path: root/bibliography.bib

@misc{ICH2017,
  author = {International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH)},
  title = {Assessment and control of DNA reactive (mutagenic) impurities in pharmaceuticals to limit potential carcinogenic risk M7(R1)},
  year = 2017,
  note = {\url{https://database.ich.org/sites/default/files/M7_R1_Guideline.pdf}},
  note = {Accessed: 29-03-2021},
}

@misc{ECHA2017,
  author ={European Chemicals Agency (ECHA)},
  title = {Guidance on Information Requirements and Chemical Safety Assessment, Chapter R.7a: Endpoint specific guidance},
  year = 2017,
  note ={\url{https://echa.europa.eu/documents/10162/13632/information_requirements_r6_en.pdf}},
  note = {Accessed: 29-03-2021},
  isbn = {978-92-9495-970-6},
  doi = {10.2823/337352}},
}
@article{Rubiolo1992,
  author = {Rubiolo, P. and Pieters, L. and Calomme, M. and Bicchi, C. and Vlietinck, A. and Vanden Berghe, D.},
  year = 1992,
  title = {Mutagenicity of pyrrolizidine alkaloids in the Salmonella typhimurium/mammalian microsome system},
  journal = {Mutation research},
  number = 281, 
  pages = {143–147}
}

@article{Chen2010,
  author = {Chen, T. and Mei, N. and Fu, P.P.},
  year = 2010,
  title = {Genotoxicity of pyrrolizidine alkaloids},
  journal = {J. Appl. Toxicol.},
  numbr = 30,
  pages = {183-96}
}

@article{Li2013,
  authors = {Li YH, Kan WL, Li N, Lin G},
  year = 2013,
  title = {Assessment of pyrrolizidine alkaloid-induced toxicity in an in vitro screening model},
  journal = {J. Ethnopharmacol.},
  number = 150,
  pages = {560-7}
}

@article{Xia2013,
  authors = {Xia, Q. and Zhao, Y. and Von Tungeln, L.S. and Doerge, D.R. and Lin, G. and et al.},
  year = 2013,
  title = {Pyrrolizidine alkaloid-derived DNA adducts as a common biological biomarker of pyrrolizidine alkaloid-induced tumorigenicity},
  journal = {Chem Res. Toxicol.},
  number = 26,
  pages = {1384-96}
}

@article{Fu2004,
  authors = {Fu, P.P. and Xia, Q. and, Lin, G. and Chou, M.W.},
  year = 2004,
  title = {Pyrrolizidine alkaloids--genotoxicity, metabolism enzymes, metabolic activation, and mechanisms},
  journal = {Drug Metab. Rev.},
  number = 36,
  pages = {1-55}
}

@article{Louisse2019,
  title = {Determination of genotoxic potencies of pyrrolizidine alkaloids in HepaRG cells using the γH2AX assay},
  journal = {Food and Chemical Toxicology},
  volume = {131},
  pages = {110532},
  year = {2019},
  issn = {0278-6915},
  doi = {https://doi.org/10.1016/j.fct.2019.05.040},
  url = {https://www.sciencedirect.com/science/article/pii/S0278691519303072},
  author = {Jochem Louisse and Deborah Rijkers and Geert Stoopen and Wendy Jansen Holleboom and Mona Delagrange and Elise Molthof and Patrick P.J. Mulder and Ron L.A.P. Hoogenboom and Marc Audebert and Ad A.C.M. Peijnenburg},
  keywords = {Pyrrolizidine alkaloids (PAs), HepaRG, Genotoxicity, γH2AX assay, Relative potency factor (RPF)},
  abstract = {Pyrrolizidine alkaloids (PAs) are secondary metabolites from plants that have been found in substantial amounts in herbal supplements, infusions and teas. Several PAs cause cancer in animal bioassays, mediated via a genotoxic mode of action, but for the majority of the PAs, carcinogenicity data are lacking. It is assumed in the risk assessment that all PAs have the same potency as riddelliine, which is considered to be one of the most potent carcinogenic PAs in rats. This may overestimate the risks, since many PAs are expected to have lower potencies. In this study we determined the concentration-dependent genotoxicity of 37 PAs representing different chemical classes using the γH2AX in cell western assay in HepaRG human liver cells. Based on these in vitro data, PAs were grouped into different potency classes. The group with the highest potency consists particularly of open diester PAs and cyclic diester PAs (including riddelliine). The group of the least potent or non-active PAs includes the monoester PAs, non-esterified necine bases, PA N-oxides, and the unsaturated PA trachelanthamine. This study reveals differences in in vitro genotoxic potencies of PAs, supporting that the assumption that all PAs have a similar potency as riddelliine is rather conservative.}
}

