Innovative analytical methodologies for characterizing chemical exposure with a view to next-generation risk assessment.

The chemical burden on the environment and human population is increasing. Consequently, regulatory risk assessment must keep pace to manage, reduce, and prevent adverse impacts on human and environmental health associated with hazardous chemicals. Surveillance of chemicals of known, emerging, or potential future concern, entering the environment-food-human continuum is needed to document the reality of risks posed by chemicals on ecosystem and human health from a one health perspective, feed into early warning systems and support public policies for exposure mitigation provisions and safe and sustainable by design strategies. The use of less-conventional sampling strategies and integration of full-scan, high-resolution mass spectrometry and effect-directed analysis in environmental and human monitoring programmes have the potential to enhance the screening and identification of a wider range of chemicals of known, emerging or potential future concern. Here, we outline the key needs and recommendations identified within the European Partnership for Assessment of Risks from Chemicals (PARC) project for leveraging these innovative methodologies to support the development of next-generation chemical risk assessment.

Contaminants of emerging concern in urine: a review of analytical methods for determining diisocyanates, benzotriazoles, benzothiazoles, 4-methylbenzylidene camphor, isothiazolinones, fragrances, and non-phthalate plasticizers.

Human biomonitoring (HBM) frameworks assess human exposure to hazardous chemicals. In this review, we discuss and summarize sample preparation procedures and analytical methodology for six groups of chemicals of emerging concern (CECs), namely diisocyanates, benzotriazoles, benzothiazoles, 4-methylbenzylidene camphor, isothiazolinones, fragrances, and non-phthalate plasticizers, which are increasingly detected in urine, however, are not yet widely included in HBM schemes, despite posing a risk to human health. The sample preparation procedures depend largely on the chemical group; however, solid-phase extraction (SPE) is most often used due to the minimized sample handling, lower sample volume, and generally achieving lower limits of quantification (LOQs) compared to other extraction techniques. In terms of sample analysis, LC-based methods generally achieve lower limits of quantification (LOQs) compared to GC-based methods for the selected six groups of chemicals owing to their broader chemical coverage. In conclusion, since these chemicals are expected to be more frequently included in future HBM studies, it becomes evident that there is a pressing need for rigorous quality assurance programs to ensure better comparability of data. These programs should include the reporting of measurement uncertainty and facilitate inter-laboratory comparisons among the reporting laboratories. In addition, high-resolution mass spectrometry should be more commonly employed to enhance the specificity and selectivity of the applied analytical methodology since it is underrepresented in HBM. Furthermore, due to the scarcity of data on the levels of these CECs in urine, large population HBM studies are necessary to gain a deeper understanding of the associated risks.

GC-EI-MS datasets of trimethylsilyl (TMS) and tert-butyl dimethyl silyl (TBDMS) derivatives for development of machine learning-based compound identification approaches.

