Deposition of Energy

13674-87-8

ASLWPAWFJZFCKF-UHFFFAOYSA-N

Tris(1,3-dichloro-2-propyl) phosphate

Tris(1,3-dichloro-2-propyl)phosphate 2-Propanol, 1,3-dichloro-, phosphate (3:1)

DTXSID9026261

PCO:0000001

PCO population of organisms

VT:1000294

VT egg quantity

PCO:0000008

PCO population growth rate

WIKI decreased

Gamma radiation

2017-04-15T16:04:31

Ionizing Radiation Ionizing radiation can vary in energy, dose, charge, and in the spatial distributions of energy transferred to other matter (linear energy transfer per unit length or LET) (ICRU 1970). At the same dose, low and high LET both generate energy deposition events, including many higher energy events (Goodhead and Nikjoo 1989). However, they differ in the spatial distribution and upper range of intensity of energy deposited. Lower LET such as gamma rays sparsely deposit many individual excitations or small clusters of excitations of low energy (Goodhead 1988). In contrast, high LET such as alpha particles have fewer tracks but readily transfer their energy to matter and therefore deposit their energy over a much smaller area (Goodhead 1994). Consequently, alpha and other high LET particles penetrate less deeply into tissue, interactions are densely focused on a narrow track, and individual energy depositions can be large (Goodhead 1988). These different energy deposition patterns can lead to differences in radiation effects including the pattern of DNA damage.

Exposure to ionizing radiation can come from natural and industrial sources. Space and terrestrial radiation includes a range of LET particles, while diagnostic radiation methods such as X-ray imaging, mammography and CT scans use low LET X-rays. Radiation therapy can use an external beam to direct radiation on a focused tissue area, or deposit solid or liquid radioactive materials in the body that release (mostly gamma) radiation internally. External radiotherapy typically uses X-rays but is moving towards higher LET charged particles such as protons and heavy ions (Durante, Orecchia et al. 2017).

2019-05-03T12:36:36

2019-05-07T12:12:13

Topoisomerase inhibitors

2019-05-19T20:21:24

Radiomimetic compounds

2019-05-19T20:21:42

Tris(1,3-dichloropropyl)phosphate - TDCPP

2018-06-19T07:35:30

2018-06-19T07:59:12

WCS_9606

common toxicological species human

10116

NCBI rat

10090

NCBI mouse

6239

NCBI nematode

WCS_7955

common ecological species zebrafish

3702

NCBI thale-cress

3349

NCBI Scotch pine

WCS_35525

common ecological species Daphnia magna

3055

NCBI Chlamydomonas reinhardtii

WCS_6396

common ecological species common brandling worm

WCS_4472

common ecological species Lemna minor

8030

NCBI Salmo salar

WikiUser_25

Wikiuser: Cyauk human and other cells in culture

WCS_90988

common ecological species fathead minnow

8078

NCBI Fundulus heteroclitus

8090

NCBI Oryzias latipes

WikiUser_22

all species

10095

NCBI mice

9913

NCBI bovine

WCS_9986

common toxicological species rabbit

WikiUser_24

Wikiuser:Migration Pig

Deposition of Energy

Energy Deposition

Molecular

Deposition of energy refers to events where energetic subatomic particles, nuclei, or electromagnetic radiation deposit energy in the media through which they transverse. The energy may either be sufficient (e.g. ionizing radiation) or insufficient (e.g. non-ionizing radiation) to ionize atoms or molecules (Beir et al.,1999).   Ionizing radiation can cause the ejection of electrons from atoms and molecules, thereby resulting in their ionization and the breakage of chemical bonds. The energy of these subatomic particles or electromagnetic waves mostly range from 124 KeV to 5.4 MeV and is dependent on the source and type of radiation (Zyla et al., 2020). To be ionizing the incident radiation must have sufficient energy to free electrons from atomic or molecular electron orbitals. The energy deposited can induce direct and indirect ionization events and this can be via internal (injections, inhalation, or absorption of radionuclides) or external exposure from radiation fields -- this also applies to non-ionizing radiation. Direct ionization is the principal path where charged particles interact with biological structures such as DNA, proteins or membranes to cause biological damage. Photons, which are electromagnetic waves can also deposit energy to cause direct ionization. Ionization of water, which is a major constituent of tissues and organs, produces free radical and molecular species, which themselves can indirectly damage critical targets such as DNA (Beir et al., 1999; Balagamwala et al., 2013) or alter cellular processes. Given the fundamental nature of energy deposition by radioactive/unstable nuclei, nucleons or elementary particles in material, this process is universal to all biological contexts. The spatial structure of ionizing energy deposition along the resulting particle track is represented as linear energy transfer (LET) (Hall and Giaccia, 2018 UNSCEAR, 2020). High LET refers to energy mostly above 10 keV μm-1 which produces more complex, dense structural damage than low LET radiation (below 10 keV μm-1). Low-LET particles produce sparse ionization events such as photons (X- and gamma rays), as well as high-energy protons. Low LET radiation travels farther into tissue but deposits smaller amounts of energy, whereas high LET radiation, which includes heavy ions, alpha particles and high-energy neutrons, does not travel as far but deposits larger amounts of energy into tissue at the same absorbed dose. The biological effect of the deposition of energy can be modulated by varying dose and dose rate of exposure, such as acute, chronic, or fractionated exposures (Hall and Giaccia, 2018). Non-ionizing radiation is electromagnetic waves that does not have enough energy to break bonds and induce ion formation but it can cause molecules to excite and vibrate faster resulting in biological effects. Examples of non-ionizing radiation include radio waves (wavelength: 100 km-1m), microwaves (wavelength: 1m-1mm), infrared radiation (wavelength: 1mm- 1 um), visible light (wavelengths: 400-700 nm), and ultraviolet radiation of longer wavelengths such as UVB (wavelengths: 315-400nm) and UVA (wavelengths: 280-315 nm). UVC radiation (200-280 nm) is, in contrast to UVB and UVA, considered to be a type of ionizing radiation.

<table border="1" bordercolor="#ccc" cellpadding="5" cellspacing="0" style="border-collapse:collapse"> <tbody> <tr> <td style="background-color:#eeeeee; text-align:center">Radiation type</td> <td style="background-color:#eeeeee; text-align:center"> Assay Name </td> <td style="background-color:#eeeeee; text-align:center"> References </td> <td style="background-color:#eeeeee; text-align:center"> Description </td> <td style="background-color:#eeeeee; text-align:center"> OECD Approved Assay </td> </tr> <tr> <td style="text-align:center">Ionizing radiation</td> <td style="text-align:center"> Monte Carlo Simulations (Geant4) </td> <td style="text-align:center"> Douglass et al., 2013; Douglass et al. 2012; Zyla et al., 2020 </td> <td style="text-align:center"> Monte Carlo simulations are based on a computational algorithm that mathematically models the deposition of energy into materials. </td> <td style="text-align:center"> No </td> </tr> <tr> <td style="text-align:center">Ionizing radiation</td> <td style="text-align:center"> Fluorescent Nuclear Track Detector (FNTD) </td> <td style="text-align:center"> Sawakuchi, 2016; Niklas, 2013; Koaira & Konishi, 2015 </td> <td style="text-align:center"> FNTDs are biocompatible chips with crystals of aluminium oxide doped with carbon and magnesium; used in conjuction with fluorescent microscopy, these FNTDs allow for the visualization and the linear energy transfer (LET) quantification of tracks produced by the deposition of energy into a material. </td> <td style="text-align:center"> No </td> </tr> <tr> <td style="text-align:center">Ionizing radiation</td> <td style="text-align:center">Tissue equivalent proportional counter (TEPC)</td> <td style="text-align:center">Straume et al, 2015</td> <td style="text-align:center">Measure the LET spectrum and calculate the dose equivalent.</td> <td style="text-align:center">No</td> </tr> <tr> <td style="text-align:center">Ionizing radiation</td> <td style="text-align:center">alanine dosimeters/NanoDots</td> <td style="text-align:center"> Lind et al. 2019; Xie et al., 2022 </td> <td style="text-align:center"> </td> <td style="text-align:center">No</td> </tr> <tr> <td style="text-align:center">Non-ionizing radiation</td> <td style="text-align:center">UV meters or radiameters</td> <td style="text-align:center">Xie et at., 2020</td> <td style="text-align:center">UVA/UVB (irradiance intensity), UV dosimeters (accumulated irradiance over time), Spectrophoto meter (absorption of UV by a substance or material)</td> <td style="text-align:center">No</td> </tr> </tbody> </table>

Energy can be deposited into any substrate, both living and non-living; it is independent of age, taxa, sex, or life-stage. Taxonomic applicability: This MIE is not taxonomically specific.   Life stage applicability: This MIE is not life stage specific.  Sex applicability: This MIE is not sex specific.