@article{Allemang2018,
  title = {Relative potency of fifteen pyrrolizidine alkaloids to induce DNA damage as measured by micronucleus induction in HepaRG human liver cells},
  journal = {Food and Chemical Toxicology},
  volume = {121},
  pages = {72-81},
  year = {2018},
  issn = {0278-6915},
  doi = {https://doi.org/10.1016/j.fct.2018.08.003},
  url = {https://www.sciencedirect.com/science/article/pii/S027869151830512X},
  author = {Ashley Allemang and Catherine Mahony and Cathy Lester and Stefan Pfuhler},
  keywords = {Pyrrolizidine alkaloids, HepaRG, Genetic toxicology, Micronucleus test, Relative potency factor, Risk assessment},
  abstract = {Plant-based 1,2-unsaturated Pyrrolizidine Alkaloids (PAs) can be found as contaminants in foods like teas, herbs and honey. PAs are responsible for liver genotoxicity/carcinogenicity following metabolic activation, making them a relevant concern for safety assessment. Current regulatory risk assessments take a precautionary approach and assume all PAs are as potent as the known most potent representatives: lasiocarpine and riddelliine. Our study investigated whether genotoxicity potency differed as a consequence of structural differences, assessing micronuclei in vitro in HepaRG cells which express metabolising enzymes at levels similar to primary human hepatocytes. Benchmark Dose (BMD) analysis was used to calculate the critical effect dose for 15 PAs representing 6 structural classes. When BMD confidence intervals were used to rank PAs, lasiocarpine was the most potent PA and plotted distinctly from all other PAs examined. PA-N-oxides were least potent, notably less potent than their corresponding parent PA's. The observed genotoxic potency compared favorably with existing in vitro data when metabolic competency was considered. Although further consideration of biokinetics will be needed to develop a robust understanding of relative potencies for a realistic risk assessment of PA mixtures, these data facilitate understanding of their genotoxic potencies and affirm that not all PAs are created equal.}
}
@article{Hadi2021,
  title = {Genotoxicity of selected pyrrolizidine alkaloids in human hepatoma cell lines HepG2 and Huh6},
  journal = {Mutation Research/Genetic Toxicology and Environmental Mutagenesis},
  volume = {861-862},
  pages = {503305},
  year = {2021},
  issn = {1383-5718},
  doi = {https://doi.org/10.1016/j.mrgentox.2020.503305},
  url = {https://www.sciencedirect.com/science/article/pii/S1383571820301765},
  author = {Naji Said Aboud Hadi and Ezgi Eyluel Bankoglu and Lea Schott and Eva Leopoldsberger and Vanessa Ramge and Olaf Kelber and Hartwig Sievers and Helga Stopper},
  keywords = {Pyrrolizidine alkaloids, Genomic damage, Micronuclei, Crosslink comet assay, HepG2 cells, Huh6 cells},
  abstract = {Introduction
Pyrrolizidine alkaloids (PAs) are found in many plant species as secondary metabolites which affect humans via contaminated food sources, herbal medicines and dietary supplements. Hundreds of compounds belonging to PAs have been identified. PAs undergo hepatic metabolism, after which they can induce hepatotoxicity and carcinogenicity. Many aspects of their mechanism of carcinogenicity are still unclear and it is important for human risk assessment to investigate this class of compounds further.
Material and methods
Human hepatoma cells HepG2 were used to investigate the genotoxicity of different chemical structural classes of PAs, namely europine, lycopsamine, retrorsine, riddelliine, seneciphylline, echimidine and lasiocarpine, in the cytokinesis-block micronucleus (CBMN) assay. The different ester type PAs europine, seneciphylline, and lasiocarpine were also tested in human hepatoma Huh6 cells. Six different PAs were investigated in a crosslink comet assay in HepG2 cells.
Results
The maximal increase of micronucleus formation was for all PAs in the range of 1.64–2.0 fold. The lowest concentrations at which significant induction of micronuclei were found were 3.2 μM for lasiocarpine and riddelliine, 32 μM for retrorsine and echimidine, and 100 μM for seneciphylline, europine and lycopsamine. Significant induction of micronuclei by lasiocarpine, seneciphylline, and europine were achieved in Huh6 cells at similar concentrations. Reduced tail formation after hydrogen peroxide treatment was found in the crosslink comet assay for all diester type PAs, while an equimolar concentration of the monoesters europine and lycopsamine did not significantly reduce DNA migration.
Conclusion
The widely available human hepatoma cell lines HepG2 and Huh6 were suitable for the assessment of PA-induced genotoxicity. Selected PAs confirmed previously published potency rankings in the micronucleus assay. In HepG2 cells, the crosslinking activity was related to the ester type, which is a first report of PA mediated effects in the comet assay.}
}

