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Westerhout J, den Heijer-Jordaan A, Princen HMG, Stierum R. A systems toxicology approach for identification of disruptions in cholesterol homeostasis after aggregated exposure to mixtures of perfluorinated compounds in humans. Toxicol Sci 2024; 198:191-209. [PMID: 38243716 DOI: 10.1093/toxsci/kfae006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2024] Open
Abstract
Per- and polyfluoroalkyl substances (PFAS) are used in various household and industrial products. In humans, positive associations were reported between PFAS, including perfluorsulfonic acid and perfluorooctanoic acid, and cholesterol, a cardiometabolic risk factor. Animal studies show the opposite. Human-centered approaches are needed to better understand the effects of PFAS mixtures on cholesterol. Here, a systems toxicology approach is described, using a gene-centered cholesterol biokinetic model. PFAS exposure-gene expression relations from published data were introduced into the model. An existing PFAS physiologically based kinetic model was augmented with lung and dermal compartments and integrated with the cholesterol model to enable exposure-effect modeling. The final model was populated with data reflecting lifetime mixture exposure from: tolerable weekly intake values; the environment; high occupational exposures (ski waxing, PFAS industry). Results indicate that low level exposures (tolerable weekly intake, environmental) did not change cholesterol. In contrast, occupational exposures clearly resulted in internal PFAS exposure and disruption of cholesterol homeostasis, largely in line with epidemiological observations. Despite model limitations (eg, dynamic range, directionality), changes in cholesterol homeostasis were predicted for ski waxers, hitherto unknown from epidemiological studies. Here, future studies involving lipid metabolism could improve risk assessment.
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Affiliation(s)
- Joost Westerhout
- TNO Risk Analysis for Products in Development, 3584 CB Utrecht, The Netherlands
| | | | | | - Rob Stierum
- TNO Risk Analysis for Products in Development, 3584 CB Utrecht, The Netherlands
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2
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Mori A, Ito S, Sekine T. A revision of the multiple-path particle dosimetry model focusing on tobacco product aerosol dynamics. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING 2024; 40:e3796. [PMID: 38185887 DOI: 10.1002/cnm.3796] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Revised: 10/15/2023] [Accepted: 11/26/2023] [Indexed: 01/09/2024]
Abstract
To assess the health impact of inhaled aerosols, it is necessary to understand aerosol dynamics and the associated dosimetry in the human respiratory tract. Although several studies have measured or simulated the dosimetry of aerosol constituents, the respiratory tract focus areas have been limited. In particular, the aerosols generated from tobacco products are complex composites and simulating their dynamics in the respiratory tract is challenging. To assess the dosimetry of the aerosol constituents of tobacco products, we developed a revised version of the Multiple-Path Particle Dosimetry (MPPD) model, which employs (1) new geometry based on CT-scanned human respiratory tract data, (2) convective mixing in the oral cavity and deep lung, and (3) constituent partitioning between the tissue and air, and clearance. The sensitivity analysis was conducted using aerosols composed of four major constituents of electronic cigarette (EC) aerosols to investigate the parameters that have a significant impact on the results. In addition, the revised model was run with 4 and 10 constituents in ECs and conventional cigarettes (CCs), respectively. Sensitivity analysis revealed that the new modeling and the physicochemical properties of constituents had a considerable impact on the simulated aerosol concentration and dosimetry. The simulations could be carried out within 3 min even when 10 constituents of CC aerosols were analyzed simultaneously. The revised model based on MPPD is an efficient and easy-to-use tool for understanding the aerosol dynamics of CC and EC constituents and their effect on the human body.
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Affiliation(s)
- Akina Mori
- Scientific Product Assessment Center, R&D Group, Japan Tobacco Inc., Yokohama, Japan
| | - Shigeaki Ito
- Scientific Product Assessment Center, R&D Group, Japan Tobacco Inc., Yokohama, Japan
| | - Takashi Sekine
- Scientific Product Assessment Center, R&D Group, Japan Tobacco Inc., Yokohama, Japan
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3
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Aakash A, Kulsoom R, Khan S, Siddiqui MS, Nabi D. Novel Models for Accurate Estimation of Air-Blood Partitioning: Applications to Individual Compounds and Complex Mixtures of Neutral Organic Compounds. J Chem Inf Model 2023; 63:7056-7066. [PMID: 37956246 PMCID: PMC10685450 DOI: 10.1021/acs.jcim.3c01288] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Revised: 10/23/2023] [Accepted: 10/25/2023] [Indexed: 11/15/2023]
Abstract
The air-blood partition coefficient (Kab) is extensively employed in human health risk assessment for chemical exposure. However, current Kab estimation approaches either require an extensive number of parameters or lack precision. In this study, we present two novel and parsimonious models to accurately estimate Kab values for individual neutral organic compounds, as well as their complex mixtures. The first model, termed the GC×GC model, was developed based on the retention times of nonpolar chemical analytes on comprehensive two-dimensional gas chromatography (GC×GC). This model is unique in its ability to estimate the Kab values for complex mixtures of nonpolar organic chemicals. The GC×GC model successfully accounted for the Kab variance (R2 = 0.97) and demonstrated strong prediction power (RMSE = 0.31 log unit) for an independent set of nonpolar chemical analytes. Overall, the GC×GC model can be used to estimate Kab values for complex mixtures of neutral organic compounds. The second model, termed the partition model (PM), is based on two types of partition coefficients: octanol to water (Kow) and air to water (Kaw). The PM was able to effectively account for the variability in Kab data (n = 344), yielding an R2 value of 0.93 and root-mean-square error (RMSE) of 0.34 log unit. The predictive power and explanatory performance of the PM were found to be comparable to those of the parameter-intensive Abraham solvation models (ASMs). Additionally, the PM can be integrated into the software EPI Suite, which is widely used in chemical risk assessment for initial screening. The PM provides quick and reliable estimation of Kab compared to ASMs, while the GC×GC model is uniquely suited for estimating Kab values for complex mixtures of neutral organic compounds. In summary, our study introduces two novel and parsimonious models for the accurate estimation of Kab values for both individual compounds and complex mixtures.