In the field of environment and health studies, recent trends have focused on the identification of contaminants of emerging concern (CEC). This is a complex, challenging task, as resources, such as compound databases (DBs) and mass spectral libraries (MSLs) concerning these compounds are very poor. This is particularly true for semi polar organic contaminants that have to be derivatized prior to gas chromatography-mass spectrometry (GC-MS) analysis with electron impact ionization (EI), for which it is barely possible to find any records. In particular, there is a severe lack of datasets of GC-EI-MS spectra generated and made publicly available for the purpose of development, validation and performance evaluation of cheminformatics-assisted compound structure identification (CSI) approaches, including novel cutting-edge machine learning (ML)-based approaches [1]. We set out to fill this gap and support the machine learning-assisted compound identification, thus aiding cheminformatics-assisted identification of silylated derivatives in GC-MS laboratories working in the field of environment and health. To this end, we have generated 12 datasets of GC-EI-MS spectra, six of which contain GC-EI-MS spectra of trimethylsilyl (TMS) and six GC-EI-MS spectra of tert-butyldimethylsilyl (TBDMS) derivatives. Four of these datasets, named testing datasets, contain mass spectra acquired by the authors. They are available in full, together with corresponding metadata. Eight datasets, named training datasets, were derived from mass spectra in the NIST 17 Mass Spectral Library. For these, we have only made the metadata publicly available, due to licensing reasons. For each type of derivative, two testing datasets are generated by acquiring and processing GC-EI-MS spectra, such that they include raw and processed GC-EI-MS spectra of TMS and TBDMS derivatives of CECs, along with their corresponding metadata. The metadata contains IUPAC name, exact mass, molecular formula, InChI, InChIKey, SMILES and PubChemID, of each CEC and CEC-TMS or CEC-TBDMS derivative, where available. Eight GC-EI-MS training datasets are generated by using the National Institute of Standards and Technology (NIST)/U.S. Environmental Protection Agency (EPA)/National Institute of Health (NIH) 17 Mass Spectral Library. For each derivative type (TMS and TBDMS), four datasets are given, each corresponding to an original dataset obtained from NIST/EPA/NIH 17 and three variants thereof, obtained after each of the filtering steps of the procedure described below. Only the metadata about the training datasets are available, describing the corresponding NIST/EPA/NIH 17 entires: These include the compound name, CAS Registry number, InChIKey, exact mass, Mw, NIST number and ID number. The datasets we present here were used to train and test predictive models for identification of silylated derivatives built with ML approaches [4]. The models were built by using data curated from the NIST Mass Spectral Library 17 [2] and the machine learning approach of CSI:Output Kernel Regression (CSI:OKR) [2]. Data from the NIST Mass Spectral Library 17 are commercially available from the National Institute of Standards and Technology (NIST)/U.S. Environmental Protection Agency (EPA)/National Institute of Health (NIH) and thus cannot be made publicly available. This highlights the need for publicly available GC-EI-MS spectra, which we address by releasing in full the four testing datasets.

An effective validation of analytical method for determination of a polar complexing agent: the illustrative case of cytotoxic bleomycin.

The effectiveness of highly polar agents in cancer treatment is well recognized, but their physicochemical properties make their analytical determination a demanding task. Their analysis requires peculiar sample preparation and chromatographic separation, which heavily impacts the precision of such an analytical method. As a case study, we chose a polar cytotoxic bleomycin, which is a mixture of complexing congeners with relatively high molecular mass, a fact that creates an added challenge in regard to its detection via electrospray mass spectrometry. These issues combined lead to a deprived method performance, so the aim of this study is manifold, i.e., to optimize, validate, and establish quality performance measures for determination of bleomycin in pharmaceutical and biological specimens. Quantification of bleomycin is done at diametrically different concentration levels: at the concentrations relevant for analysis of pharmaceutical dosage forms it is based on a direct reversed-phase HPLC-UV detection, involving minimum sample pretreatment. On the contrary, analysis of bleomycin in biological specimens requires phospholipid removal and protein precipitation followed by HILIC chromatography with MS/MS detection of bleomycin A2 and B2 copper complexes being the predominant species. This study further attempts to solve the traceability issue in the absence of certified reference standards, determines measurement uncertainty, investigates BLM stability and method performance characteristics, and, last but not least, provides an explanatory example of how a method quality assurance procedure should be established in case of an exceedingly complex analytical method.

Aerobic degradation of tetramethyl bisphenol F (TMBPF) with activated sludge: Kinetics and biotransformation products.