@InCollection{Hartmann1995,
  author = {Hartmann, T. and Witte, L.},
  year = 1995,
  title = {Chemistry, Biology and Chemoecology of the Pyrrolizidine Alkaloids},
  booktitle = {Alkaloids: Chemical and Biological Perspectives},
  editor = {S.W. Pelletier}, 
  pages = {155-233},
  publisher = {Pergamon},
  address = {London, New York}
}

@article{Langel2011,
  author = {Langel, D. and Ober, D. and Pelser P.B.},
  year = 2011,
  title = {The evolution of pyrrolizidine alkaloid biosynthesis and diversity in the Senecioneae},
  jounrnal = {Phytochemistry Reviews},
  number = 10,
  pages = {3-74}
}

@article{Weininger1989,
  author = {David Weininger and Arthur Weininger and Joseph L. Weininger},
  title = {SMILES. 2. Algorithm for generation of unique SMILES notation},
  journal = {J. Chem. Inf. Comput. Sci.},
  year = 1989, 
  number = 29,
  pages = {97–101},
  doi = {https://doi.org/10.1021/ci00062a008},
}

@article{Willighagen2017,
  author = {Willighagen, E.L. and Mayfield, J.W. and Alvarsson, J. et al.},
  title = {The Chemistry Development Kit (CDK) v2.0: atom typing, depiction, molecular formulas, and substructure searching},
  journal = {J. Cheminform.},
  number =  {9(33)},
  year = 2017,
  doi = {https://doi.org/10.1186/s13321-017-0220-4}
}

@article{Schoening2017,
  author = {Verena Schöning and Felix Hammann and Mark Peinl and Jürgen Drewe},
  title = {Editor's Highlight: Identification of Any Structure-Specific Hepatotoxic Potential of Different Pyrrolizidine Alkaloids Using Random Forests and Artificial Neural Networks},
  journal = {Toxicol. Sci.},
  year = 2017,
  number = 160,
  pages = {361-370},
}

@article{EFSA2011,
  author = {EFSA},
  title = {Scientific Opinion on Pyrrolizidine alkaloids in food and feed},
  journal = {EFSA Journal},
  year = 2011,
  number = 9,
  pages = {1-134},
}

@book{Mattocks1986,
  author = {Mattocks, AR},
  title = {Chemistry and Toxicology of Pyrrolizidine Alkaloids},
  year = 1986,
  publisher = {Academic Press},
}

@article{Maaten2008,
  author = {van der Maaten, L.J.P. and Hinton, G.E.},
  title = {Visualizing Data Using t-SNE},
  journal = {Journal of Machine Learning Research},
  year = 2008,
  number = 9,
  pages = "2579–2605"
}

@article{Helma2018,
  author = { Christoph Helma and David Vorgrimmler and Denis Gebele and Martin Gütlein and Barbara Engeli and Jürg Zarn and Benoit Schilter and Elena Lo Piparo},
  title = "Modeling Chronic Toxicity: A comparison of experimental variability with {(Q)SAR}/read-across predictions",
  year = 2018,
  journal = {Frontiers in Pharmacology},
  number = 9,
  pages = "413",
}