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Affiliation(s)
- Ahmad Aakash
- Institute
of Environmental Science and Engineering (IESE), School of Civil and
Environmental Engineering (SCEE), National
University of Sciences and Technology (NUST), H-12, 48000 Islamabad, Pakistan
| | - Ramsha Kulsoom
- Institute
of Environmental Science and Engineering (IESE), School of Civil and
Environmental Engineering (SCEE), National
University of Sciences and Technology (NUST), H-12, 48000 Islamabad, Pakistan
| | - Saba Khan
- Institute
of Environmental Science and Engineering (IESE), School of Civil and
Environmental Engineering (SCEE), National
University of Sciences and Technology (NUST), H-12, 48000 Islamabad, Pakistan
| | - Musab Saeed Siddiqui
- Institute
of Environmental Science and Engineering (IESE), School of Civil and
Environmental Engineering (SCEE), National
University of Sciences and Technology (NUST), H-12, 48000 Islamabad, Pakistan
| | - Deedar Nabi
- Institute
of Environmental Science and Engineering (IESE), School of Civil and
Environmental Engineering (SCEE), National
University of Sciences and Technology (NUST), H-12, 48000 Islamabad, Pakistan
- GEOMAR
Helmholtz Center for Ocean Research, Wischhofstrasse 1-3, 24148 Kiel, Germany
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4
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Hubbard HF, Ring CL, Hong T, Henning CC, Vallero DA, Egeghy PP, Goldsmith MR. Exposure Prioritization ( Ex Priori): A Screening-Level High-Throughput Chemical Prioritization Tool. TOXICS 2022; 10:569. [PMID: 36287849 PMCID: PMC9609548 DOI: 10.3390/toxics10100569] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Revised: 09/24/2022] [Accepted: 09/25/2022] [Indexed: 06/16/2023]
Abstract
To estimate potential chemical risk, tools are needed to prioritize potential exposures for chemicals with minimal data. Consumer product exposures are a key pathway, and variability in consumer use patterns is an important factor. We designed Ex Priori, a flexible dashboard-type screening-level exposure model, to rapidly visualize exposure rankings from consumer product use. Ex Priori is Excel-based. Currently, it is parameterized for seven routes of exposure for 1108 chemicals present in 228 consumer product types. It includes toxicokinetics considerations to estimate body burden. It includes a simple framework for rapid modeling of broad changes in consumer use patterns by product category. Ex Priori rapidly models changes in consumer user patterns during the COVID-19 pandemic and instantly shows resulting changes in chemical exposure rankings by body burden. Sensitivity analysis indicates that the model is sensitive to the air emissions rate of chemicals from products. Ex Priori's simple dashboard facilitates dynamic exploration of the effects of varying consumer product use patterns on prioritization of chemicals based on potential exposures. Ex Priori can be a useful modeling and visualization tool to both novice and experienced exposure modelers and complement more computationally intensive population-based exposure models.