Low Unspecific

High

All life stages

Moderate Moderate Moderate High High High Moderate High Moderate Moderate High Low Balagamwala, E. H. et al. (2013), “Introduction to radiotherapy and standard teletherapy techniques”, Dev Ophthalmol, Vol. 52, Karger, Basel, https://doi.org/10.1159/000351045  Beir, V. et al. (1999), “The Mechanistic Basis of Radon-Induced Lung Cancer”, in Health Risks of Exposure to Radon: BEIR VI, National Academy Press, Washington, D.C., https://doi.org/10.17226/5499  Douglass, M. et al. (2013), “Monte Carlo investigation of the increased radiation deposition due to gold nanoparticles using kilovoltage and megavoltage photons in a 3D randomized cell model”, Medical Physics, Vol. 40/7, American Institute of Physics, College Park, https://doi.org/10.1118/1.4808150  Douglass, M. et al. (2012), “Development of a randomized 3D cell model for Monte Carlo microdosimetry simulations.”, Medical Physics, Vol. 39/6, American Institute of Physics, College Park, https://doi.org/10.1118/1.4719963  Hall, E. J. and Giaccia, A.J. (2018), Radiobiology for the Radiologist, 8th edition, Wolters Kluwer, Philadelphia.   Kodaira, S. and Konishi, T. (2015), “Co-visualization of DNA damage and ion traversals in live mammalian cells using a fluorescent nuclear track detector.”, Journal of Radiation Research, Vol. 56/2, Oxford University Press, Oxford, https://doi.org/10.1093/jrr/rru091  Lind, O.C., D.H. Oughton and Salbu B. (2019), "The NMBU FIGARO low dose irradiation facility", International Journal of Radiation Biology, Vol. 95/1, Taylor & Francis, London, https://doi.org/10.1080/09553002.2018.1516906. Sawakuchi, G.O. and Akselrod, M.S. (2016), “Nanoscale measurements of proton tracks using fluorescent nuclear track detectors.”, Medical Physics, Vol. 43/5, American Institute of Physics, College Park, https://doi.org/10.1118/1.4947128  Straume, T. et al. (2015), “Compact Tissue-equivalent Proportional Counter for Deep Space Human Missions.”, Health physics, Vol. 109/4, Lippincott Williams & Wilkins, Philadelphia, https://doi.org/10.1097/HP.0000000000000334  Niklas, M. et al. (2013), “Engineering cell-fluorescent ion track hybrid detectors.”, Radiation Oncology, Vol. 8/104, BioMed Central, London, https://doi.org/10.1186/1748-717X-8-141  UNSCEAR (2020), Sources, effects and risks of ionizing radiation, United Nations.  Xie, Li. et al. (2022), "Ultraviolet B Modulates Gamma Radiation-Induced Stress Responses in Lemna Minor at Multiple Levels of Biological Organisation", SSRN, Elsevier, Amsterdam, http://dx.doi.org/10.2139/ssrn.4081705 . Zyla, P.A. et al. (2020), Review of particle physics: Progress of Theoretical and Experimental Physics, 2020 Edition, Oxford University Press, Oxford.      AOPWiki 2019-08-22T09:44:23

2023-08-09T15:06:01

Increase, DNA strand breaks

Molecular

DNA strand breaks can occur on a single strand (SSB) or both strands (double strand breaks; DSB). SSBs arise when the phosphate backbone connecting adjacent nucleotides in DNA is broken on one strand. DSBs are generated when both strands are simultaneously broken at sites that are sufficiently close to one another that base-pairing and chromatin structure are insufficient to keep the two DNA ends juxtaposed. As a consequence, the two DNA ends generated by a DSB can physically dissociate from one another, becoming difficult to repair and increasing the chance of inappropriate recombination with other sites in the genome (Jackson, 2002). SSB can turn into DSB if the replication fork stalls at the lesion leading to fork collapse. Strand breaks are intermediates in various biological events, including DNA repair (e.g., excision repair), V(D)J recombination in developing lymphoid cells and chromatin remodeling in both somatic cells and germ cells. The spectrum of damage  can be complex, particularily if the stressor is from large amounts of deposited energy which can result in complex lesions and clustered damage defined as two or more oxidized bases, abasic sites or starnd breaks on opposing DNA strands within a few helical turns. These lesions are more difficult to repair and have been studied in many types of models  (Barbieri et al., 2019 and Asaithamby et al., 2011). DSBs and complex lesions  are of particular concern, as they are considered the most lethal and deleterious type of DNA lesion. If misrepaired or left unrepaired, DSBs may drive the cell towards genomic instability, apoptosis or tumorigenesis (Beir, 1999).