@article{Benigni1988,
author = { R.   Benigni  and  A.   Giuliani },
title = {Computer‐assisted analysis of interlaboratory Ames test variability},
journal = {Journal of Toxicology and Environmental Health},
volume = {25},
number = {1},
pages = {135-148},
year  = {1988},
publisher = {Taylor & Francis},
doi = {10.1080/15287398809531194},
    note ={PMID: 3418743},

URL = { 
        https://doi.org/10.1080/15287398809531194
    
},
eprint = { 
        https://doi.org/10.1080/15287398809531194
    
}

}

@Article{Kazius2005,
  author = "Kazius, J. and McGuire, R. and Bursi, R.",
  year = 2005,
  title = "Derivation and validation of toxicophores for mutagenicity prediction",
  journal = "J Med Chem",
  number = 48,
  pages = "312-20",
}

@article{Hansen2009,
  author = {Hansen, Katja and Mika, Sebastian and Schroeter, Timon and Sutter, Andreas and ter Laak, Antonius and Steger-Hartmann, Thomas and Heinrich, Nikolaus and Müller, Klaus-Robert},
  title = {Benchmark Data Set for in Silico Prediction of Ames Mutagenicity},
  journal = {Journal of Chemical Information and Modeling},
  volume = {49},
  number = {9},
  pages = {2077-2081},
  year = {2009},
  doi = {10.1021/ci900161g},
  note ={PMID: 19702240},
  URL = { https://doi.org/10.1021/ci900161g },
  eprint = { https://doi.org/10.1021/ci900161g }
}

@article{Yap2011,
  author = "Yap, CW.",
  year = 2011,
  title = "PaDEL-descriptor: an open source software to calculate molecular descriptors and fingerprints",
  journal = "Journal of computational chemistry",
  number = 32,
  pages = "1466-74"
}

@Article{Bender2004,
  author =       "Andreas Bender and  Hamse Y. Mussa and Robert C.
                 Glen and Stephan Reiling",
  title =        "Molecular Similarity Searching Using Atom
                 Environments, Information-Based Feature Selection, and
                 a Naïve Bayesian Classifier",
  journal =      "Journal of Chemical Information and Computer
                 Sciences",
  volume =       "44",
  number =       "1",
  pages =        "170--178",
  year =         "2004",
  DOI =          "10.1021/ci034207y",
  note =         "PMID: 14741025",
  URL =          "http://dx.doi.org/10.1021/ci034207y",
  eprint =       "http://dx.doi.org/10.1021/ci034207y",
}