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Affiliation(s)
| | - Caroline L. Ring
- Chemical Characterization and Exposure Division, Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Durham, NC 27713, USA
| | - Tao Hong
- ICF International, 2635 Meridian Parkway, Durham, NC 27713, USA
| | - Cara C. Henning
- ICF International, 2635 Meridian Parkway, Durham, NC 27713, USA
| | - Daniel A. Vallero
- Chemical Characterization and Exposure Division, Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Durham, NC 27713, USA
| | - Peter P. Egeghy
- Chemical Characterization and Exposure Division, Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Durham, NC 27713, USA
| | - Michael-Rock Goldsmith
- Chemical Characterization and Exposure Division, Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Durham, NC 27713, USA
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5
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Chang X, Tan YM, Allen DG, Bell S, Brown PC, Browning L, Ceger P, Gearhart J, Hakkinen PJ, Kabadi SV, Kleinstreuer NC, Lumen A, Matheson J, Paini A, Pangburn HA, Petersen EJ, Reinke EN, Ribeiro AJS, Sipes N, Sweeney LM, Wambaugh JF, Wange R, Wetmore BA, Mumtaz M. IVIVE: Facilitating the Use of In Vitro Toxicity Data in Risk Assessment and Decision Making. TOXICS 2022; 10:232. [PMID: 35622645 PMCID: PMC9143724 DOI: 10.3390/toxics10050232] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Accepted: 04/24/2022] [Indexed: 02/04/2023]
Abstract
During the past few decades, the science of toxicology has been undergoing a transformation from observational to predictive science. New approach methodologies (NAMs), including in vitro assays, in silico models, read-across, and in vitro to in vivo extrapolation (IVIVE), are being developed to reduce, refine, or replace whole animal testing, encouraging the judicious use of time and resources. Some of these methods have advanced past the exploratory research stage and are beginning to gain acceptance for the risk assessment of chemicals. A review of the recent literature reveals a burst of IVIVE publications over the past decade. In this review, we propose operational definitions for IVIVE, present literature examples for several common toxicity endpoints, and highlight their implications in decision-making processes across various federal agencies, as well as international organizations, including those in the European Union (EU). The current challenges and future needs are also summarized for IVIVE. In addition to refining and reducing the number of animals in traditional toxicity testing protocols and being used for prioritizing chemical testing, the goal to use IVIVE to facilitate the replacement of animal models can be achieved through their continued evolution and development, including a strategic plan to qualify IVIVE methods for regulatory acceptance.
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Affiliation(s)
- Xiaoqing Chang
- Inotiv-RTP, 601 Keystone Park Drive, Suite 200, Morrisville, NC 27560, USA; (X.C.); (D.G.A.); (S.B.); (L.B.); (P.C.)
| | - Yu-Mei Tan
- U.S. Environmental Protection Agency, Office of Pesticide Programs, 109 T.W. Alexander Drive, Durham, NC 27709, USA;
| | - David G. Allen
- Inotiv-RTP, 601 Keystone Park Drive, Suite 200, Morrisville, NC 27560, USA; (X.C.); (D.G.A.); (S.B.); (L.B.); (P.C.)
| | - Shannon Bell
- Inotiv-RTP, 601 Keystone Park Drive, Suite 200, Morrisville, NC 27560, USA; (X.C.); (D.G.A.); (S.B.); (L.B.); (P.C.)
| | - Paul C. Brown
- U.S. Food and Drug Administration, Center for Drug Evaluation and Research, 10903 New Hampshire Avenue, Silver Spring, MD 20903, USA; (P.C.B.); (A.J.S.R.); (R.W.)
| | - Lauren Browning
- Inotiv-RTP, 601 Keystone Park Drive, Suite 200, Morrisville, NC 27560, USA; (X.C.); (D.G.A.); (S.B.); (L.B.); (P.C.)
| | - Patricia Ceger
- Inotiv-RTP, 601 Keystone Park Drive, Suite 200, Morrisville, NC 27560, USA; (X.C.); (D.G.A.); (S.B.); (L.B.); (P.C.)
| | - Jeffery Gearhart
- The Henry M. Jackson Foundation, Air Force Research Laboratory, 711 Human Performance Wing, Wright-Patterson Air Force Base, OH 45433, USA;
| | - Pertti J. Hakkinen
- National Library of Medicine, National Center for Biotechnology Information, 8600 Rockville Pike, Bethesda, MD 20894, USA;
| | - Shruti V. Kabadi
- U.S. Food and Drug Administration, Center for Food Safety and Applied Nutrition, Office of Food Additive Safety, 5001 Campus Drive, HFS-275, College Park, MD 20740, USA;
| | - Nicole C. Kleinstreuer
- National Institute of Environmental Health Sciences, National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods, P.O. Box 12233, Research Triangle Park, NC 27709, USA;
| | - Annie Lumen
- U.S. Food and Drug Administration, National Center for Toxicological Research, 3900 NCTR Road, Jefferson, AR 72079, USA;
| | - Joanna Matheson
- U.S. Consumer Product Safety Commission, Division of Toxicology and Risk Assessment, 5 Research Place, Rockville, MD 20850, USA;
| | - Alicia Paini
- European Commission, Joint Research Centre (JRC), 21027 Ispra, Italy;
| | - Heather A. Pangburn
- Air Force Research Laboratory, 711 Human Performance Wing, 2729 R Street, Area B, Building 837, Wright-Patterson Air Force Base, OH 45433, USA;
| | - Elijah J. Petersen
- U.S. Department of Commerce, National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg, MD 20899, USA;
| | - Emily N. Reinke
- U.S. Army Public Health Center, 8252 Blackhawk Rd., Aberdeen Proving Ground, MD 21010, USA;
| | - Alexandre J. S. Ribeiro
- U.S. Food and Drug Administration, Center for Drug Evaluation and Research, 10903 New Hampshire Avenue, Silver Spring, MD 20903, USA; (P.C.B.); (A.J.S.R.); (R.W.)