This study investigated the bio-degradation kinetics of tetramethyl bisphenol F (TMBPF), a non-estrogenic alternative to bisphenol A (BPA). Batch biotransformation experiments were performed whereby samples were inoculated with activated sludge and analysed using liquid chromatography-Orbitrap-tandem mass spectrometry (LC-Orbitrap-MS) utilising two non-targeted workflows (commercial and freely available online) for biotransformation products (BTP) identification. The degradation of TMBPF followed single first-order reaction kinetics and depended on the initial concentration (ci) with faster degradation -kt = 0.16, (half-life = 4.4 days) at lower concentrations ci = 0.1 mg L-1, compared with -kt = 0.02 (half-live = 36.4 days) at ci = 10.0 mg L-1. After 18 days, only 8% of the original TMBPF remained at the lowest tested concentration (0.1 mg L-1). Twelve BTPs were identified, three of which were workflow and one condition-specific. The highest relative quantities of BTPs were observed in nutrient-mineral and mineral media after ten days, while after 14 days, 36 and 31% of TMBPF (ci = 1 mg L-1) remained in the nutrient-mineral and mineral media, respectively. Also, the kinetics of TMBPF and its BTPs were the same with and without an additional carbon source. A newly proposed biodegradation pathway for TMBPF involves cleavage of the methylene bridge, hydroxylation with further oxidation, sulphation, nitrification, nitro reduction with further oxidation, acetylation, and glycine conjugation, providing a deeper insight into the fate of TMBPF during biological wastewater treatment.

Exposure of children and adolescents from Northeastern Slovenia to per- and polyfluoroalkyl substances.

Per- and polyfluoroalkyl substances (PFAS) are of high concern for the environment, wildlife, and human health due to their persistence and potential to cause adverse health effects. Despite political measures to restrict the production and distribution of PFAS and to limit the exposure of populations, PFAS can be measured at commonly high detection frequencies in human samples. Thus, this pilot study aimed to determine the serum concentrations of PFPA, PFHpA, PFOA, PFNA, PFDA, PFUnDA, PFHxS, PFHpS, PFOS, PFHxA, PFDoDA, and PFBS in 113 girls and 112 boys (age 7-10 and 12-15) from Northeastern Slovenia - a rural area characterized by agricultural activities - and to identify potential sources of exposure using questionnaire data. PFAS were analysed by liquid chromatography coupled to mass spectrometry after phospholipid removal. 9 out of 12 analytes were detected at detection frequencies above 30%, with the highest geometric means (GM) being observed for PFOS (GM 1.9 ng/mL) > PFOA (GM 1.0 ng/mL) > PFHxS (GM 0.3 ng/mL) = PFNA (GM 0.3 ng/mL). We identified the participants' socio-economic status, age, sex, sampling region, public water supply, and the consumption of fish and seafood, cereals, and locally produced fruits, vegetables, and mushrooms as the predominant determinants of exposure. Furthermore, we compared our results with the serum and plasma concentrations reported for similar age groups in other studies and concluded that PFAS exposure in this highly agricultural area in Slovenia is notably low. This is the first study systematic HBM study of PFAS exposure in Slovenia, although it was conducted on a limited number of participants representative of rural and agricultural areas, it represents a good basis for upgrading the approach to a nationwide HBM study.

Current exposure to phthalates and DINCH in European children and adolescents - Results from the HBM4EU Aligned Studies 2014 to 2021.