@article{OBoyle2011a,
  abstract = {{BACKGROUND: A frequent problem in computational modeling is the interconversion of chemical structures between different formats. While standard interchange formats exist (for example, Chemical Markup Language) and de facto standards have arisen (for example, SMILES format), the need to interconvert formats is a continuing problem due to the multitude of different application areas for chemistry data, differences in the data stored by different formats (0D versus 3D, for example), and competition between software along with a lack of vendor-neutral formats.RESULTS: We discuss, for the first time, Open Babel, an open-source chemical toolbox that speaks the many languages of chemical data. Open Babel version 2.3 interconverts over 110 formats. The need to represent such a wide variety of chemical and molecular data requires a library that implements a wide range of cheminformatics algorithms, from partial charge assignment and aromaticity detection, to bond order perception and canonicalization. We detail the implementation of Open Babel, describe key advances in the 2.3 release, and outline a variety of uses both in terms of software products and scientific research, including applications far beyond simple format interconversion.CONCLUSIONS: Open Babel presents a solution to the proliferation of multiple chemical file formats. In addition, it provides a variety of useful utilities from conformer searching and 2D depiction, to filtering, batch conversion, and substructure and similarity searching. For developers, it can be used as a programming library to handle chemical data in areas such as organic chemistry, drug design, materials science, and computational chemistry. It is freely available under an open-source license from http://openbabel.org.}},
  added-at = {2019-03-11T21:00:05.000+0100},
  author = {O'Boyle, Noel and Banck, Michael and James, Craig and Morley, Chris and Vandermeersch, Tim and Hutchison, Geoffrey},
  biburl = {https://www.bibsonomy.org/bibtex/27ab2699fef73132efcfa6853c3031bf0/fairybasslet},
  booktitle = {Journal of Cheminformatics},
  citeulike-article-id = {9866193},
  citeulike-linkout-0 = {http://dx.doi.org/doi:10.1186/1758-2946-3-33},
  citeulike-linkout-1 = {http://www.jcheminf.com/content/3/1/33},
  citeulike-linkout-2 = {http://dx.doi.org/10.1186/1758-2946-3-33},
  citeulike-linkout-3 = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3198950/},
  citeulike-linkout-4 = {http://view.ncbi.nlm.nih.gov/pubmed/21982300},
  citeulike-linkout-5 = {http://www.hubmed.org/display.cgi?uids=21982300},
  citeulike-linkout-6 = {http://link.springer.com/article/10.1186/1758-2946-3-33},
  day = 07,
  doi = {doi:10.1186/1758-2946-3-33},
  interhash = {c20842ab14c8a3bbd2dcf3e8072b82d1},
  intrahash = {7ab2699fef73132efcfa6853c3031bf0},
  issn = {1758-2946},
  journal = {J. Cheminf.},
  keywords = {chemical-file-formats computer-program cpsst open-babel open-source software-library toolkit},
  month = oct,
  number = 1,
  pages = 33,
  pdf = {file:///H:/publications/OBoyle2011a.pdf},
  pmcid = {PMC3198950},
  pmid = {21982300},
  posted-at = {2011-11-08 10:20:24},
  priority = {2},
  publisher = {Chemistry Central Ltd},
  timestamp = {2019-03-11T21:06:37.000+0100},
  title = {{Open Babel: An open chemical toolbox}},
  url = {http://www.jcheminf.com/content/3/1/33},
  volume = 3,
  year = 2011
}

@article{Rücker2007,
  author = "Rücker, C and Rücker, G and Meringer, M.",
  year = 2007,
  title = "y-Randomization and Its Variants in QSPR/QSAR",
  journal = "J. Chem. Inf. Model.",
  number = 47,
  pages = "2345-57"
}

@Article{Maunz2013,
  DOI =          "10.3389/fphar.2013.00038",
  URL =          "http://dx.doi.org/10.3389/fphar.2013.00038",
  year =         "2013",
  publisher =    "Frontiers Media {SA}",
  volume =       "4",
  author =       "Andreas Maunz and Martin G{\"{u}}tlein and Micha
                 Rautenberg and David Vorgrimmler and Denis Gebele and
                 Christoph Helma",
  title =        "lazar: a modular predictive toxicology framework",
  journal =      "Frontiers in Pharmacology",
}

@Article{doi:10.1021/ci00057a005,
  author =       "David Weininger",
  title =        "SMILES, a chemical language and information system. 1.
                 Introduction to methodology and encoding rules",
  journal =      "Journal of Chemical Information and Computer
                 Sciences",
  volume =       "28",
  number =       "1",
  pages =        "31--36",
  year =         "1988",
  DOI =          "10.1021/ci00057a005",
  URL =          "http://dx.doi.org/10.1021/ci00057a005",
  eprint =       "http://dx.doi.org/10.1021/ci00057a005",
}

@Article{OBoyle2011,
  DOI =          "10.1186/1758-2946-3-33",
  URL =          "http://dx.doi.org/10.1186/1758-2946-3-33",
  year =         "2011",
  publisher =    "Springer Science and Business Media",
  volume =       "3",
  number =       "1",
  pages =        "33",
  author =       "Noel M OBoyle and Michael Banck and Craig A James and
                 Chris Morley and Tim Vandermeersch and Geoffrey R
                 Hutchison",
  title =        "Open Babel: An open chemical toolbox",
  journal =      "Journal of Cheminformatics",
}