| | - Nisha Sipes
- U.S. Environmental Protection Agency, Center for Computational Toxicology and Exposure, 109 TW Alexander Dr., Research Triangle Park, NC 27711, USA; (N.S.); (J.F.W.); (B.A.W.)
| | - Lisa M. Sweeney
- UES, Inc., 4401 Dayton-Xenia Road, Beavercreek, OH 45432, Assigned to Air Force Research Laboratory, 711 Human Performance Wing, Wright-Patterson Air Force Base, OH 45433, USA;
| | - John F. Wambaugh
- U.S. Environmental Protection Agency, Center for Computational Toxicology and Exposure, 109 TW Alexander Dr., Research Triangle Park, NC 27711, USA; (N.S.); (J.F.W.); (B.A.W.)
| | - Ronald Wange
- U.S. Food and Drug Administration, Center for Drug Evaluation and Research, 10903 New Hampshire Avenue, Silver Spring, MD 20903, USA; (P.C.B.); (A.J.S.R.); (R.W.)
| | - Barbara A. Wetmore
- U.S. Environmental Protection Agency, Center for Computational Toxicology and Exposure, 109 TW Alexander Dr., Research Triangle Park, NC 27711, USA; (N.S.); (J.F.W.); (B.A.W.)
| | - Moiz Mumtaz
- Agency for Toxic Substances and Disease Registry, Office of the Associate Director for Science, 1600 Clifton Road, S102-2, Atlanta, GA 30333, USA
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Kenyon EM, Eklund C, Pegram RA, Lipscomb JC. Comparison of in vivo derived and scaled in vitro metabolic rate constants for several volatile organic compounds (VOCs). Toxicol In Vitro 2020; 69:105002. [PMID: 32946980 DOI: 10.1016/j.tiv.2020.105002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Revised: 08/26/2020] [Accepted: 09/13/2020] [Indexed: 10/23/2022]
Abstract
Metabolic rate parameters estimation using in vitro data is necessary due to numbers of chemicals for which data are needed, trend towards minimizing laboratory animal use, and limited opportunity to collect data in human subjects. We evaluated how well metabolic rate parameters derived from in vitro data predict overall in vivo metabolism for a set of environmental chemicals for which well validated and established methods exist. We compared values of VmaxC derived from in vivo vapor uptake studies with estimates of VmaxC scaled up from in vitro hepatic microsomal metabolism studies for VOCs for which data were available in male F344 rats. For 6 of 7 VOCs, differences between the in vivo and scaled up in vitro VmaxC estimates were less than 2.6-fold. For bromodichloromethane (BDCM), the in vivo derived VmaxC was approximately 4.4-fold higher than the in vitro derived and scaled up VmaxC. The more rapid rate of BDCM metabolism estimated based in vivo studies suggests other factors such as extrahepatic metabolism, binding or other non-specific losses making a significant contribution to overall clearance. Systematic and reliable utilization of scaled up in vitro biotransformation rate parameters in PBPK models will require development of methods to predict cases in which extrahepatic metabolism and binding as well as other factors are likely to be significant contributors.
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Affiliation(s)
- Elaina M Kenyon
- Center for Computational Toxicology and Exposure, U.S. EPA, Office of Research and Development, Research Triangle Park, NC, United States.
| | - Christopher Eklund
- Center for Computational Toxicology and Exposure, U.S. EPA, Office of Research and Development, Research Triangle Park, NC, United States
| | - Rex A Pegram
- Center for Computational Toxicology and Exposure, U.S. EPA, Office of Research and Development, Research Triangle Park, NC, United States
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7
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Wilkinson M, White IR, Goodacre R, Nijsen T, Fowler SJ. Effects of high relative humidity and dry purging on VOCs obtained during breath sampling on common sorbent tubes. J Breath Res 2020; 14:046006. [DOI: 10.1088/1752-7163/ab7e17] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
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8
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Mirzaei H, O'Brien A, Tasnim N, Ravishankara A, Tahmooressi H, Hoorfar M. Topical review on monitoring tetrahydrocannabinol in breath. J Breath Res 2020; 14:034002. [PMID: 31842004 DOI: 10.1088/1752-7163/ab6229] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Legalization of cannabis for recreational use has compelled governments to seek new tools to accurately monitor Δ9-tetrahydrocannabinol (Δ9-THC) and understand its effect on impairment. Various methods have been employed to measure Δ9-THC, and its respective metabolites, in different biological matrices. Recently, breath analysis has gained interest as a non-invasive method for the detection of chemicals that are either produced as part of biological processes or are absorbed from the environment. Existing breath analyzers function by analyzing previously collected samples or by direct real-time analysis. Portable hand-held devices are of particular interest for law enforcement and personal use. This paper reviews and compares both commercially available and prototype devices that proclaim Δ9-THC detection in exhaled breath using methods such as Field Asymmetric Ion Mobility Spectrometry, Semiconductor-Enriched Single-Walled Carbon Nanotube chemiresistors, Liquid Chromatography Tandem-mass Spectrometry, microfluidic-based artificial olfaction, and optical-based gas sensing.