Please refer to the table below for details regarding these and other methodologies for detecting DNA DSBs.   <table cellspacing="0" class="Table" style="border-collapse:collapse; border:none; margin-left:15px"> <tbody> <tr> <td style="background-color:whitesmoke; border-bottom:1px double #2b2b2b; border-left:1px double #2b2b2b; border-right:1px double #2b2b2b; border-top:1px double #2b2b2b; height:37px; vertical-align:top; width:85px"> Assay Name </td> <td style="background-color:whitesmoke; border-bottom:1px double #2b2b2b; border-left:none; border-right:1px double #2b2b2b; border-top:1px double #2b2b2b; height:37px; vertical-align:top; width:89px"> References </td> <td style="background-color:whitesmoke; border-bottom:1px double #2b2b2b; border-left:none; border-right:1px double #2b2b2b; border-top:1px double #2b2b2b; height:37px; vertical-align:top; width:228px"> Description </td> <td style="background-color:whitesmoke; border-bottom:1px double #2b2b2b; border-left:none; border-right:1px double #7f7f7f; border-top:1px double #2b2b2b; height:37px; vertical-align:top; width:46px"> OECD Approved Assay </td> </tr> <tr> <td style="background-color:whitesmoke; border-bottom:1px double #2b2b2b; border-left:1px double #2b2b2b; border-right:1px double #2b2b2b; border-top:none; height:61px; vertical-align:top; width:85px"> Comet Assay (Single Cell Gel Eletrophoresis - Alkaline) </td> <td style="background-color:whitesmoke; border-bottom:1px double #2b2b2b; border-left:none; border-right:1px double #2b2b2b; border-top:none; height:61px; vertical-align:top; width:89px"> Collins, 2004; Olive and Banath, 2006; Platel et al., 2011; Nikolova et al., 2017 </td> <td style="background-color:whitesmoke; border-bottom:1px double #2b2b2b; border-left:none; border-right:1px double #2b2b2b; border-top:none; height:61px; vertical-align:top; width:228px"> To detect SSBs or DSBs, single cells are encapsulated in agarose on a slide, lysed, and subjected to gel electrophoresis at an alkaline pH (pH >13); DNA fragments are forced to move, forming a "comet"-like appearance </td> <td style="background-color:whitesmoke; border-bottom:1px double #2b2b2b; border-left:none; border-right:1px double #7f7f7f; border-top:none; height:61px; vertical-align:top; width:46px"> Yes (No. 489) </td> </tr> <tr> <td style="background-color:whitesmoke; border-bottom:1px double #2b2b2b; border-left:1px double #2b2b2b; border-right:1px double #2b2b2b; border-top:none; height:61px; vertical-align:top; width:85px"> Comet Assay (Single Cell Gel Eltrophoresis - Neutral) </td> <td style="background-color:whitesmoke; border-bottom:1px double #2b2b2b; border-left:none; border-right:1px double #2b2b2b; border-top:none; height:61px; vertical-align:top; width:89px"> Collins, 2014; Olive and Banath, 2006; Anderson and Laubenthal, 2013; Nikolova et al., 2017 </td> <td style="background-color:whitesmoke; border-bottom:1px double #2b2b2b; border-left:none; border-right:1px double #2b2b2b; border-top:none; height:61px; vertical-align:top; width:228px"> To detect DSBs, single cells are encapsulated in agarose on a slide, lysed, and subjected to gel electrophoresis at a neutral pH; DNA fragments, which are not denatured at the neutral pH, are forced to move, forming a "comet"-like appearance </td> <td style="background-color:whitesmoke; border-bottom:1px double #2b2b2b; border-left:none; border-right:1px double #7f7f7f; border-top:none; height:61px; vertical-align:top; width:46px"> N/A </td> </tr> <tr> <td style="background-color:whitesmoke; border-bottom:1px double #2b2b2b; border-left:1px double #2b2b2b; border-right:1px double #2b2b2b; border-top:none; height:37px; vertical-align:top; width:85px"> γ-H2AX Foci Quantification - Flow Cytometry </td> <td style="background-color:whitesmoke; border-bottom:1px double #2b2b2b; border-left:none; border-right:1px double #2b2b2b; border-top:none; height:37px; vertical-align:top; width:89px"> Rothkamm and Horn, 2009; Bryce et al., 2016 </td> <td style="background-color:whitesmoke; border-bottom:1px double #2b2b2b; border-left:none; border-right:1px double #2b2b2b; border-top:none; height:37px; vertical-align:top; width:228px"> Measurement of γ-H2AX immunostaining in cells by flow cytometry, normalized to total levels of H2AX </td> <td style="background-color:whitesmoke; border-bottom:1px double #2b2b2b; border-left:none; border-right:1px double #7f7f7f; border-top:none; height:37px; vertical-align:top; width:46px"> N/A </td> </tr> <tr> <td style="background-color:whitesmoke; border-bottom:1px double #2b2b2b; border-left:1px double #2b2b2b; border-right:1px double #2b2b2b; border-top:none; height:37px; vertical-align:top; width:85px"> γ-H2AX Foci Quantification - Western Blot </td> <td style="background-color:whitesmoke; border-bottom:1px double #2b2b2b; border-left:none; border-right:1px double #2b2b2b; border-top:none; height:37px; vertical-align:top; width:89px"> Burma et al., 2001; Revet et al., 2011 </td> <td style="background-color:whitesmoke; border-bottom:1px double #2b2b2b; border-left:none; border-right:1px double #2b2b2b; border-top:none; height:37px; vertical-align:top; width:228px"> Measurement of γ-H2AX immunostaining in cells by Western blotting, normalized to total levels of H2AX </td> <td style="background-color:whitesmoke; border-bottom:1px double #2b2b2b; border-left:none; border-right:1px double #7f7f7f; border-top:none; height:37px; vertical-align:top; width:46px"> N/A </td> </tr> <tr> <td style="background-color:whitesmoke; border-bottom:1px double #2b2b2b; border-left:1px double #2b2b2b; border-right:1px double #2b2b2b; border-top:none; height:49px; vertical-align:top; width:85px"> γ-H2AX Foci Quantification - Microscopy </td> <td style="background-color:whitesmoke; border-bottom:1px double #2b2b2b; border-left:none; border-right:1px double #2b2b2b; border-top:none; height:49px; vertical-align:top; width:89px"> Redon et al., 2010; Mah et al., 2010; Garcia-Canton et al., 2013 </td> <td style="background-color:whitesmoke; border-bottom:1px double #2b2b2b; border-left:none; border-right:1px double #2b2b2b; border-top:none; height:49px; vertical-align:top; width:228px"> Quantification of γ-H2AX immunostaining by counting γ- H2AX foci visualized with a microscope </td> <td style="background-color:whitesmoke; border-bottom:1px double #2b2b2b; border-left:none; border-right:1px double #7f7f7f; border-top:none; height:49px; vertical-align:top; width:46px"> N/A </td> </tr> <tr> <td style="background-color:whitesmoke; border-bottom:1px double #2b2b2b; border-left:1px double #2b2b2b; border-right:1px double #2b2b2b; border-top:none; height:37px; vertical-align:top; width:85px"> γ-H2AX Foci Detection - ELISA and flow cytometry </td> <td style="background-color:whitesmoke; border-bottom:1px double #2b2b2b; border-left:none; border-right:1px double #2b2b2b; border-top:none; height:37px; vertical-align:top; width:89px"> Ji et al., 2017; Bryce et al., 2016 </td> <td style="background-color:whitesmoke; border-bottom:1px double #2b2b2b; border-left:none; border-right:1px double #2b2b2b; border-top:none; height:37px; vertical-align:top; width:228px"> Detection of γ-H2AX in cells by ELISA, normalized to total levels of H2AX; γH2AX foci detection can be high-throughput and automated using flow cytometry-based immunodetection. </td> <td style="background-color:whitesmoke; border-bottom:1px double #2b2b2b; border-left:none; border-right:1px double #7f7f7f; border-top:none; height:37px; vertical-align:top; width:46px"> N/A </td> </tr> <tr> <td style="background-color:whitesmoke; border-bottom:1px double #2b2b2b; border-left:1px double #2b2b2b; border-right:1px double #2b2b2b; border-top:none; height:61px; vertical-align:top; width:85px"> Pulsed Field Gel Electrophoresis (PFGE) </td> <td style="background-color:whitesmoke; border-bottom:1px double #2b2b2b; border-left:none; border-right:1px double #2b2b2b; border-top:none; height:61px; vertical-align:top; width:89px"> Ager et al., 1990; Gardiner et al., 1985; Herschleb et al., 2007; Kawashima et al., 2017 </td> <td style="background-color:whitesmoke; border-bottom:1px double #2b2b2b; border-left:none; border-right:1px double #2b2b2b; border-top:none; height:61px; vertical-align:top; width:228px"> To detect DSBs, cells are embedded and lysed in agarose, and the released DNA undergoes gel electrophoresis in which the direction of the voltage is periodically alternated; Large DNA fragments are thus able to be separated by size </td> <td style="background-color:whitesmoke; border-bottom:1px double #2b2b2b; border-left:none; border-right:1px double #7f7f7f; border-top:none; height:61px; vertical-align:top; width:46px"> N/A </td> </tr> <tr> <td style="background-color:whitesmoke; border-bottom:1px double #2b2b2b; border-left:1px double #2b2b2b; border-right:1px double #2b2b2b; border-top:none; height:73px; vertical-align:top; width:85px"> The TUNEL (Terminal Deoxynucleotidyl Transferase dUTP Nick End Labeling) Assay </td> <td style="background-color:whitesmoke; border-bottom:1px double #2b2b2b; border-left:none; border-right:1px double #2b2b2b; border-top:none; height:73px; vertical-align:top; width:89px"> Loo, 2011 </td> <td style="background-color:whitesmoke; border-bottom:1px double #2b2b2b; border-left:none; border-right:1px double #2b2b2b; border-top:none; height:73px; vertical-align:top; width:228px"> To detect strand breaks, dUTPs added to the 3’OH end of a strand break by the DNA polymerase terminal deoxynucleotidyl transferase (TdT) are tagged with a fluorescent dye or a reporter enzyme to allow visualization (We note that this method is typically used to measure apoptosis) </td> <td style="background-color:whitesmoke; border-bottom:1px double #2b2b2b; border-left:none; border-right:1px double #7f7f7f; border-top:none; height:73px; vertical-align:top; width:46px"> N/A </td> </tr> <tr> <td style="background-color:whitesmoke; border-bottom:1px double #7f7f7f; border-left:1px double #2b2b2b; border-right:1px double #2b2b2b; border-top:none; height:49px; vertical-align:top; width:85px"> In Vitro DNA Cleavage Assays using Topoisomerase </td> <td style="background-color:whitesmoke; border-bottom:1px double #7f7f7f; border-left:none; border-right:1px double #2b2b2b; border-top:none; height:49px; vertical-align:top; width:89px"> Nitiss, 2012 </td> <td style="background-color:whitesmoke; border-bottom:1px double #7f7f7f; border-left:none; border-right:1px double #2b2b2b; border-top:none; height:49px; vertical-align:top; width:228px"> Cleavage of DNA can be achieved using purified topoisomerase; DNA strand breaks can then be separated and quantified using gel electrophoresis </td> <td style="background-color:whitesmoke; border-bottom:1px double #7f7f7f; border-left:none; border-right:1px double #7f7f7f; border-top:none; height:49px; vertical-align:top; width:46px"> N/A </td> </tr> <tr> <td style="background-color:whitesmoke; border-bottom:1px double #7f7f7f; border-left:1px double #2b2b2b; border-right:1px double #2b2b2b; border-top:none; height:49px; text-align:center; vertical-align:top; width:85px">PCR assay </td> <td style="background-color:whitesmoke; border-bottom:1px double #7f7f7f; border-left:none; border-right:1px double #2b2b2b; border-top:none; height:49px; text-align:center; vertical-align:top; width:89px">Figueroa‑González & Pérez‑Plasencia, 2017 </td> <td style="background-color:whitesmoke; border-bottom:1px double #7f7f7f; border-left:none; border-right:1px double #2b2b2b; border-top:none; height:49px; text-align:center; vertical-align:top; width:228px">Assay of strand breaks through the observation of DNA amplification prevention. Breaks block Taq polymerase, reducing the number of DNA templates, preventing amplification </td> <td style="background-color:whitesmoke; border-bottom:1px double #7f7f7f; border-left:none; border-right:1px double #7f7f7f; border-top:none; height:49px; text-align:center; vertical-align:top; width:46px">N/A</td> </tr> <tr> <td style="background-color:whitesmoke; border-bottom:1px double #7f7f7f; border-left:1px double #2b2b2b; border-right:1px double #2b2b2b; border-top:none; height:49px; text-align:center; vertical-align:top; width:85px">Sucrose density gradient centrifuge </td> <td style="background-color:whitesmoke; border-bottom:1px double #7f7f7f; border-left:none; border-right:1px double #2b2b2b; border-top:none; height:49px; text-align:center; vertical-align:top; width:89px">Raschke et al. 2009 </td> <td style="background-color:whitesmoke; border-bottom:1px double #7f7f7f; border-left:none; border-right:1px double #2b2b2b; border-top:none; height:49px; text-align:center; vertical-align:top; width:228px">Division of DNA pieces by density, increased fractionation leads to lower density pieces, with the use of a sucrose cushion </td> <td style="background-color:whitesmoke; border-bottom:1px double #7f7f7f; border-left:none; border-right:1px double #7f7f7f; border-top:none; height:49px; text-align:center; vertical-align:top; width:46px">N/A</td> </tr> <tr> <td style="background-color:whitesmoke; border-bottom:1px double #7f7f7f; border-left:1px double #2b2b2b; border-right:1px double #2b2b2b; border-top:none; height:49px; text-align:center; vertical-align:top; width:85px">Alkaline Elution Assay </td> <td style="background-color:whitesmoke; border-bottom:1px double #7f7f7f; border-left:none; border-right:1px double #2b2b2b; border-top:none; height:49px; text-align:center; vertical-align:top; width:89px">Kohn, 1991 </td> <td style="background-color:whitesmoke; border-bottom:1px double #7f7f7f; border-left:none; border-right:1px double #2b2b2b; border-top:none; height:49px; text-align:center; vertical-align:top; width:228px">Cells lysed with detergent-solution, filtered through membrane to remove all but intact DNA </td> <td style="background-color:whitesmoke; border-bottom:1px double #7f7f7f; border-left:none; border-right:1px double #7f7f7f; border-top:none; height:49px; text-align:center; vertical-align:top; width:46px">N/A</td> </tr> <tr> <td style="background-color:whitesmoke; border-bottom:1px double #7f7f7f; border-left:1px double #2b2b2b; border-right:1px double #2b2b2b; border-top:none; height:49px; text-align:center; vertical-align:top; width:85px">Unwinding Assay </td> <td style="background-color:whitesmoke; border-bottom:1px double #7f7f7f; border-left:none; border-right:1px double #2b2b2b; border-top:none; height:49px; text-align:center; vertical-align:top; width:89px">Nacci et al. 1992 </td> <td style="background-color:whitesmoke; border-bottom:1px double #7f7f7f; border-left:none; border-right:1px double #2b2b2b; border-top:none; height:49px; text-align:center; vertical-align:top; width:228px">DNA is stored in alkaline solutions with DNA-specific dye and allowed to unwind following removal from tissue, increased strand damage associated with increased unwinding </td> <td style="background-color:whitesmoke; border-bottom:1px double #7f7f7f; border-left:none; border-right:1px double #7f7f7f; border-top:none; height:49px; text-align:center; vertical-align:top; width:46px">N/A</td> </tr> </tbody> </table>

Taxonomic applicability: DNA strand breaks are relevant to all species, including vertebrates such as humans, that contain DNA (Cannan & Pederson, 2016).   Life stage applicability: This key event is not life stage specific as all life stages display strand breaks. However, there is an increase in baseline levels of DNA strand breaks seen in older individuals though it is unknown whether this change due to increased break induction or a greater retention of breaks due to poor repair (White & Vijg, 2016).  Sex applicability: This key event is not sex specific as both sexes display evidence of strand breaks. In some cell types, such as peripheral blood mononuclear cells, males show higher levels of single strand breaks than females (Garm et al., 2012).  Evidence for perturbation by a stressor: There are studies demonstrating that increased DNA strand breaks can result from exposure to multiple stressor types including ionizing & non-ionizing radiation, chemical agents, and oxidizing agents (EPRI, 2014; Hamada, 2014; Cencer et al., 2018; Cannan & Pederson, 2016; Yang et al., 1998).