Phthalates are mainly used as plasticizers for polyvinyl chloride (PVC). Exposure to several phthalates is associated with different adverse effects most prominently on the development of reproductive functions. The HBM4EU Aligned Studies (2014-2021) have investigated current European exposure to ten phthalates (DEP, BBzP, DiBP, DnBP, DCHP, DnPeP, DEHP, DiNP, DiDP, DnOP) and the substitute DINCH to answer the open policy relevant questions which were defined by HBM4EU partner countries and EU institutions as the starting point of the programme. The exposure dataset includes ∼5,600 children (6-11 years) and adolescents (12-18 years) from up to 12 countries per age group and covering the North, East, South and West European regions. Study data from participating studies were harmonised with respect to sample size and selection of participants, selection of biomarkers, and quality and comparability of analytical results to provide a comparable perspective of European exposure. Phthalate and DINCH exposure were deduced from urinary excretions of metabolites, where concentrations were expressed as their key descriptor geometric mean (GM) and 95th percentile (P95). This study aims at reporting current exposure levels and differences in these between European studies and regions, as well as comparisons to human biomonitoring guidance values (HBM-GVs). GMs for children were highest for ∑DEHP metabolites (33.6 µg/L), MiBP (26.6 µg/L), and MEP (24.4 µg/L) and lowest for∑DiDP metabolites (1.91 µg/L) and ∑DINCH metabolites (3.57 µg/L). In adolescents highest GMs were found for MEP (43.3 µg/L), ∑DEHP metabolites (28.8 µg/L), and MiBP (25.6 µg/L) and lowest for ∑DiDP metabolites (= 2.02 µg/L) and ∑DINCH metabolites (2.51 µg/L). In addition, GMs and P95 stratified by European region, sex, household education level, and degree of urbanization are presented. Differences in average biomarker concentrations between sampling sites (data collections) ranged from factor 2 to 9. Compared to the European average, children in the sampling sites OCC (Denmark), InAirQ (Hungary), and SPECIMEn (The Netherlands) had the lowest concentrations across all metabolites and ESTEBAN (France), NAC II (Italy), and CROME (Greece) the highest. For adolescents, comparably higher metabolite concentrations were found in NEB II (Norway), PCB cohort (Slovakia), and ESTEBAN (France), and lower concentrations in POLAES (Poland), FLEHS IV (Belgium), and GerES V-sub (Germany). Multivariate analyses (Survey Generalized Linear Models) indicate compound-specific differences in average metabolite concentrations between the four European regions. Comparison of individual levels with HBM-GVs revealed highest rates of exceedances for DnBP and DiBP, with up to 3 and 5%, respectively, in children and adolescents. No exceedances were observed for DEP and DINCH. With our results we provide current, detailed, and comparable data on exposure to phthalates in children and - for the first time - in adolescents, and - for the first time - on DINCH in children and adolescents of all four regions of Europe which are particularly suited to inform exposure and risk assessment and answer open policy relevant questions.

Removal of residues of psychoactive substances during wastewater treatment, their occurrence in receiving river waters and environmental risk assessment.

Continuous consumption combined with incomplete removal during wastewater treatment means residues of psychoactive substances (licit drugs, medications of abuse and illicit drugs) are constantly introduced into the aquatic environment, where they have the potential to affect non-target organisms. In this study, 17 drug residues of psychoactive substances were determined in wastewater influent, effluent and in receiving rivers of six Slovene municipal wastewater treatment plants employing different treatment technologies. Variations in removal efficiencies (REs) during spring, summer and winter were explored, and ecotoxic effects were evaluated using in silico (Ecological Structure-Activity Relationships software-ECOSAR) and in vivo (algal growth inhibition test) methods. Drug residues were detected in influent and effluent in the ng/L to µg/L range. In receiving rivers, biomarkers were in the ng/L range, and there was good agreement between measured and predicted concentrations. On average, REs were highest for nicotine, 11-nor-9-carboxy-∆9-tetrahydrocannabinol (THC-COOH), cocaine residues, and amphetamine (>90 %) and lowest for methadone residues (<30 %). REs were comparable between treatments involving activated sludge and membrane bioreactors, while the moving biofilm bed reactor (MBBR) removed cotinine, cocaine, and benzoylecgonine to a lesser extent. Accordingly, higher levels of nicotine and cocaine residues were detected in river water receiving MBBR discharge. Although there were seasonal variations in REs and levels of drug residues in receiving rivers, no general pattern could be observed. No significant inhibition of algal growth (Chlamydomonas reinhardtii) was observed for the tested compounds (1 mg/L) during 72 h and 240 h of exposure, although effects on aquatic plants were predicted in silico. In addition, environmental risk assessment revealed that levels of nicotine, methadone, 2-ethylidene-1,5-dimethyl-3,3-diphenylpyrrolidine (EDDP), morphine, and 3,4-methylenedioxymethamphetamine (MDMA) pose a risk to aquatic organisms. Since nicotine and EDDP can have acute and chronic effects, the authors support regular monitoring of receiving surface waters, followed up by regulatory actions.