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9
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Cotterill JV, Palazzolo L, Ridgway C, Price N, Rorije E, Moretto A, Peijnenburg A, Eberini I. Predicting estrogen receptor binding of chemicals using a suite of in silico methods - Complementary approaches of (Q)SAR, molecular docking and molecular dynamics. Toxicol Appl Pharmacol 2019; 378:114630. [PMID: 31220507 DOI: 10.1016/j.taap.2019.114630] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2019] [Revised: 05/17/2019] [Accepted: 06/17/2019] [Indexed: 11/18/2022]
Abstract
With the aim of obtaining reliable estimates of Estrogen Receptor (ER) binding for diverse classes of compounds, a weight of evidence approach using estimates from a suite of in silico models was assessed. The predictivity of a simple Majority Consensus of (Q)SAR models was assessed using a test set of compounds with experimental Relative Binding Affinity (RBA) data. Molecular docking was also carried out and the binding energies of these compounds to the ERα receptor were determined. For a few selected compounds, including a known full agonist and antagonist, the intrinsic activity was determined using low-mode molecular dynamics methods. Individual (Q)SAR model predictivity varied, as expected, with some models showing high sensitivity, others higher specificity. However, the Majority Consensus (Q)SAR prediction showed a high accuracy and reasonably balanced sensitivity and specificity. Molecular docking provided quantitative information on strength of binding to the ERα receptor. For the 50 highest binding affinity compounds with positive RBA experimental values, just 5 of them were predicted to be non-binders by the Majority QSAR Consensus. Furthermore, agonist-specific assay experimental values for these 5 compounds were negative, which indicates that they may be ER antagonists. We also showed different scenarios of combining (Q)SAR results with Molecular docking classification of ER binding based on cut-off values of binding energies, providing a rational combined strategy to maximize terms of toxicological interest.
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Affiliation(s)
- J V Cotterill
- Fera Science Limited, Sand Hutton, York YO41 1LZ, UK
| | - L Palazzolo
- Università degli Studi di Milano, Dipartimento di Scienze Farmacologiche e Biomolecolari, Via Balzaretti 9, 20133 Milano, Italy
| | - C Ridgway
- Fera Science Limited, Sand Hutton, York YO41 1LZ, UK
| | - N Price
- Fera Science Limited, Sand Hutton, York YO41 1LZ, UK
| | - E Rorije
- Centre for Safety of Substances and Products, National Institute for Public Health and Environment (RIVM), P.O. Box 1, 3720 BA, Bilthoven, The Netherlands
| | - A Moretto
- Università degli Studi di Milano, Dipartimento di Scienze Biomediche e Cliniche, Ospedale L. Sacco, Padiglione 17, Via G.B. Grassi 74, 20157 Milano, Italy
| | - A Peijnenburg
- Wageningen University & Research, Wageningen, The Netherlands
| | - I Eberini
- Università degli Studi di Milano, Dipartimento di Scienze Farmacologiche e Biomolecolari & DSRC, Via Balzaretti 9, 20133 Milano, Italy.
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10
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Chebekoue SF, Krishnan K. Derivation of internal dose-based thresholds of toxicological concern for occupational inhalation exposure to systemically acting organic chemicals. JOURNAL OF OCCUPATIONAL AND ENVIRONMENTAL HYGIENE 2019; 16:308-319. [PMID: 30676257 DOI: 10.1080/15459624.2019.1568445] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
This study aimed at deriving occupational thresholds of toxicological concern for inhalation exposure to systemically-acting organic chemicals using predicted internal doses. The latter were also used to evaluate the quantitative relationship between occupational exposure limit and internal dose. Three internal dose measures were identified for investigation: (i) the daily area under the venous blood concentration vs. time curve, (ii) the daily rate of the amount of parent chemical metabolized, and (iii) the maximum venous blood concentration at the end of an 8-hr work shift. A dataset of 276 organic chemicals with 8-hr threshold limit values-time-weighted average was compiled along with their molecular structure and Cramer classes (Class I: low toxicity, Class II: intermediate toxicity, Class III: suggestive of significant toxicity). Using a human physiologically-based pharmacokinetic model, the three identified dose metrics were predicted for an 8-hr occupational inhalation exposure to the threshold limit value for each chemical. Distributional analyses of the predicted dose metrics were performed to identify the percentile values corresponding to the occupational thresholds of toxicological concern. Also, simple linear regression analyses were performed to evaluate the relationship between the 8-hr threshold limit value and each of the predicted dose metrics, respectively. No threshold of toxicological concern could be derived for class II due to few chemicals. Based on the daily rate of the amount of parent chemical metabolized, the proposed internal dose-based occupational thresholds of toxicological concern were 5.61 × 10-2 and 9 × 10-4 mmol/d at the 10th percentile level for classes I and III, respectively, while they were 4.55 × 10-1 and 8.5 × 10-3 mmol/d at the 25th percentile level. Even though high and significant correlations were observed between the 8-hr threshold limit values and the predicted dose metrics, the one with the rate of the amount of chemical metabolized was remarkable regardless of the Cramer class (r2 = 0.81; n = 276). The proposed internal dose-based occupational thresholds of toxicological concern are potentially useful for screening-level assessments as well as prioritization within an integrated occupational risk assessment framework.