High Unspecific

High

All life stages

Not Specified Ager, D. D. et al. (1990). “Measurement of Radiation- Induced DNA Double-Strand Breaks by Pulsed-Field Gel Electrophoresis.” Radiat Res. 122(2), 181-7. Anderson, D. & Laubenthal J. (2013), “Analysis of DNA Damage via Single-Cell Electrophoresis. In: Makovets S, editor. DNA Electrophoresis. Totowa.”, NJ: Humana Press. p 209-218. Asaithamby, A., B. Hu and D.J. Chen. (2011) Unrepaired clustered DNA lesions induce chromosome breakage in human cells. Proc Natl Acad Sci U S A 108(20): 8293-8298 . Barbieri, S., G. Babini, J. Morini et a l (2019). . Predicting DNA damage foci and their experimental readout with 2D microscopy: a unified approach applied to photon and neutron exposures. Scientific Reports 9(1): 14019 Bryce, S. et al. (2016), “Genotoxic mode of action predictions from a multiplexed flow cytometric assay and a machine learning approach.”, Environ Mol Mutagen. 57:171-189. Doi: 10.1002/em.21996. Burma, S. et al. (2001), “ATM phosphorylates histone H2AX in response to DNA double-strand breaks.”, J Biol Chem, 276(45): 42462-42467. doi:10.1074/jbc.C100466200 Cannan, W.J. and D.S. Pederson (2016), "Mechanisms and Consequences of Double-Strand DNA Break Formation in Chromatin.", Journal of Cellular Physiology, Vol.231/1, Wiley, New York, https://doi.org/10.1002/jcp.25048.   Cencer, C. et al. (2018), “PARP-1/PAR Activity in Cultured Human Lens Epithelial Cells Exposed to Two Levels of UVB Light”, Photochemistry and Photobiology, Vol.94/1, Wiley-Blackwell, Hoboken, https://doi.org/10.1111/php.12814.   Charlton, E. D. et al. (1989), “Calculation of Initial Yields of Single and Double Stranded Breaks in Cell Nuclei from Electrons, Protons, and Alpha Particles.”,  Int. J. Radiat. Biol. 56(1): 1-19. doi: 10.1080/09553008914551141. Collins, R. A. (2004), “The Comet Assay for DNA Damage and Repair. Molecular Biotechnology.”, Mol Biotechnol. 26(3): 249-61. doi:10.1385/MB:26:3:249 EPRI (2014), Epidemiology and mechanistic effects of radiation on the lens of the eye: Review and scientific appraisal of the literature, EPRI, California.  Figueroa‑González, G. and C. Pérez‑Plasencia. (2017), “Strategies for the evaluation of DNA damage and repair mechanisms in cancer”, Oncology Letters, Vol.13/6, Spandidos Publications, Athens, https://doi.org/10.3892/ol.2017.6002.  Garcia-Canton, C. et al. (2013), “Assessment of the in vitro p-H2AX assay by High Content Screening asa novel genotoxicity test.”, Mutat Res. 757:158-166.  Doi:  10.1016/j.mrgentox.2013.08.002 Gardiner, K. et al. (1986), “Fractionation of Large Mammalian DNA Restriction Fragments Using Vertical Pulsed-Field Gradient Gel Electrophoresis.”,  Somatic Cell and Molecular Genetics. 12(2): 185-95.Doi: 10.1007/bf01560665. Garm, C. et al. (2012), “Age and gender effects on DNA strand break repair in peripheral blood mononuclear cells”, Aging Cell, Vol.12/1, Blackwell Publishing Ltd, Oxford, https://doi.org/10.1111/acel.12019.  Hamada, N. (2014), “What are the intracellular targets and intratissue target cells for radiation effects?”, Radiation research, Vol. 181/1, The Radiation Research Society, Indianapolis, https://doi.org/10.1667/RR13505.1.  Herschleb, J. et al. (2007), “Pulsed-field gel electrophoresis.”,  Nat Protoc. 2(3): 677-684. doi:10.1038/nprot.2007.94 Iliakis, G. et al. (2015), “Alternative End-Joining Repair Pathways Are the Ultimate Backup for Abrogated Classical Non-Homologous End-Joining and Homologous Recombination Repair: Implications for the Formation of Chromosome Translocations.”,  Mutation Research/Genetic Toxicology and Environmental Mutagenesis. 2(3): 677-84. doi: 10.1038/nprot.2007.94 Jackson, S. (2002). “Sensing and repairing DNA double-strand breaks.”,  Carcinogenesis. 23:687-696. Doi:10.1093/carcin/23.5.687. Ji, J. et al. (2017), “Phosphorylated fraction of H2AX as a measurement for DNA damage in cancer cells and potential applications of a novel assay.”,  PLoS One. 12(2): e0171582. doi:10.1371/journal.pone.0171582 Kawashima, Y.(2017), “Detection of DNA double-strand breaks by pulsed-field gel electrophoresis.”,  Genes Cells 22:84-93. Doi: 10.1111/gtc.12457. Khoury, L. et al. (2013), “Validation of high-throughput genotoxicity assay screening using cH2AX in-cell Western assay on HepG2 cells.”, Environ Mol Mutagen, 54:737-746. Doi:  10.1002/em.21817. Khoury, L. et al. (2016), “Evaluation of four human cell lines with distinct biotransformation properties for genotoxic screening.”, Mutagenesis, 31:83-96. Doi: <a href="https://doi.org/10.1093/mutage/gev058" target="_blank">10.1093/mutage/gev058</a>. Kohn, K.W. (1991), “Principles and practice of DNA filter elution”, Pharmacology & Therapeutics, Vol.49/1, Elsevier, Amsterdam, https://doi.org/10.1016/0163-7258(91)90022-E.  Loo, DT. (2011), “In Situ Detection of Apoptosis by the TUNEL Assay: An Overview of Techniques. In: Didenko V, editor. DNA Damage Detection In Situ, Ex Vivo, and In Vivo. Totowa.”, NJ: Humana Press. p 3-13.doi: <a href="https://doi.org/10.1007/978-1-60327-409-8_1" target="_blank">10.1007/978-1-60327-409-8_1</a>. Mah, L. J. et al. (2010), “Quantification of gammaH2AX foci in response to ionising radiation.”,  J Vis Exp(38). doi:10.3791/1957. Nacci, D. et al. (1992), “Application of the DNA alkaline unwinding assay to detect DNA strand breaks in marine bivalves”, Marine Environmental Research, Vol.33/2, Elsevier BV, Amsterdam, https://doi.org/10.1016/0141-1136(92)90134-8.  Nikolova, T., F. et al. (2017), “Genotoxicity testing: Comparison of the γH2AX focus assay with the alkaline and neutral comet assays.”,  Mutat Res 822:10-18. Doi: <a href="https://doi.org/10.1016/j.mrgentox.2017.07.004" target="_blank">10.1016/j.mrgentox.2017.07.004</a>. Nitiss, J. L. et al. (2012), “Topoisomerase assays. ”, Curr Protoc Pharmacol. Chapter 3: Unit 3 3. OECD. (2014). Test No. 489: “In vivo mammalian alkaline comet assay.”  OECD Guideline for the Testing of Chemicals, Section 4 . Olive, P. L., & Banáth, J. P. (2006), “The comet assay: a method to measure DNA damage in individual cells.”,  Nature Protocols. 1(1): 23-29. doi:10.1038/nprot.2006.5. Platel A. et al. (2011), “Study of oxidative DNA damage in TK6 human lymphoblastoid cells by use of the thymidine kinase gene-mutation assay and the in vitro modified comet assay: Determination of No-Observed-Genotoxic-Effect-Levels.”,  Mutat Res 726:151-159. Doi: 10.1016/j.mrgentox.2011.09.003. Raschke, S., J. Guan and G. Iliakis. (2009), “Application of alkaline sucrose gradient centrifugation in the analysis of DNA replication after DNA damage”, Methods in Molecular Biology, Vol.521, Humana Press, Totowa, https://doi.org/10.1007/978-1-60327-815-7_18.  Redon, C. et al. (2010), “The use of gamma-H2AX as a biodosimeter for total-body radiation exposure in non-human primates.”,  PLoS One. 5(11): e15544. doi:10.1371/journal.pone.0015544 Revet, I. et al. (2011), “Functional relevance of the histone γH2Ax in the response to DNA damaging agents.” Proc Natl Acad Sci USA.108:8663-8667. Doi: 10.1073/pnas.1105866108 Rogakou, E.P. et al. (1998), “DNA Double-stranded Breaks Induce Histone H2AX Phosphorylation on Serine 139.” , J Biol Chem, 273:5858-5868. Doi: 10.1074/jbc.273.10.5858 Rothkamm, K. & Horn, S. (2009), “γ-H2AX as protein biomarker for radiation exposure.”,  Ann Ist Super Sanità, 45(3): 265-71. White, R.R. and J. Vijg. (2016), “Do DNA Double-Strand Breaks Drive Aging?”, Molecular Cell, Vol.63, Elsevier, Amsterdam, http://doi.org/10.1016/j.molcel.2016.08.004.  Yang, Y. et al. (1998), “The effect of catalase amplification on immortal lens epithelial cell lines”, Experimental Eye Research, Vol.67/6, Academic Press Inc, Cambridge, https://doi.org/10.1006/exer.1998.0560.   AOPWiki 2019-05-19T16:33:20

2023-05-15T08:39:51

Increase, Oocyte apoptosis

Cellular

AOPWiki 2020-04-30T16:41:18

2020-04-30T16:41:18

Decrease, Oogenesis

Organ

AOPWiki 2017-04-15T16:20:50

2020-04-30T16:41:53

Reduction, Cumulative fecundity and spawning

Individual

Spawning refers to the release of eggs. Cumulative fecundity refers to the total number of eggs deposited by a female, or group of females over a specified period of time.