Cross-sectional associations between exposure to per- and polyfluoroalkyl substances and body mass index among European teenagers in the HBM4EU aligned studies.

Per- and polyfluoroalkyl substances (PFAS) are widespread pollutants that may impact youth adiposity patterns. We investigated cross-sectional associations between PFAS and body mass index (BMI) in teenagers/adolescents across nine European countries within the Human Biomonitoring for Europe (HBM4EU) initiative. We used data from 1957 teenagers (12-18 yrs) that were part of the HBM4EU aligned studies, consisting of nine HBM studies (NEBII, Norway; Riksmaten Adolescents 2016-17, Sweden; PCB cohort (follow-up), Slovakia; SLO CRP, Slovenia; CROME, Greece; BEA, Spain; ESTEBAN, France; FLEHS IV, Belgium; GerES V-sub, Germany). Twelve PFAS were measured in blood, whilst weight and height were measured by field nurse/physician or self-reported in questionnaires. We assessed associations between PFAS and age- and sex-adjusted BMI z-scores using linear and logistic regression adjusted for potential confounders. Random-effects meta-analysis and mixed effects models were used to pool studies. We assessed mixture effects using molar sums of exposure biomarkers with toxicological/structural similarities and quantile g-computation. In all studies, the highest concentrations of PFAS were PFOS (medians ranging from 1.34 to 2.79 µg/L). There was a tendency for negative associations with BMI z-scores for all PFAS (except for PFHxS and PFHpS), which was borderline significant for the molar sum of [PFOA and PFNA] and significant for single PFOA [ß-coefficient (95% CI) per interquartile range fold change = -0.06 (-0.17, 0.00) and -0.08 (-0.15, -0.01), respectively]. Mixture assessment indicated similar negative associations of the total mixture of [PFOA, PFNA, PFHxS and PFOS] with BMI z-score, but not all compounds showed associations in the same direction: whilst [PFOA, PFNA and PFOS] were negatively associated, [PFHxS] associated positively with BMI z-score. Our results indicated a tendency for associations of relatively low PFAS concentrations with lower BMI in European teenagers. More prospective research is needed to investigate this potential relationship and its implications for health later in life.

Machine learning for identification of silylated derivatives from mass spectra.

MOTIVATION: Compound structure identification is using increasingly more sophisticated computational tools, among which machine learning tools are a recent addition that quickly gains in importance. These tools, of which the method titled Compound Structure Identification:Input Output Kernel Regression (CSI:IOKR) is an excellent example, have been used to elucidate compound structure from mass spectral (MS) data with significant accuracy, confidence and speed. They have, however, largely focused on data coming from liquid chromatography coupled to tandem mass spectrometry (LC-MS). Gas chromatography coupled to mass spectrometry (GC-MS) is an alternative which offers several advantages as compared to LC-MS, including higher data reproducibility. Of special importance is the substantial compound coverage offered by GC-MS, further expanded by derivatization procedures, such as silylation, which can improve the volatility, thermal stability and chromatographic peak shape of semi-volatile analytes. Despite these advantages and the increasing size of compound databases and MS libraries, GC-MS data have not yet been used by machine learning approaches to compound structure identification. RESULTS: This study presents a successful application of the CSI:IOKR machine learning method for the identification of environmental contaminants from GC-MS spectra. We use CSI:IOKR as an alternative to exhaustive search of MS libraries, independent of instrumental platform and data processing software. We use a comprehensive dataset of GC-MS spectra of trimethylsilyl derivatives and their molecular structures, derived from a large commercially available MS library, to train a model that maps between spectra and molecular structures. We test the learned model on a different dataset of GC-MS spectra of trimethylsilyl derivatives of environmental contaminants, generated in-house and made publicly available. The results show that 37% (resp. 50%) of the tested compounds are correctly ranked among the top 10 (resp. 20) candidate compounds suggested by the model. Even though spectral comparisons with reference standards or de novo structural elucidations are neccessary to validate the predictions, machine learning provides efficient candidate prioritization and reduction of the time spent for compound annotation.