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Affiliation(s)
- Sandrine F Chebekoue
- a École de Santé Publique de l'Université de Montréal (ESPUM) , Montréal , Québec , Canada
| | - Kannan Krishnan
- a École de Santé Publique de l'Université de Montréal (ESPUM) , Montréal , Québec , Canada
- b Institut de recherche Robert-Sauvé en santé et en sécurité du travail (IRSST) , Montréal , Québec , Canada
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11
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Critical Review of Volatile Organic Compound Analysis in Breath and In Vitro Cell Culture for Detection of Lung Cancer. Metabolites 2019; 9:metabo9030052. [PMID: 30889835 PMCID: PMC6468373 DOI: 10.3390/metabo9030052] [Citation(s) in RCA: 79] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2019] [Revised: 03/11/2019] [Accepted: 03/13/2019] [Indexed: 12/16/2022] Open
Abstract
Breath analysis is a promising technique for lung cancer screening. Despite the rapid development of breathomics in the last four decades, no consistent, robust, and validated volatile organic compound (VOC) signature for lung cancer has been identified. This review summarizes the identified VOC biomarkers from both exhaled breath analysis and in vitro cultured lung cell lines. Both clinical and in vitro studies have produced inconsistent, and even contradictory, results. Methodological issues that lead to these inconsistencies are reviewed and discussed in detail. Recommendations on addressing specific issues for more accurate biomarker studies have also been made.
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12
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Chebekoue SF, Krishnan K. A framework for application of quantitative property-property relationships (QPPRs) in physiologically based pharmacokinetic (PBPK) models for high-throughput prediction of internal dose of inhaled organic chemicals. CHEMOSPHERE 2019; 215:634-646. [PMID: 30347358 DOI: 10.1016/j.chemosphere.2018.10.041] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/03/2018] [Revised: 10/03/2018] [Accepted: 10/06/2018] [Indexed: 06/08/2023]
Abstract
New generation of toxicological tests and assessment strategies require validated toxicokinetic data or models that are lacking for most chemicals. This study aimed at developing a quantitative property-property relationship (QPPR)-based human physiologically based pharmacokinetic (PBPK) modeling framework for high-throughput predictions of inhalation toxicokinetics of organic chemicals. A PBPK model was parameterized with QPPR-derived values for hepatic clearance (CLh) and partition coefficients (P) [blood:air (Pba) and tissue:air (Pta) and tissue:blood (Ptb)]. The model was initially applied to an evaluation dataset of 40 organic chemicals in the applicability domain, and then to an expanded dataset of 249 organic chemicals from diverse chemical classes. 'Batch' analyses were performed for rapid assessments of hundreds of chemicals. The simulations of inhalation toxicokinetics following an 8-h exposure to 1 ppm of each chemical were successful. The mean ratios of their predicted-to-experimental values were within a factor of 1.36-2.36 for Ptb and 1.18 for CLh, for 80% of the chemicals in the evaluation dataset. The predicted 24-h area under the venous blood concentration-time curve (AUC24) values were within the predicted envelopes obtained while using experimental values of Pba and considering either no or maximal hepatic extraction. The reliability analysis (based on combined sensitivity and uncertainty analyses) indicated that AUC24 predictions for 55% of the expanded dataset were moderately to highly reliable, with 46% exhibiting highly reliable values. Overall, the modeling framework suggests that molecular structure and chemical properties can together be effectively used to obtain first-cut estimates of the toxicokinetics of data-poor organic chemicals for screening and prioritization purposes.
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Affiliation(s)
- Sandrine F Chebekoue
- École de Santé Publique de l'Université de Montréal (ESPUM), Montréal, Québec, Canada.
| | - Kannan Krishnan
- École de Santé Publique de l'Université de Montréal (ESPUM), Montréal, Québec, Canada; Institut de recherche Robert-Sauvé en santé et en sécurité du travail (IRSST), Montréal, Québec, Canada.