In laboratory-based reproduction assays (e.g., OECD Test No. 229; OECD Test No. 240), spawning and cumulative fecundity can be directly measured through daily observation of egg deposition and egg counts. In some cases, fecundity may be estimated based on gonado-somatic index (<a href="http://www.oecd.org/officialdocuments/publicdisplaydocumentpdf/?cote=env/jm/mono(2008)22&doclanguage=en">OECD 2008</a>).

Cumulative fecundity and spawning can, in theory, be evaluated for any egg laying animal.

High Female

High

Adult, reproductively mature

High High High

<ul> <li>OECD 2008. Series on testing and assessment, Number 95. Detailed Review Paper on Fish Life-cycle Tests. OECD Publishing, Paris. ENV/JM/MONO(2008)22.</li> <li>OECD (2015), Test No. 240: Medaka Extended One Generation Reproduction Test (MEOGRT), OECD Publishing, Paris. DOI: <a href="http://dx.doi.org/10.1787/9789264242258-en" target="_blank" title="http://dx.doi.org/10.1787/9789264242258-en">http://dx.doi.org/10.1787/9789264242258-en</a></li> <li>OECD. 2012a. Test no. 229: Fish short term reproduction assay. Paris, France:Organization for Economic Cooperation and Development.</li> </ul> AOPWiki 2016-11-29T18:41:22

2017-03-20T17:52:57

Decrease, Population growth rate

Population

A population can be defined as a group of interbreeding organisms, all of the same species, occupying a specific space during a specific time (Vandermeer and Goldberg 2003, Gotelli 2008).  As the population is the biological level of organization that is often the focus of ecological risk assessments, population growth rate (and hence population size over time) is important to consider within the context of applied conservation practices. If N is the size of the population and t is time, then the population growth rate (dN/dt) is proportional to the instantaneous rate of increase, r, which measures the per capita rate of population increase over a short time interval. Therefore, r, is a difference between the instantaneous birth rate (number of births per individual per unit of time; b) and the instantaneous death rate (number of deaths per individual per unit of time; d) [Equation 1]. Because  r is an instantaneous rate, its units can be changed via division.  For example, as there are 24 hours in a day, an r of 24 individuals/(individual x day) is equal to an r of 1 individual/(individual/hour) (Caswell 2001, Vandermeer and Goldberg 2003, Gotelli 2008, Murray and Sandercock 2020).  Equation 1:  r = b - d This key event refers to scenarios where r < 0 (instantaneous death rate exceeds instantaneous birth rate). Examining r in the context of population growth rate: ● A population will decrease to extinction when the instantaneous death rate exceeds the instantaneous birth rate (r < 0).              ● The smaller the value of r below 1, the faster the population will decrease to zero.   ● A population will increase when resources are available and the instantaneous birth rate exceeds the instantaneous death rate (r > 0)            ● The larger the value that r exceeds 1, the faster the population can increase over time       ● A population will neither increase or decrease when the population growth rate equals 0 (either due to N = 0, or if the per capita birth and death rates are exactly balanced).  For example, the per capita birth and death rates could become exactly balanced due to density dependence and/or to the effect of a stressor that reduces survival and/or reproduction (Caswell 2001, Vandermeer and Goldberg 2003, Gotelli 2008, Murray and Sandercock 2020).      Effects incurred on a population from a chemical or non-chemical stressor could have an impact directly upon birth rate (reproduction) and/or death rate (survival), thereby causing a decline in population growth rate.   ● Example of direct effect on r:  Exposure to 17b-trenbolone reduced reproduction (i.e., reduced b) in the fathead minnow over 21 days at water concentrations ranging from 0.0015 to about 41 mg/L (Ankley et al. 2001; Miller and Ankley 2004).              Alternatively, a stressor could indirectly impact survival and/or reproduction.   ● Example of indirect effect on r:  Exposure of non-sexually differentiated early life stage fathead minnow to the fungicide prochloraz has been shown to produce male-biased sex ratios based on gonad differentiation, and resulted in projected change in population growth rate (decrease in reproduction due to a decrease in females and thus recruitment) using a population model. (Holbech et al., 2012; Miller et al. 2022) Density dependence can be an important consideration: ● The effect of density dependence depends upon the quantity of resources present within a landscape.  A change in available resources could increase or decrease the effect of density dependence and therefore cause a change in population growth rate via indirectly impacting survival and/or reproduction.   ● This concept could be thought of in terms of community level interactions whereby one species is not impacted but a competitor species is impacted by a chemical stressor resulting in a greater availability of resources for the unimpacted species.  In this scenario, the impacted species would experience a decline in population growth rate. The unimpacted species would experience an increase in population growth rate (due to a smaller density dependent effect upon population growth rate for that species).        Closed versus open systems: ● The above discussion relates to closed systems (there is no movement of individuals between population sites) and thus a declining population growth rate cannot be augmented by immigration.   ● When individuals depart (emigrate out of a population) the loss will diminish population growth rate.   Population growth rate applies to all organisms, both sexes, and all life stages.

Population growth rate (instantaneous growth rate) can be measured by sampling a population over an interval of time (i.e. from time t = 0 to time t = 1).  The interval of time should be selected to correspond to the life history of the species of interest (i.e. will be different for rapidly growing versus slow growing populations). The population growth rate, r, can be determined by taking the difference (subtracting) between the initial population size, Nt=0 (population size at time t=0), and the population size at the end of the interval, Nt=1 (population size at time t = 1), and then subsequently dividing by the initial population size.  Equation 2:  r = (Nt=1 - Nt=0) / Nt=0 The diversity of forms, sizes, and life histories among species has led to the development of a vast number of field techniques for estimation of population size and thus population growth over time (Bookhout 1994, McComb et al. 2021).   ● For stationary species an observational strategy may involve dividing a habitat into units. After setting up the units, samples are performed throughout the habitat at a select number of units (determined using a statistical sampling design) over a time interval (at time t = 0 and again at time t = 1), and the total number of organisms within each unit are counted. The numbers recorded are assumed to be representative for the habitat overall, and can be used to estimate the population growth rate within the entire habitat over the time interval.   ● For species that are mobile throughout a large range, a strategy such as using a mark-recapture method may be employed (i.e. tags, bands, transmitters) to determine a count over a time interval (at time = 0 and again at time =1).    Population growth rate can also be estimated using mathematical model constructs (for example, ranging from simple differential equations to complex age or stage structured matrix projection models and individual based modeling approaches), and may assume a linear or nonlinear population increase over time (Caswell 2001, Vandermeer and Goldberg 2003, Gotelli 2008, Murray and Sandercock 2020). The AOP framework can be used to support the translation of pathway-specific mechanistic data into responses relevant to population models and output from the population models, such as changing (declining) population growth rate, can be used to assess and manage risks of chemicals (Kramer et al. 2011). As such, this translational capability can increase the capacity and efficiency of safety assessments both for single chemicals and chemical mixtures (Kramer et al. 2011).   Some examples of modeling constructs used to investigate population growth rate: ● A modeling construct could be based upon laboratory toxicity tests to determine effect(s) that are then linked to the population model and used to estimate decline in population growth rate.  Miller et al. (2007) used concentration–response data from short term reproductive assays with fathead minnow (Pimephales promelas) exposed to endocrine disrupting chemicals in combination with a population model to examine projected alterations in population growth rate.   ● A model construct could be based upon a combination of effects-based monitoring at field sites (informed by an AOP) and a population model.  Miller et al. (2015) applied a population model informed by an AOP to project declines in population growth rate for white suckers (Catostomus commersoni) using observed changes in sex steroid synthesis in fish exposed to a complex pulp and paper mill effluent in Jackfish Bay, Ontario, Canada. Furthermore, a model construct could be comprised of a series of quantitative models using KERs that culminates in the estimation of change (decline) in population growth rate.   ● A quantitative adverse outcome pathway (qAOP) has been defined as a mathematical construct that models the dose–response or response–response relationships of all KERs described in an AOP (Conolly et al. 2017, Perkins et al. 2019). Conolly et al. (2017) developed a qAOP using data generated with the aromatase inhibitor fadrozole as a stressor and then used it to predict potential population‐level impacts (including decline in population growth rate). The qAOP modeled aromatase inhibition (the molecular initiating event) leading to reproductive dysfunction in fathead minnow (Pimephales promelas) using 3 computational models: a hypothalamus–pituitary–gonadal axis model (based on ordinary differential equations) of aromatase inhibition leading to decreased vitellogenin production (Cheng et al. 2016), a stochastic model of oocyte growth dynamics relating vitellogenin levels to clutch size and spawning intervals (Watanabe et al. 2016), and a population model (Miller et al. 2007). ● Dynamic energy budget (DEB) models offer a methodology that reverse engineers stressor effects on growth, reproduction, and/or survival into modular characterizations related to the acquisition and processing of energy resources (Nisbet et al. 2000, Nisbet et al. 2011).  Murphy et al. (2018) developed a conceptual model to link DEB and AOP models by interpreting AOP key events as measures of damage-inducing processes affecting DEB variables and rates. ● Endogenous Lifecycle Models (ELMs), capture the endogenous lifecycle processes of growth, development, survival, and reproduction and integrate these to estimate and predict expected fitness (Etterson and Ankley, 2021).  AOPs can be used to inform ELMs of effects of chemical stressors on the vital rates that determine fitness, and to decide what hierarchical models of endogenous systems should be included within an ELM (Etterson and Ankley, 2021).