Suspect and non-targeted screening-based human biomonitoring identified 74 biomarkers of exposure in urine of Slovenian children.

Human exposure to organic contaminants is widespread. Many of these contaminants show adverse health effects on human population. Human biomonitoring (HBM) follows the levels and the distribution of biomarkers of exposure (BoE), but it is usually done in a targeted manner. Suspect and non-targeted screening (SS/NTS) tend to find BoE in an agnostic way, without preselection of compounds, and include finding evidence of exposure to predicted, unpredicted known and unknown chemicals. This study describes the application of high-resolution mass spectrometry (HRMS)-based SS/NTS workflow for revealing organic contaminants in urine of a cohort of 200 children from Slovenia, aged 6-9 years. The children originated from two regions, urban and rural, and the latter were sampled in two time periods, summer and winter. We tentatively identified 74 BoE at the confidence levels of 2 and 3. These BoE belong to several classes of pharmaceuticals, personal care products, plasticizers and plastic related products, volatile organic compounds, nicotine, caffeine and pesticides. The risk of three pesticides, atrazine, amitraz and diazinon is of particular concern since their use was limited in the EU. Among BoE we tentatively identified compounds that have not yet been monitored in HBM schemes and demonstrate limited exposure data, such as bisphenol G, polyethylene glycols and their ethers. Furthermore, 7 compounds with unknown use and sources of exposure were tentatively identified, either indicating the entry of new chemicals into the market, or their metabolites and transformation products. Interestingly, several BoE showed location and time dependency. Globally, this study presents high-throughput approach to SS/NTS for HBM. The results shed a light on the exposure of Slovenian children and raise questions on potential adverse health effects of such mixtures on this vulnerable population.

Cardiopulmonary Effects and Pharmacokinetics of Dexmedetomidine Used as an Adjunctive Analgesic to Regional Anesthesia of the Oral Cavity with Levobupivacaine in Dogs.

This study investigated the cardiopulmonary effects and pharmacokinetics of dexmedetomidine (DEX) used as an adjunctive analgesic for regional anesthesia of the oral cavity with levobupivacaine in anesthetized dogs. Forty dogs were randomly assigned to four groups of 10 dogs. All dogs received levobupivacaine (4 blocks) with DEX IO (infraorbital block, n = 10) or IA (inferior alveolar block, n = 10) or placebo (PLC; n = 10) or DEX (n = 10) was injected intravenously (IV) after administration of levobupivacaine. The dose of DEX was always 0.5 µg/kg. Cardiopulmonary parameters were recorded, and blood was drawn for the quantification of DEX in plasma using LC-MS/MS. Heart rate was lower in all LB + DEX groups, while mean arterial pressure (MAP) was higher in the LB + DEX IV and LB + DEX IA groups compared to the LB + PLC IV group. Compared to DEX IV, IO and IA administration resulted in lower MAP up to 2 min after application. Absorption of DEX was faster at IO administration (Cmax and Tmax were 0.47 ± 0.08 ng/mL and 7.22 ± 1.28 min and 0.76 ± 0.09 ng/mL and 7.50 ± 1.63 min for the IO and IA block, respectively). The IA administration resulted in better bioavailability and faster elimination (t1/2 was 63.44 ± 24.15 min and 23.78 ± 3.78 min for the IO and IA block, respectively). Perineural administration of DEX may be preferable because of the less pronounced cardiovascular response compared to IV administration.

Degradation of bisphenol A and S in wastewater during cold atmospheric pressure plasma treatment.