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Chebekoue SF, Krishnan K. Derivation of Occupational Thresholds of Toxicological Concern for Systemically Acting Noncarcinogenic Organic Chemicals. Toxicol Sci 2018; 160:47-56. [PMID: 29036659 DOI: 10.1093/toxsci/kfx155] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Many substances in workplace do not have occupational exposure limits. The threshold of toxicological concern (TTC) principle is part of the hierarchy of approaches useful in occupational health risk assessment. The aim of this study was to derive occupational TTCs (OTTCs) reflecting the airborne concentrations below which no significant risk to workers would be anticipated. A reference dataset consisting of the 8-h threshold limit values-Time-Weighted Average for 280 organic substances was compiled. Each substance was classified into low (class I), intermediate (class II), or high (class III) hazard categories as per Cramer rules. For each chemical, n-octanol:water partition coefficient and vapor pressure along with the molecular weight were used to predict the blood:air partition coefficient. The blood:air partition coefficient along with data on water solubility and ventilation rate allowed the prediction of pulmonary retention factor and absorbed dose in workers. For each Cramer class, the distribution of the predicted doses was analyzed to identify the various percentile values corresponding to the OTTC. Accordingly, for Cramer classes I-III, the OTTCs derived in this study correspond to 0.15, 0.0085, and 0.006 mmol/d, respectively, at the 10th percentile level, while these values were 1.5, 0.09 and 0.03 mmol/d at the 25th percentile level. The proposed OTTCs are not meant to replace the traditional occupational exposure limits, but can be used in data-poor situations along with exposure estimates to support screening level risk assessment and prioritization.
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Affiliation(s)
- Sandrine F Chebekoue
- Département de Santé Environnementale et Santé au Travail, École de Santé Publique de l'Université de Montréal, Université de Montréal, Montréal, Québec H3C 3J7, Canada
| | - Kannan Krishnan
- Département de Santé Environnementale et Santé au Travail, École de Santé Publique de l'Université de Montréal, Université de Montréal, Montréal, Québec H3C 3J7, Canada
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Tejero Rioseras A, Singh KD, Nowak N, Gaugg MT, Bruderer T, Zenobi R, Sinues PML. Real-Time Monitoring of Tricarboxylic Acid Metabolites in Exhaled Breath. Anal Chem 2018; 90:6453-6460. [DOI: 10.1021/acs.analchem.7b04600] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Affiliation(s)
- Alberto Tejero Rioseras
- Department of Chemistry and Applied Biosciences, ETH Zurich, 8093 Zurich, Switzerland
- SEADM, S.L., 28036 Madrid, Spain
- Department of Analytical Chemistry, University of Cordoba, 14005 Cordoba, Spain
| | - Kapil Dev Singh
- University Children’s Hospital Basel, University of Basel, 4056 Basel, Switzerland
- Department of Biomedical Engineering, University of Basel, 4123 Allschwil, Switzerland
| | - Nora Nowak
- Department of Chemistry and Applied Biosciences, ETH Zurich, 8093 Zurich, Switzerland
| | - Martin T. Gaugg
- Department of Chemistry and Applied Biosciences, ETH Zurich, 8093 Zurich, Switzerland
| | - Tobias Bruderer
- Department of Chemistry and Applied Biosciences, ETH Zurich, 8093 Zurich, Switzerland
| | - Renato Zenobi
- Department of Chemistry and Applied Biosciences, ETH Zurich, 8093 Zurich, Switzerland
| | - Pablo M.-L. Sinues
- Department of Chemistry and Applied Biosciences, ETH Zurich, 8093 Zurich, Switzerland
- University Children’s Hospital Basel, University of Basel, 4056 Basel, Switzerland
- Department of Biomedical Engineering, University of Basel, 4123 Allschwil, Switzerland
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Webster EM, Qian H, Mackay D, Christensen RD, Tietjen B, Zaleski R. Modeling Human Exposure to Indoor Contaminants: External Source to Body Tissues. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2016; 50:8697-8704. [PMID: 27434742 DOI: 10.1021/acs.est.6b00895] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
Information on human indoor exposure is necessary to assess the potential risk to individuals from many chemicals of interest. Dynamic indoor and human physicologically based pharmacokinetic (PBPK) models of the distribution of nonionizing, organic chemical concentrations in indoor environments resulting in delivered tissue doses are developed, described and tested. The Indoor model successfully reproduced independently measured, reported time-dependent air concentrations of chloroform released during showering and of 2-butyoxyethanol following use of a volatile surface cleaner. The Indoor model predictions were also comparable to those from a higher tier consumer model (ConsExpo 4.1) for the surface cleaner scenario. The PBPK model successful reproduced observed chloroform exhaled air concentrations resulting from an inhalation exposure. Fugacity based modeling provided a seamless description of the partitioning, fluxes, accumulation and release of the chemical in indoor media and tissues of the exposed subject. This has the potential to assist in health risk assessments, provided that appropriate physical/chemical property, usage characteristics, and toxicological information are available.