Consideration of population size and changes in population size over time is potentially relevant to all living organisms.

Not Specified Unspecific

Not Specified

All life stages

High

<ul> <li>Ankley GT, Jensen KM, Makynen EA, Kahl MD, Korte JJ, Hornung MW, Henry TR, Denny JS, Leino RL, Wilson VS, Cardon MD, Hartig PC, Gray LE. 2003. Effects of the androgenic growth promoter 17b-trenbolone on fecundity and reproductive endocrinology of the fathead minnow. Environ. Toxicol. Chem. 22: 1350–1360.</li> <li>Bookhout TA. 1994. Research and management techniques for wildlife and habitats. The Wildlife Society, Bethesda, Maryland. 740 pp.</li> <li>Caswell H. 2001. Matrix Population Models. Sinauer Associates, Inc., Sunderland, MA, USA</li> <li>Cheng WY, Zhang Q, Schroeder A, Villeneuve DL, Ankley GT, Conolly R.  2016.  Computational modeling of plasma vitellogenin alterations in response to aromatase inhibition in fathead minnows. Toxicol Sci 154: 78–89.</li> <li>Conolly RB, Ankley GT, Cheng W-Y, Mayo ML, Miller DH, Perkins EJ, Villeneuve DL, Watanabe KH. 2017. Quantitative adverse outcome pathways and their application to predictive toxicology. Environ. Sci. Technol. 51:  4661-4672.</li> <li>Etterson MA, Ankley GT.  2021.  Endogenous Lifecycle Models for Chemical Risk Assessment. Environ. Sci. Technol. 55:  15596-15608. </li> <li>Gotelli NJ, 2008. A Primer of Ecology. Sinauer Associates, Inc., Sunderland, MA, USA.</li> <li>Holbech H, Kinnberg KL, Brande-Lavridsen N, Bjerregaard P, Petersen GI, Norrgren L, Orn S, Braunbeck T, Baumann L, Bomke C, Dorgerloh M, Bruns E, Ruehl-Fehlert C, Green JW, Springer TA, Gourmelon A. 2012 Comparison of zebrafish (Danio rerio) and fathead minnow (Pimephales promelas) as test species in the Fish Sexual Development Test (FSDT). Comp. Biochem. Physiol. C Toxicol. Pharmacol. 155:  407–415.</li> <li>Kramer VJ, Etterson MA, Hecker M, Murphy CA, Roesijadi G, Spade DJ, Stromberg JA, Wang M, Ankley GT.  2011.  Adverse outcome pathways and risk assessment: Bridging to population level effects.  Environ. Toxicol. Chem. 30, 64-76.</li> <li>McComb B, Zuckerberg B, Vesely D, Jordan C.  2021.  Monitoring Animal Populations and their Habitats: A Practitioner's Guide.  Pressbooks, Oregon State University, Corvallis, OR Version 1.13, 296 pp. </li> <li>Miller DH, Villeneuve DL, Santana Rodriguez KJ, Ankley GT. 2022.  A multidimensional matrix model for predicting the effect of male biased sex ratios on fish populations. Environmental Toxicology and Chemistry 41(4): 1066-1077.</li> <li>Miller DH, Tietge JE, McMaster ME, Munkittrick KR, Xia X, Griesmer DA, Ankley GT. 2015. Linking mechanistic toxicology to population models in forecasting recovery from chemical stress: A case study from Jackfish Bay, Ontario, Canada. Environmental Toxicology and Chemistry 34(7):  1623-1633.</li> <li>Miller DH, Jensen KM, Villeneuve DE, Kahl MD, Makynen EA, Durhan EJ, Ankley GT. 2007. Linkage of biochemical responses to population-level effects: A case study with vitellogenin in the fathead minnow (Pimephales promelas). Environ Toxicol Chem 26:  521–527.</li> <li>Miller DH, Ankley GT. 2004. Modeling impacts on populations: Fathead minnow (Pimephales promelas) exposure to the endocrine disruptor 17b-trenbolone as a case study. Ecotox Environ Saf 59: 1–9.</li> <li>Murphy CA, Nisbet RM, Antczak P, Garcia-Reyero N, Gergs A, Lika K, Mathews T, Muller EB, Nacci D, Peace A, Remien CH, Schultz IR, Stevenson LM, Watanabe KH.  2018.  Incorporating suborganismal processes into dynamic energy budget models for ecological risk assessment.  Integrated Environmental Assessment and Management 14(5):  615–624.</li> <li>Murray DL, Sandercock BK (editors).  2020.  Population ecology in practice.  Wiley-Blackwell, Oxford UK, 448 pp.</li> <li>Nisbet RM, Jusup M, Klanjscek T, Pecquerie L.  2011.  Integrating dynamic energy budget (DEB) theory with traditional bioenergetic models.  The Journal of Experimental Biology 215: 892-902.</li> <li>Nisbet RM, Muller EB, Lika K, Kooijman SALM. 2000. From molecules to ecosystems through dynamic energy budgets. J Anim Ecol 69:  913–926.</li> <li>Perkins EJ,  Ashauer R, Burgoon L, Conolly R, Landesmann B,, Mackay C, Murphy CA, Pollesch N, Wheeler JR, Zupanic A, Scholzk S.  2019.  Building and applying quantitative adverse outcome pathway models for chemical hazard and risk assessment.  Environmental Toxicology and Chemistry 38(9): 1850–1865. </li> <li>Vandermeer JH, Goldberg DE. 2003.  Population ecology: first principles.  Princeton University Press, Princeton NJ, 304 pp.</li> <li>Villeneuve DL, Crump D, Garcia-Reyero N, Hecker M, Hutchinson TH, LaLone CA, Landesmann B, Lattieri T, Munn S, Nepelska M, Ottinger MA, Vergauwen L, Whelan M. Adverse outcome pathway (AOP) development 1: Strategies and principles. Toxicol Sci. 2014: 142:312–320</li> <li>Watanabe KH, Mayo M, Jensen KM, Villeneuve DL, Ankley GT, Perkins EJ.  2016.  Predicting fecundity of fathead minnows (Pimephales promelas) exposed to endocrine‐disrupting chemicals using a MATLAB(R)‐based model of oocyte growth dynamics. PLoS One 11:  e0146594.</li> </ul> AOPWiki 2016-11-29T18:41:24

2023-01-03T09:09:06

<upstream-id>bac5b8f8-5e17-4991-ab3a-c38af5b7e85e</upstream-id> <downstream-id>efbb5ace-1e19-40ab-8744-e25d1645f8d1</downstream-id> Direct deposition of ionizing energy refers to imparted energy interacting directly with the DNA double helix and producing randomized damage. This can be in the form of double strand breaks (DSBs), single-strand breaks, base damage, or the crosslinking of DNA to other molecules (Smith et al., 2003; Joiner, 2009; Christensen, 2014; Sage and Shikazono, 2017). Among these, the most detrimental type of DNA damage to a cell is DSBs. They are caused by the breaking of the sugar-phosphate backbone on both strands of the DNA double helix molecule, either directly across from each other or several nucleotides apart (Ward, 1988; Iliakis et al., 2015). This occurs when high-energy subatomic particles interact with the orbital electrons of the DNA causing ionization (where electrons are ejected from atoms) and excitation (where electrons are raised to higher energy levels) (Joiner, 2009). The number of DSBs produced and the complexity of the breaks is highly dependent on the amount of energy deposited on and absorbed by the cell. This can vary as a function of the dose-rate (Brooks et al., 2016) and the radiation quality which is a function of its linear energy transfer (LET) (Sutherland et al., 2000; Nikjoo et al., 2001; Jorge et al., 2012). LET describes the amount of energy that an ionizing particle transfers to media per unit distance (Smith et al., 2003; Okayasu, 2012a; Christensen et al., 2014). High LET radiation, such as alpha particles, heavy ion particles, and neutrons can deposit larger quantities of energy within a single track than low LET radiation, such as γ-rays, X-rays, electrons, and protons (Kadhim et al., 2006; Franken et al., 2012; Frankenberg et al., 1999; Rydberg et al., 2002; Belli et al., 2000; Antonelli et al., 2015). As such, radiation with higher LETs tends to produce more complex, dense structural damage, particularly in the form of clustered damage, in comparison to lower LET radiation (Nikjoo et al., 2001; Terato and Ide, 2005; Hada and Georgakilas, 2008; Okayasu, 2012a; Lorat et al., 2015; Nikitaki et al., 2016). Thus, the complexity and yield of clustered DNA damage increases with ionizing density (Ward, 1988; Goodhead, 2006). However, clustered damage can also be induced even by a single radiation track through a cell. While the amount of DSBs produced depends on the radiation dose (see dose concordance), it also depends on several other factors. As the LET increases, the complexity of DNA damage increases, decreasing the repair rate, and increasing toxicity (Franken et al., 2012; Antonelli et al., 2015).

The strategy for collating the evidence on radiation stressors to support the relationship is described in Kozbenko et al 2022.  Briefly, a scoping review methodology was used to prioritize studies based on a population, exposure, outcome, endpoint statement.