Developing novel, fast and efficient ecologically benign processes for removing organic contaminants is important for the continued development of water treatment. For this reason, this study investigates the implementation of Cold Atmospheric pressure Plasma (CAP) generated in ambient air as an efficient tool for the removal of Bisphenol A (BPA) and Bisphenol S (BPS)-known endocrine disrupting compounds in water and wastewater, by monitoring degradation kinetics and its transformation products. The highest removal efficiencies of BPA (>98%) and BPS (>70%) were obtained after 480 s of CAP exposure. A pseudo-first-order kinetic revealed that BPA (-kt = 4.4 ̶ 9.0 ms-1) degrades faster than BPS (-kt = 0.4 ̶ 2.4 ms-1) and that the degradation is also time- and CAP power-dependent, while the initial concentration or matrix type had a negligible effect. This study also tentatively identified three previously reported and one novel transformation product of BPA and four novel transformation products of BPS. Their postulated structures suggested similar breakdown mechanisms, i.e., hydroxylation followed by ring cleavage. The results demonstrate that CAP technology is an effective process for the degradation of both BPA and BPS without the need for additional chemicals, indicating that CAP is a promising technology for water and wastewater remediation worthy of further investigation and optimization.

LC-HRMS based method for suspect/non-targeted screening for biomarkers of chemical exposure in human urine.

Every day we are exposed to a cocktail of anthropogenic compounds many of which are biologically active and capable of inducing negative effects. The simplest way to monitor contaminants in a population is via human biomonitoring (HBM), however conventional targeted approaches require foreknowledge of chemicals of concern, often have compound specific extractions and provide information only for those compounds. This study developed an extraction process for human biomarkers of interest (BoE) in urine that is less compound specific. Combining this with an ultra-high resolution mass spectrometer capable of operating in full scan, and a suspect and non-targeted analysis (SS/NTA) approach, this method provides a more holistic characterization of human exposure. Sample preparation development was based on enzymatically hydrolysed urine spiked with 34 native standards and extracted by solid-phase extraction (SPE). HRMS data was processed by MzMine2 and 80% of standards were identified in the final data matrix using typical NTA data processing procedures.

UHPLC-HRMS data from non-targeted screening for biotransformation products of cytostatic drug imatinib.

Imatinib is a selective tyrosine kinase inhibitor used to treat chronic myeloid leukemia. It enters the environment by excretion from the body through urine and feces and is transferred with wastewater to a wastewater treatment plant. There, it can be degraded by activated sludge, forming a number of biotransformation products. Presence of imatinib and its potential transformation products in the environment can impose a high risk to aquatic organisms and human health, therefore it is important to obtain knowledge of its environmental fate. The data presented here is a result of a simulated biodegradation of imatinib at two levels of activated sludge using a batch biotransformation setup, with and without carbon source. The data was acquired with UHPLC-HRMS/MS and processed by MzMine2.36 [1]. The dataset presents a table of [M+H]+ features with retention times and corresponding MS/MS data. With development of new data mining tools this data can be used to identify new transformation products of imatinib and with it fully understand its environmental fate and the risk associated with its presence in the environment.

The pharmacokinetics of levobupivacaine 0.5% after infraorbital or inferior alveolar block in anesthetized dogs.

Introduction: Data are lacking on the pharmacokinetic profile and safety of levobupivacaine (LB) used for regional anesthesia of the maxilla and mandibles in dogs. Methods: Infraorbital block (n = 10), inferior alveolar block (n = 10) or both infraorbital and inferior alveolar blocks (n = 10) were administered to dogs undergoing dental surgery under isoflurane anesthesia. The dose of LB was calculated as 0.11 ml/kg2/3 for the infraorbital block and 0.18 ml/kg2/3 for the inferior alveolar block. Blood samples were collected before and immediately after administration of the oral blocks, and 3, 4, 7, 12, 17, 32, 47, 62, 92, and 122 min thereafter. Quantification of LB in plasma was performed by LC-MS/MS. Results and discussion: The results are presented as median and interquartile range. In dogs in which all four quadrants of the oral cavity were desensitized with LB, the C max was 1,335 (1,030-1,929) ng/ml, the T max was 7 (4-9.5) min, and the AUC(0 → 120) was 57,976 (44,954-96,224) ng min/ml. Plasma concentrations of LB were several times lower than the reported toxic concentrations, and no signs of cardiovascular depression or neurotoxicity were observed in any of the dogs, suggesting that the occurrence of severe adverse effects after administration of LB at the doses used in this study is unlikely.