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Affiliation(s)
- Eva M Webster
- Carrousel Environmental Modelling Research , Peterborough, Ontario K9H 0E2 Canada
| | - Hua Qian
- ExxonMobil Biomedical Sciences, Inc. , Annandale, New Jersey 08801, United States
| | - Donald Mackay
- Environment and Resource Sciences, Trent University , Peterborough, Ontario K9L 0G2 Canada
| | - Rebecca D Christensen
- Environment and Resource Sciences, Trent University , Peterborough, Ontario K9L 0G2 Canada
| | - Britta Tietjen
- Environment and Resource Sciences, Trent University , Peterborough, Ontario K9L 0G2 Canada
- Freie Universität Berlin , Biodiversity and Ecological Modeling, D-14195 Berlin, Germany
| | - Rosemary Zaleski
- ExxonMobil Biomedical Sciences, Inc. , Annandale, New Jersey 08801, United States
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Gajewska M, Worth A, Urani C, Briesen H, Schramm KW. The acute effects of daily nicotine intake on heart rate--a toxicokinetic and toxicodynamic modelling study. Regul Toxicol Pharmacol 2014; 70:312-24. [PMID: 25066669 DOI: 10.1016/j.yrtph.2014.07.015] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2014] [Revised: 07/16/2014] [Accepted: 07/17/2014] [Indexed: 11/29/2022]
Abstract
Joint physiologically-based toxicokinetic and toxicodynamic (PBTK/TD) modelling was applied to simulate concentration-time profiles of nicotine, a well-known stimulant, in the human body following single and repeated dosing. Both kinetic and dynamic models were first calibrated by using in vivo literature data for the Caucasian population. The models were then used to estimate the blood and liver concentrations of nicotine in terms of the Area Under Curve (AUC) and the peak concentration (Cmax) for selected exposure scenarios based on inhalation (cigarette smoking), oral intake (nicotine lozenges) and dermal absorption (nicotine patches). The model simulations indicated that whereas frequent cigarette smoking gives rise to high AUC and Cmax in blood, the use of nicotine-rich dermal patches leads to high AUC and Cmax in the liver. Venous blood concentrations were used to estimate one of the most common acute effects, mean heart rate, both at rest and during exercise. These estimations showed that cigarette smoking causes a high peak heart rate, whereas dermal absorption causes a high mean heart rate over 48h. This study illustrates the potential of using PBTK/TD modelling in the safety assessment of nicotine-containing products.
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Affiliation(s)
- M Gajewska
- Systems Toxicology Unit and EURL ECVAM, Institute for Health and Consumer Protection, European Commission, Joint Research Centre, 21027 Ispra, VA, Italy; University of Milano Bicocca, Dep. of Earth and Environmental Sciences, Piazza della Scienza 1, Milano, Italy; TUM, Wissenschaftszentrum Weihenstephan für Ernährung und Landnutzung, Department für Biowissenschaften, Weihenstephaner Steig 23, 85350 Freising, Germany.
| | - A Worth
- Systems Toxicology Unit and EURL ECVAM, Institute for Health and Consumer Protection, European Commission, Joint Research Centre, 21027 Ispra, VA, Italy
| | - C Urani
- University of Milano Bicocca, Dep. of Earth and Environmental Sciences, Piazza della Scienza 1, Milano, Italy
| | - H Briesen
- TUM, Wissenschaftszentrum Weihenstephan für Ernährung und Landnutzung, Lehrstuhl für Systemverfahrenstechnik, Weihenstephaner Steig 23, 85350 Freising, Germany
| | - K-W Schramm
- TUM, Wissenschaftszentrum Weihenstephan für Ernährung und Landnutzung, Department für Biowissenschaften, Weihenstephaner Steig 23, 85350 Freising, Germany; Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Molecular EXposomics (MEX), Ingolstädter Landstr.1, D-85764 Neuherberg, Germany
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PBTK modelling platforms and parameter estimation tools to enable animal-free risk assessment: recommendations from a joint EPAA--EURL ECVAM ADME workshop. Regul Toxicol Pharmacol 2013; 68:119-39. [PMID: 24287156 DOI: 10.1016/j.yrtph.2013.11.008] [Citation(s) in RCA: 90] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2013] [Revised: 11/07/2013] [Accepted: 11/12/2013] [Indexed: 12/25/2022]
Abstract
Information on toxicokinetics is critical for animal-free human risk assessment. Human external exposure must be translated into human tissue doses and compared with in vitro actual cell exposure associated to effects (in vitro-in vivo comparison). Data on absorption, distribution, metabolism and excretion in humans (ADME) could be generated using in vitro and QSAR tools. Physiologically-based toxicokinetic (PBTK) computer modelling could serve to integrate disparate in vitro and in silico findings. However, there are only few freely-available PBTK platforms currently available. And although some ADME parameters can be reasonably estimated in vitro or in silico, important gaps exist. Examples include unknown or limited applicability domains and lack of (high-throughput) tools to measure penetration of barriers, partitioning between blood and tissues and metabolic clearance. This paper is based on a joint EPAA--EURL ECVAM expert meeting. It provides a state-of-the-art overview of the availability of PBTK platforms as well as the in vitro and in silico methods to parameterise basic (Tier 1) PBTK models. Five high-priority issues are presented that provide the prerequisites for wider use of non-animal based PBTK modelling for animal-free chemical risk assessment.
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