Overall Weight of Evidence for this KER: High

The biological rationale linking the direct deposition of energy on DNA with an increase in DSB formation is strongly supported by numerous literature reviews that are available on this topic (J .F. Ward, 1988; Lipman, 1988; Hightower, 1995; Terato & Ide, 2005; Goodhead, 2006; Kim & Lee, 2007; Asaithamby et al., 2008; Hada & Georgakilas, 2008; Jeggo, 2009; Clement, 2012; Okayasu, 2012b; Stewart, 2012; M. E. Lomax et al., 2013; EPRI, 2014; Hamada, 2014; Moore et al., 2014; Desouky et al., 2015; Ainsbury, 2016; Foray et al., 2016; Hamada & Sato, 2016; Hamada, 2017a; Sage & Shikazono, 2017; Chadwick, 2017; Wang et al., 2021; Nagane et al., 2021; Sylvester et al., 2018; Baselet et al., 2019). Ionizing radiation can be in the form of high energy particles (such as alpha particles, beta particles, or charged ions) or high energy photons (such as gamma-rays or X-rays). Ionizing radiation can break the DNA within chromosomes both directly and indirectly, as shown through using velocity sedimentation of DNA through neutral and alkaline sucrose gradients. The most direct path entails a collision between a high-energy particle or photon and a strand of DNA. Additionally, excitation of secondary electrons in the DNA allows for a cascade of ionization events to occur, which can lead to the formation of multiple damage sites (Joiner, 2009). As an example, high-energy electrons will traverse a DNA molecule in a mammalian cell within 10-18 s and 10-14 s, resulting in 100,000 ionizing events per 1 Gy dose in a 10 μm cell (Joiner, 2009). The amount of damage can be influenced by factors such as the cell cycle stage and chromatin structure. It has been shown that in more condensed, packed chromatin structures such as those present in intact cells and heterochromatin, it is more difficult for the DNA to be damaged (Radulescu et al., 2006; Agrawala et al., 2008; Falk et al., 2008; Venkatesh et al., 2016). In contrast, DNA damage is more easily induced in lightly-packed chromatin such as euchromatin and nucleoids, (Radulescu et al., 2006; Falk et al., 2008; Venkatesh et al., 2016). Of the possible radiation-induced DNA damage types, DSB is considered to be the most harmful to the cell, as there may be severe consequences if this damage is not adequately repaired (Khanna & Jackson, 2001; Smith et al., 2003; Okayasu, 2012a; M. E. Lomax et al., 2013; Rothkamm et al., 2015). A considerable fraction of DSBs can also be formed in cells through indirect mechanisms.  In this case, deposited energy can split water molecules near DNA, which can generate a significant quantity of reactive oxygen species in the form of hydroxyl free radicals (Ward, 1988; Wolf, 2008; Desouky et al., 2015; Maier et al., 2016, Cencer et al., 2018; Bains, 2019; Ahmadi et al., 2021). Estimates using models and experimental results suggest that hydroxyl radicals may be present within nanoseconds of energy deposition by radiation (Yamaguchi et al., 2005). These short-lived but highly reactive hydroxyl radicals may react with nearby DNA. This will produce DNA damage, including single-strand breaks and DSBs (Ward, 1988; Sasaki, 1998; Desouky et al., 2015; Maier et al., 2016). DNA breaks are especially likely to be produced if the sugar moiety is damaged, and DSBs occur when two single-strand breaks are in close proximity to each other (Ward, 1988).

Empirical data strongly supports this KER. The evidence presented below is summarized in table 1. The types of DNA damage produced by ionizing radiation and the associated mechanisms, including the induction of DSBs, are reviewed by Lomax et al. (2013) and documents produced by international radiation governing frameworks (Valentin, 1998; UNSCEAR, 2000). Other reviews also highlight the relationship between the deposition of energy by radiation and DSB induction, and discuss the various methods available to detect these DSBs (Terato & Ide, 2005; Rothkamm et al., 2015; Sage & Shikazono, 2017). A visual representation of the time frames and dose ranges probed by the dedicated studies discussed here is shown in Figures 1 & 2 below.     <img alt="" src="https://aopwiki.org/system/dragonfly/production/2022/10/12/4zw4nw353c_ke1_mie_dsb_dose_v2.png" style="height:734px; width:1000px" /> Figure 1: Plot of example studies (y-axis) against equivalent dose (Sv) used to determine the empirical link between direct deposition of energy and DSBs. The z-axis denotes the equivalent dose rate used in each study. The y-axis is ordered from low LET to high LET from top to bottom.      <img alt="" src="https://aopwiki.org/system/dragonfly/production/2022/10/12/a85jspx5_ke1_mie_dsb_time_v2.png" style="height:706px; width:1000px" /> Figure 2: Plot of example studies (y-axis) against time scales used to determine the empirical link between direct deposition of energy and DSBs. The z-axis denotes the equivalent dose rate used in each study. The y-axis is ordered from low LET to high LET from top to bottom.      Dose Concordance There is evidence in the literature suggesting a dose concordance between the direct deposition of energy by ionizing radiation and the incidence (Grudzenski et al., 2010) of DNA DSBs. Results from in vitro (Aufderheide et al., 1987; Sidjanin, 1993; Bucolo, 1994; Frankenberg et al., 1999; Rogakou et al., 1999; Belli et al., 2000; Sutherland et al., 2000; Lara et al., 2001; Rydberg et al., 2002; Baumstark-Kham et al., 2003; Rothkamm and Lo, 2003; Long, 2004; Kuhne et al., 2005; Sudprasert et al., 2006; Beels et al., 2009; Grudzenski et al., 2010; Liao, 2011; Franken et al., 2012; Bannik et al., 2013; Shelke & Das, 2015; Antonelli et al., 2015; Markiewicz et al., 2015; Allen, 2018; Dalke, 2018; Bains, 2019; Ahmadi et al., 2021; Sabirzhanov et al., 2020; Ungvari et al., 2013; Rombouts et al., 2013; Baselet et al., 2017), in vivo (Reddy, 1998; Sutherland et al., 2000; Rube et al., 2008; Beels et al., 2009; Grudzenski et al., 2010; Markiewicz et al., 2015; Barnard, 2018; Barnard, 2019; Barnard, 2022; Schmal et al., 2019; Barazzuol et al., 2017; Geisel et al., 2012), ex vivo (Rube et al., 2008; Flegal et al., 2015)  and simulation studies (Charlton et al., 1989) suggest that there is a positive, linear, dose-dependent increase in DSBs with increasing deposition of energy across a wide range of radiation types (iron ions, X-rays, ultrasoft X-rays, gamma-rays, photons, UV light, and alpha particles) and radiation doses (1 mGy - 100 Gy) (Aufderheide et al., 1987; Sidjanin, 1993; Frankenberg et al., 1999; Sutherland et al., 2000; de Lara et al., 2001; Baumstark-Khan et al., 2003; Rothkamm & Lo, 2003; Kuhne et al., 2005; Rube et al., 2008; Grudzenski et al., 2010; Bannik et al., 2013; Shelke & Das, 2015; Antonelli et al., 2015; Dalke, 2018; Barazzuol et al., 2017; Ungvari et al., 2013; Rombouts et al., 2013; Baselet et al., 2017; Geisel et al., 2012). DSBs have been predicted to occur at energy deposition levels as low as 75 eV (Charlton et al., 1989).     Time Concordance There is evidence suggesting a time concordance between the direct deposition of energy and the incidence of DSBs. A number of different models and experiments have provided evidence of ionizing radiation-induced foci (IRIF), which can be used to infer DSB formation seconds (Mosconi et al., 2011) or minutes after radiation exposure (Rogakou et al., 1999; Rothkamm and Lo, 2003; Rube et al., 2008; Beels et al., 2009; Kuefner et al., 2009; Grudzenski et al., 2010; Antonelli et al., 2015; Acharya et al., 2010; Sabirzhanov et al., 2020; Rombouts et al., 2013; Nübel et al., 2006; Baselet et al., 2017; Zhang et al., 2017).       Essentiality Deposition of energy is essential for DNA strand breaks. They can also be caused through other routes, such as oxidative stress (Cadet et al., 2012), but under normal physiological conditions deposition of energy is necessary. This was tested through many studies using  various indicators such as 53BP1 foci/cell, γH2AX foci/cell, DNA migration, and the amount of DNA in tails for the comet assay. Various organisms such as humans, mice, rabbits, guinea pigs, and cattle were used. They showed that without the deposition of energy, there was only a negligible amount of DNA strand breaks (Aufderheide et al., 1987; Sidjanin, 1993; Bucolo, 1994; Reddy, 1998; Rogers, 2004; Bannik et al., 2013; Dalke, 2018; Bains, 2019; Barnard, 2019; Barnard, 2021).