Exposure of men and lactating women to environmental phenols, phthalates, and DINCH.

Phthalates and 1,2-Cyclohexane dicarboxylic acid diisononyl ester (DINCH), bisphenols (BPs), parabens (PBs), and triclosan (TCS) are high-production-volume chemicals of pseudo-persistence that are concerning for the environment and human health. This study aims to assess the exposure to 10 phthalates, DINCH, and environmental phenols (3 BPs, 7 PBs, and TCS) of Slovenian men (n = 548) and lactating primiparous women (n = 536). We observed urinary concentrations comparable to studies from other countries and significant differences among the sub-populations. In our study, men had significantly higher levels of phthalates, DINCH, and BPs, whereas the concentrations of PBs in urine were significantly higher in women. The most significant determinant of exposure was the area of residence and the year of sampling (2008-2014) that mirrors trends in the market. Participants from urban or industrialized sampling locations had higher levels of almost all monitored analytes compared to rural locations. In an attempt to assess the risk of the population, hazard quotient (HQ) values were calculated for individual compounds and the chemical mixture. Individual analytes do not seem to pose a risk to the studied population at current exposure levels, whereas the HQ value of the chemical mixture is near the threshold of 1 which would indicate a higher risk. We conclude that greater emphasis on the risk resulting from cumulative exposure to chemical mixtures and additional studies are needed to estimate the exposure of susceptible populations, such as children.

Assessment of susceptibility to phthalate and DINCH exposure through CYP and UGT single nucleotide polymorphisms.

Single nucleotide polymorphisms (SNPs) of cytochrome P450 (CYPs) and UDP-glucuronosyltransferase (UGTs) genes have been proposed to influence phthalates and 1,2-cyclo-hexanedicarboxylic acid diisononyl ester (DINCH) biotransformation but have not been investigated on a populational level. We investigated the role of SNPs in CYP2C9, CYP2C19, CYP2D6, UGT2B15, and UGT1A7 genes in the biotransformation of phthalates (DEHP, DEP, DiBP, DnBP, BBzP, DiNP, DidP) and DINCH by determining their urine metabolites. From the Slovenian study population of 274 men and 289 lactating primiparous women we obtained data on phthalate and DINCH urine metabolite levels (MEHP, 5OH-MEHP, 5oxo-MEHP, 5cx-MEPP, MEP, MiBP, MnBP, MBzP, cx-MINP, OH-MiDP, MCHP, MnPeP, MnOP, 5OH-MINCH, 5oxo-MINCH), SNP genotypes (rs1057910 = CYP2C9*3, rs1799853 = CYP2C9*2, rs4244285 = CYP2C19*2, rs12248560 = CYP2C19*17, rs3892097 = CYP2D6*4, rs1902023 = UGT2B15*2, and rs11692021 = UGT1A7*3) and questionnaires. Associations of SNPs with levels of metabolites and their ratios were assessed by multiple linear regression and ordinary logistic regression analyses. Significant associations were observed for CYP2C9*2, CYP2C9*3, CYP2C19*17, and UGT1A7*3 SNPs. The most pronounced was the influence of CYP2C9*2 and *3 on the reduced DEHP biotransformation, with lower levels of metabolites and their ratios in men and women. In contrast, carriers of CYP2C19*17 showed higher urine levels of DEHP metabolites in both genders, and in women also in higher DiNP, DiDP, and DINCH metabolite levels. The presence of UGT1A7*3 was associated with increased metabolite levels of DINCH in men and of DiBP and DBzP in women. Statistical models explained up to 27% of variability in metabolite levels or their ratios. Our observations confirm the effect of CYP2C9*2 and *3 SNPs towards reduced DEHP biotransformation. We show that CYP2C9*2, CYP2C9*3, CYP2C19*17, and UGT1A7*3 SNPs might represent biomarkers of susceptibility or resilience in phthalates and DINCH exposure that have been so far unrecognised.