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  • 1.
    Dracheva, Elena
    et al.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Norinder, Ulf
    Department of Computer and Systems Sciences, Stockholm University, Kista, Sweden.
    Rydén, Patrik
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Engelhardt, Josefin
    Department of Environmental Science, Stockholm University, Stockholm, Sweden.
    Weiss, Jana M.
    Department of Environmental Science, Stockholm University, Stockholm, Sweden.
    Andersson, Patrik L.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    In Silico Identification of Potential Thyroid Hormone System Disruptors among Chemicals in Human Serum and Chemicals with a High Exposure Index2022In: Environmental Science and Technology, ISSN 0013-936X, E-ISSN 1520-5851, Vol. 56, no 12, p. 8363-8372Article in journal (Refereed)
    Abstract [en]

    Data on toxic effects are at large missing the prevailing understanding of the risks of industrial chemicals. Thyroid hormone (TH) system disruption includes interferences of the life cycle of the thyroid hormones and may occur in various organs. In the current study, high-throughput screening data available for 14 putative molecular initiating events of adverse outcome pathways, related to disruption of the TH system, were used to develop 19 in silico models for identification of potential thyroid hormone system-disrupting chemicals. The conformal prediction framework with the underlying Random Forest was used as a wrapper for the models allowing for setting the desired confidence level and controlling the error rate of predictions. The trained models were then applied to two different databases: (i) an in-house database comprising xenobiotics identified in human blood and ii) currently used chemicals registered in the Swedish Product Register, which have been predicted to have a high exposure index to consumers. The application of these models showed that among currently used chemicals, fewer were overall predicted as active compared to chemicals identified in human blood. Chemicals of specific concern for TH disruption were identified from both databases based on their predicted activity.

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  • 2.
    Golosovskaia, Elena
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Development of in silico methods to aid chemical risk assessment: focusing on kinetic interactions in mixtures2024Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The environment and biota are constantly exposed to numerous chemicals through contaminated food, soil, water, and air. These chemicals can be taken up and distributed to reach sensitive tissues where they may cause various effects. Many of these chemicals lack data on their environmental and human health effects. Traditional toxicological tests relying on animal experiments are today being phased out in favor of cell-based and computational methods for early hazard detection and exposure assessment. This thesis focuses on developing computational tools for various stages of chemical risk assessment with a particular focus on bisphenols and per- and polyfluoroalkyl substances (PFAS). In Paper I, quantitative structure-activity relationship (QSAR) models covering molecular targets of the thyroid hormone (TH) system were developed and applied to two data sets to prioritize chemicals of concern for detailed toxicological studies. In Papers II and III, experimental and computational approaches were combined to study toxicokinetics and maternal transfer in zebrafish. Our main focus was to study potential mixture effects on administration, distribution, metabolism, and elimination (ADME) processes, i.e., to reveal if co-exposed chemicals impact each other’s ADME. Physiologically based kinetic (PBK) mixture models were developed to allow translation of external exposure concentrations into tissue concentrations and modelling plausible mechanisms of chemical interactions in a mixture.

    Main findings of this thesis are summarized as follows:

    • Application of QSAR models (Paper I) to two chemical inventories revealed that chemicals found in human blood could induce a large iirange of pathways in the TH system whereas chemicals used in Sweden with predicted high exposure index to consumers showed a lower likelihood to induce TH pathways.

    • Two zebrafish experiments (Paper II and Paper III) did not reveal statistically significant mixture effects on ADME of chemicals.

    • In Paper II, a PBK mixture model for PFAS accounting for competitive plasma protein binding was developed. The model demonstrated good predictive performance. Competitive plasma protein binding did not affect the predicted internal concentrations.

    • In Paper III we developed a binary PBK model parametrized for two bisphenols and PFOS showing that competitive plasma protein binding has an effect on ADME of bisphenols at PFOS concentrations at μg/L levels. At these levels internal concentrations of bisphenols were shown to decrease, implying that PFOS outcompeted bisphenols from studied plasma proteins resulting in higher excretion rates.

    Developed QSAR models showed good predictive power and the ability to identify and prioritize chemicals of concern with confidence. Additionally, PBK models aid in hypotheses testing and predicting exposure concentrations at which co-exposed chemicals could potentially influence each other’s ADME properties. These tools will provide overall early tier data on exposure and effects using non-testing methods in assessment of risks of chemicals. 

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  • 3.
    Golosovskaia, Elena
    et al.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Örn, Stefan
    Department of Biomedical Sciences and Veterinary Public Health, Swedish University of Agricultural Sciences (SLU), Uppsala, Sweden.
    Ahrens, Lutz
    Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences (SLU), Uppsala, Sweden.
    Chelcea, Ioana C.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Andersson, Patrik L.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Studying mixture effects on uptake and tissue distribution of PFAS in zebrafish (Danio rerio) using physiologically based kinetic (PBK) modelling2024In: Science of the Total Environment, ISSN 0048-9697, E-ISSN 1879-1026, Vol. 912, article id 168738Article in journal (Refereed)
    Abstract [en]

    Per- and polyfluoroalkyl substances (PFAS) are ubiquitously distributed in the aquatic environment. They include persistent, mobile, bioaccumulative, and toxic chemicals and it is therefore critical to increase our understanding on their adsorption, distribution, metabolism, excretion (ADME). The current study focused on uptake of seven emerging PFAS in zebrafish (Danio rerio) and their potential maternal transfer. In addition, we aimed at increasing our understanding on mixture effects on ADME by developing a physiologically based kinetic (PBK) model capable of handling co-exposure scenarios of any number of chemicals. All studied chemicals were taken up in the fish to varying degrees, whereas only perfluorononanoate (PFNA) and perfluorooctanoate (PFOA) were quantified in all analysed tissues. Perfluorooctane sulfonamide (FOSA) was measured at concerningly high concentrations in the brain (Cmax over 15 μg/g) but also in the liver and ovaries. All studied PFAS were maternally transferred to the eggs, with FOSA and 6:2 perfluorooctane sulfonate (6,2 FTSA) showing significant (p < 0.02) signs of elimination from the embryos during the first 6 days of development, while perfluorobutane sulfonate (PFBS), PFNA, and perfluorohexane sulfonate (PFHxS) were not eliminated in embryos during this time-frame. The mixture PBK model resulted in >85 % of predictions within a 10-fold error and 60 % of predictions within a 3-fold error. At studied levels of PFAS exposure, competitive binding was not a critical factor for PFAS kinetics. Gill surface pH influenced uptake for some carboxylates but not the sulfonates. The developed PBK model provides an important tool in understanding kinetics under complex mixture scenarios and this use of New Approach Methodologies (NAMs) is critical in future risk assessment of chemicals and early warning systems.

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  • 4.
    Golosovskaia, Elena
    et al.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Örn, Stefan
    Leonards, Pim
    Koekkoek, Jacco
    Andersson, Patrik
    Studying interaction effects on toxicokinetics in zebrafish combining experimental and modelling approachesManuscript (preprint) (Other academic)
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