@Article{mazzatorta08,
  author =       "Paolo Mazzatorta and Manuel Dominguez Estevez and
                 Myriam Coulet and Benoit Schilter",
  title =        "Modeling Oral Rat Chronic Toxicity",
  journal =      "Journal of Chemical Information and Modeling",
  volume =       "48",
  number =       "10",
  pages =        "1949--1954",
  year =         "2008",
  DOI =          "10.1021/ci8001974",
  note =         "PMID: 18803370",
  URL =          "http://dx.doi.org/10.1021/ci8001974",
  eprint =       "http://dx.doi.org/10.1021/ci8001974",
}

@Manual{pls,
  title =        "pls: Partial Least Squares and Principal Component
                 Regression",
  author =       "Bjørn-Helge Mevik and Ron Wehrens and Kristian Hovde
                 Liland",
  year =         "2015",
  note =         "R package version 2.5-0",
  URL =          "https://CRAN.R-project.org/package=pls",
}

@Article{Kuhn08,
  author =       "Max Kuhn",
  title =        "Building predictive models in R using the caret
                 package",
  journal =      "J. of Stat. Soft",
  year =         "2008",
}

@Article{Jeliazkova15,
  author =       "Nina Jeliazkova and Charalampos Chomenidis and Philip
                 Doganis and Bengt Fadeel and Roland Grafström and
                 Barry Hardy and Janna Hastings and Markus Hegi and
                 Vedrin Jeliazkov and Nikolay Kochev and Pekka Kohonen
                 and Cristian R. Munteanu and Haralambos Sarimveis and
                 Bart Smeets and Pantelis Sopasakis and Georgia Tsiliki
                 and David Vorgrimmler and Egon Willighagen",
  title =        "The eNanoMapper database for nanomaterial safety
                 information",
  journal =      "Beilstein J. Nanotechnol.",
  pages =        "1609–1634",
  number =       "6",
  year =         "2015",
  DOI =          "doi:10.3762/bjnano.6.165",
}

@TechReport{Fowler2011,
  author =       "B. Fowler and S. Savage and B. Mendez",
  year =         "2011",
  title =        "White paper: Protecting public health in the 21st
                 century: the case for computational toxicology",
  institution =  "ICF International, Inc.icfi.com.",
}

@Article{Cotterill2008,
  author =       "Cotterill, J.V. and Chaudry, M.Q. and Mattews, W. and R.
                 W. Watkins",
  year =         "2008",
  title =        "In silico assessment of toxicity of heat-generated
                 food contaminants",
  journal =      "Food Chemical Toxicology",
  number =       "46(6)",
  pages =        "1905--1918",
}

@Article{Grob2006,
  author =       "Grob, K. and Biedermann, M. and Scherbaum, E. and Roth, M.
                 and K. Rieger",
  year =         "2006",
  title =       "Food contamination with organic materials in
                 perspective: packaging materials as the largest and
                 least controlled source? A view focusing on the
                 European situation",
  journal =      "Crit. Rev. Food. Sci. Nutr.",
  number =       "46",
  pages =        "529--35",
  DOI =          "10.1080/10408390500295490",
}

@Article{LoPiparo2011,
  author =       "Lo Piparo, E. and Worth, A. and Manibusan, A. and Yang, C. and
                 Schilter, B. and Mazzatorta, P. and Jacobs, M.N. and
                 Steinkelner, H. and L. Mohimont",
  year =         "2011",
  title =        "Use of Computational tools in the field of food
                 safety",
  journal =      "Regulatory Toxicology and Pharmacology",
  number =       "60(3)",
  pages =        "354--362",
}

@Article{LoPiparo2014,
  author =       "Lo Piparo, E. and Maunz, A. and Helma, C. and Vorgrimmler, D. and Schilter, B.",
  year =         "2014",
  title =        "Automated and reproducible read-across like models for
                 predicting carcinogenic potency",
  journal =      "Regulatory Toxicology and Pharmacology",
  number =       "70",
  pages =        "370--378",
}

