical Review on the Opportunity to Use Placenta and Innovative Biomonitoring Methods to Characterize the Prenatal Chemical Exposome.

Adverse effects associated with chemical exposures during pregnancy include several developmental and reproductive disorders. However, considering the tens of thousands of chemicals present on the market, the effects of chemical mixtures on the developing fetus is still likely underestimated. In this critical review, we discuss the potential to apply innovative biomonitoring methods using high-resolution mass spectrometry (HRMS) on placenta to improve the monitoring of chemical exposure during pregnancy. The physiology of the placenta and its relevance as a matrix for monitoring chemical exposures and their effects on fetal health is first outlined. We then identify several key parameters that require further investigations before placenta can be used for large-scale monitoring in a robust manner. Most critical is the need for standardization of placental sampling. Placenta is a highly heterogeneous organ, and knowledge of the intraplacenta variability of chemical composition is required to ensure unbiased and robust interindividual comparisons. Other important variables include the time of collection, the sex of the fetus, and mode of delivery. Finally, we discuss the first applications of HRMS methods on the placenta to decipher the chemical exposome and describe how the use of placenta can complement biofluids collected on the mother or the fetus.