@Article{Schilter2014,
  author =       "Schilter, B. and Benigni, R. and Boobis, A. and Chiodini, A. and
                 Cockburn, A. and Cronin, M.T. and Lo Piparo, E. and Modi, S. and
                 Thiel A. and A. Worth",
  title =        "Establishing the level of safety concern for chemicals
                 in food without the need for toxicity testing",
  year =         "2014",
  journal =      "Regulatory Toxicology and Pharmacology",
  number =       "68",
  pages =        "275--298",
}

@Article{Stanton2016,
  author =       "Stanton, K. and F.H. Krusezewski",
  year =         "2016",
  title =        "Quantifying the benefits of using read-across and in
                 silico techniques to fullfill hazard data requirements
                 for chemical categories",
  journal =      "Regulatory Toxicology and Pharmacology",
  number =       "81",
  pages =        "250--259",
  DOI =          "10.1016/j-yrtph.2016.09.004.",
}

@Article{Zarn2011,
  author =       "Zarn, J.A. and B.E. Engeli and J.R. Schlatter",
  year =         "2011",
  title =        "Study parameters influencing {NOAEL} and {LOAEL} in
                 toxicity feeding studies for pesticides: exposure
                 duration versus dose decrement, dose spacing, group
                 size and chemical class",
  journal =      "Regul. Toxicol. Pharmacol.",
  number =       "61",
  pages =        "243--250",
}

@Article{Zarn2013,
  author =       "J.A. Zarn and B.E. Engeli and J.R. Schlatter",
  year =         "2013",
  title =        "Characterization of the dose decrement in regulatory
                 rat pesticide toxicity feeding studies",
  journal =      "Regul. Toxicol. Pharmacol.",
  number =       "67",
  pages =        "215--220",
}

@Article{EFSA2016,
  author =       {EFSA},
  year =         "2016",
  title =        "Guidance on the establishment of the residue
                  definition for dietary assessment: {EFSA} panel on Plant
                  Protect Products and their Residues ({PPR})",
  journal =      "EFSA Journal",
  number =       "14",
  pages =        "1--12",
}

@TechReport{ECHA2008,
  author =       "{ECHA}",
  year =         "2008",
  title =        "Guidance on information requirements and chemical
                  safety assessment, Chapter R.6: {QSARs} and grouping of
                 chemicals",
  institution =  "ECHA",
}

@Misc{EFSA2014,
  author =       "{EFSA}",
  year =         "2014",
  title =        "Rapporteur Member State assessment reports submitted
                 for the {EU} peer review of active substances used in
                 plant protection products",
  URL =          "http://dar.efsa.europa.eu/dar-web/provision",
  note =         "accessed 8.1.2015",
}

@Misc{HealthCanada2016,
  author =       "{Health Canada}",
  year =         "2016",
  URL =          "https://www.canada.ca/en/health-canada/services/chemical-substances/chemicals-management-plan.html",
}

@InCollection{OECD2015,
  author =       "{OECD}",
  year =         "2015",
  title =        "Fundamental and guiding principles for {(Q)SAR} analysis
                 of chemicals carcinogens with mechanistic
                 considerations Monograph 229 {ENV/JM/MONO(2015)46}",
  chapter =      "229",
  booktitle =    "Series on Testing and Assessment No 229",
}

@InCollection{Schilter2013,
  author =       "Schilter, B. and Constable, A. and Perrin, I.",
  title =        "Naturally occurring toxicants of plant origin: risk
                 assessment and management considerations",
  year =         "2013",
  booktitle =    "Food Safety Management: a practical guide for
                 industry",
  chapter =      "3",
  editor =       "Y. Motarjemi",
  publisher =    "Elsevier",
  pages =        "45--57",
}

@Misc{EPA2011,
  title =        "Fact Sheets on New Active Ingredients",
  author =       "{US EPA}",
  year =         "2011",
  note =         "this database was not further maintained by US EPA.
                 Only data used until 27.11.2014, accessed 27.4.11
                 A.D.",
}

@TechReport{WHO2011,
  author =       "WHO",
  year =         "2011",
  title =        "Joint {FAO/WHO} Meeting on Pesticide Residues ({JMPR})
                 publications",
  URL =          "http://www.who.int/foodsafety/publications/jmpr-monographs/en/",
  note =         "accessed 20.3.15 A.D.",
}