Uncertainties and inconsistencies in this KER are as follows: <ul> <li>Studies have shown that dose-rates (Brooks et al., 2016) and radiation quality (Sutherland et al., 2000; Nikjoo et al., 2001; Jorge et al., 2012) are factors that can influence the dose-response relationship.  </li> <li>Low-dose radiation has been observed to have beneficial effects and may even invoke protection against spontaneous genomic damage (Feinendegen, 2005; Day et al., 2007; Feinendegen et al., 2007; Shah et al., 2012; Nenoi et al., 2015; Dalke, 2018). This protective effect has been documented in in vivo and in vitro, as reviewed by ICRP (2007) and UNSCEAR (2008) and can vary depending on the cell type, the tissue, the organ, or the entire organism (Brooks et al., 2016).</li> <li>Depositing ionizing energy is a stochastic event; as such this can influence the location, degree and type of DNA damage imparted on a cell. As an example, studies have shown that mitochondrial DNA may also be an important target for genotoxic effects of ionizing radiation (Wu et al., 1999).</li> </ul>

<table border="1"> <tbody> <tr> <td> Modulating Factor  </td> <td> Details   </td> <td> Effects on the KER   </td> <td> References   </td> </tr> <tr> <td> Nitroxides  </td> <td> Increased concentration  </td> <td> Decreased DNA strand breaks.  </td> <td> DeGraff et al., 1992; Citrin & Mitchel, 2014  </td> </tr> <tr> <td> 5-fluorouracil  </td> <td> Increased concentration  </td> <td> Increased DNA strand breaks.  </td> <td> De Angelis et al., 2006; Citrin & Mitchel, 2014  </td> </tr> <tr> <td> Thiols  </td> <td> Increased concentration  </td> <td> Decreased DNA strand breaks.  </td> <td> Milligan et al., 1995; Citrin & Mitchel, 2014  </td> </tr> <tr> <td> Cisplatin  </td> <td> Increased concentration  </td> <td> Decreased DNA break repair.  </td> <td> Sears & Turchi; Citrin & Mitchel, 2014  </td> </tr> </tbody> </table>

Quantitative understanding of this linkage suggests that DSBs can be predicted upon exposure to ionizing radiation. This is dependent on the biological model, the type of radiation and the radiation dose. In general, 1 Gy of radiation is thought to result in 3000 damaged bases (Maier et al., 2016), 1000 single-strand breaks, and 40 DSBs (Ward, 1988; Foray et al., 2016; Maier et al., 2016) . The table below provides representative examples of the calculated DNA damage rates across different model systems, most of which are examining DNA DSBs.     Dose Concordance  The following tables provide representative examples of the relationship, unless otherwise indicated, all data is significantly significant.  <table border="1"> <tbody> <tr> <td> Reference  </td> <td> Experiment Description  </td> <td> Result  </td> </tr> <tr> <td> Ward, 1988  </td> <td> In vitro. Cells containing approximately 6 pg of DNA were exposed to 1 Gy.  </td> <td> Under the assumption of 6 pg of DNA per cell. 60 eV of energy deposited per event over a total of 1 Gy. Deoxyribose (2.3 pg/cell): 14,000 eV deposited, 235 events. Bases (2.4 pg/cell): 14.7 keV deposited, 245 events. Phosphate (1.2 pg/cell): 7,300 eV deposited, 120 events. Bound water (3.1 pg/cell): 19 keV deposited, 315 events. Inner hydration shell (4.2 pg/cell): 25,000 eV deposited 415 events.  </td> </tr> <tr> <td> Charlton, 1989  </td> <td> In-silico. A computer simulation/model was used to test various types of radiation with doses from 0 to 400 eV (energy deposited) on the amount of DNA damage produced.  </td> <td> Simulated dose-concordance prediction of increase in number of DSBs/54 nucleotide pairs as direct deposition of energy increases in the range 75-400 eV. In the range 100 - 150 eV: 0.38 DSBs/54 nucleotide pairs and at 400 eV: ~0.80 DSBs per 64 nucleotide pairs.  </td> </tr> <tr> <td> Sutherland, 2000  </td> <td> In vitro. Human cells were exposed to 137Cs γ-rays (0 – 100 Gy, 0.16 – 1.6 Gy/min). The frequency of DSBs was determined using gel electrophoresis.  </td> <td> Using isolated bacteriophage T7 DNA and 0-100 Gy of γ radiations, observed a response of 2.4 DSBs per megabase pair per Gy.  </td> </tr> <tr> <td> Rogakou et al., 1999  </td> <td> In vitro. Normal human fibroblasts (IMR90) and human breast cancer cells (MCF7 were exposed to 0.6 and 2 Gy 137Cs γ-rays delivered at 15.7 Gy/min. The number of DSBs were determined by immunoblotting for γ-H2AX.    </td> <td> Radiation doses of 0.6 Gy & 2 Gy to normal human fibroblasts (IMR90) and MCF7 cells resulted in 10.1 & 12.2 DSBs per nucleus on average (0.6 Gy), respectively; increasing to 24 & 27.1 DSBs per nucleus (2 Gy).  </td> </tr> <tr> <td> Kuhne et al., 2005  </td> <td> In vitro. Primary human skin fibroblasts (HSF2) were exposed to 0 – 70 Gy 60Co γ-rays (0.33 Gy/min), X-rays (29 kVp, 1.13 Gy/min), and CKX-rays (0.14 Gy/min). The number of DSBs were determined with pulsed-field gel electrophoresis.  </td> <td> γ-ray and X-ray irradiation of primary human skin fibroblasts (HSF2) at 0 - 70 Gy. γ-rays: (6.1 ± 0.2) x 10-9 DSBs per base pair per Gy, X-rays: (7.0 ± 0.2) x 10-9 DSBs per base pair per Gy. CKX -rays: (12.1 ± 1.9) x 10-9 DSBs per base pair per Gy.  </td> </tr> <tr> <td> Rothkamm, 2003  </td> <td> In vitro. Primary human fibroblast cell lines MRC-5 (lung), HSF1 and HSF2 (skin), and180BR (deficient in DNA ligase IV) were exposed to 1 mGy – 100 Gy X-rays (90 kV). Low doses were delivered at 6 – 60 mGy/min and high doses were delivered at 2 Gy/min. The number of DSBs were determined with pulsed-field gel electrophoresis.  </td> <td> X-ray irradiation of primary human fibroblasts (MRC-5) in the range 1 mGy - 100 Gy, 35 DSBs per cell per Gy.  </td> </tr> <tr> <td> Grudzenski et al, 2010  </td> <td> In vitro. Primary human fibroblasts (HSF1) and C57BL/6NCrl adult mice were exposed to X-rays (2.5 – 200 mGy, 70 mGy/min), and photons (10 mGy – 1 Gy, 2 Gy/min (100 mGy and 1 Gy), and 0.35 Gy/min (10 mGy)). γ-H2AX immunofluorescence was observed to determine DSBs.  </td> <td> X-rays irradiating primary human fibroblasts (HSF1) in the range 2.5 - 100 mGy yielded a response of 21 foci per Gy. When irradiating adult C57BL/6NCrl mice with photons a response of 0.07 foci per cell at 10 mGy was found. At 100 mGy the response was 0.6 foci per cell and finally, at 1 Gy; 8 foci per cell.  </td> </tr> <tr> <td> de Lara, 2001  </td> <td> In vitro. Chinese hamster cells (V79-4) were exposed to 0 – 20 Gy of  60Co γ-rays (2 Gy/min), and ultrasoft X-rays (0.7 – 35 Gy/min): carbon-K shell (0.28 keV), copper L-shell (0.96 keV), aluminum K-shell (1.49 keV), and titanium K-shell (4.55 keV). The number of DSBs were determined with pulsed-field gel electrophoresis.  </td> <td> V79-4 cells irradiated with γ-rays and ultrasoft X-rays (carbon K-shell, copper L-shell, aluminium K-shell and titanum K-shell) in the range 0 - 20 Gy. Response (DSBs per Gy per cell): γ-rays: 41, carbon K-shell: 112, copper L-shell: 94, aluminum K-shell: 77, titanium K-shell: 56.  </td> </tr> <tr> <td> Rübe et al., 2008  </td> <td> In vivo. Brain, lung, heart and small intestine tissue from adult SCID, A-T, BALB/c and C57BL/6NCrl mice; Whole blood and isolated lymphocytes from BALB/c and C57BL/6NCrl mice were exposed to 0.1 – 2 Gy of photons (whole body irradiation, 6 MV, 2 Gy/min) and X-rays (whole body irradiation, 90 kV, 2 Gy/min). γ-H2AX foci were determined with immunochemistry to measure DSBs.  </td> <td> Linear dose-dependent increase in DSBs in the brain, small intestine, lung and heart of C57BL/6CNrl mice after whole-body irradiation with 0.1 - 1.0 Gy of radiation. 0.8 foci per cell (0.1 Gy) and 8 foci per cell (1 Gy).  </td> </tr> <tr> <td> Antonelli et al., 2015  </td> <td> In vitro. Primary human foreskin fibroblasts (AG01522) were exposed to 0 – 1 Gy of 136Cs γ-rays (1 Gy/min), protons (0.84 MeV, 28.5 keV/um), carbon ions (58 MeV/u, 39.4 keV/um), and alpha particles (americium-241, 0.75 MeV/u, 0.08 Gy/min, 125.2 keV/um). γ-H2AX foci were determined with immunochemistry to measure DSBs.  </td> <td> Linear dose-dependent increase in the number of DSBs from 0 - 1 Gy for γ-rays and alpha particles as follows: γ-rays: 24.1 foci per Gy per cell nucleus, alpha particles: 8.8 foci per Gy per cell nucleus.  </td> </tr> <tr> <td> Barnard et al., 2019  </td> <td> In vivo. 10-week-old female C57BL/6 mice were whole-body exposed to 0.5, 1, and 2 Gy of 60Co γ-rays at 0.3, 0.063, and 0.014 Gy/min. p53 binding protein 1 (53BP1) foci were determined via immunofluorescence.  </td> <td> Central LECs showed a linear increase in mean 53BP1 foci/cell with the maximum dose and dose-rate displaying a 78x increase compared to control. Peripheral LECs and lower dose rates displayed similar results, with slightly fewer foci.  </td> </tr> <tr> <td> Ahmadi et al., 2021  </td> <td> In vitro. Human LEC cells were exposed to 137Cs γ-rays at doses of 0, 0.1, 0.25, and 0.5 Gy and dose rates of 0.065 and 0.3 Gy/min. DNA strand breaks were measured using the comet assay.  </td> <td> Human LECs showed a gradual increase in the tail from the comet assay with the maximum dose and dose-rate displaying a 3.7x increase compared to control. Lower dose-rates followed a similar pattern with a lower amount of strand breaks.  </td> </tr> <tr> <td> Hamada et al., 2006  </td> <td> In vitro. Primary normal human diploid fibroblast (HE49) cells were exposed to 0.1, 0.5, and 4 Gy X-rays at 240 kV with a dose rate of 0.5 Gy/min. The number of H2AX foci/cell, which represented DNA strand breaks, was determined 6 – 7 minutes after irradiation through fluorescence microscopy.  </td> <td> Cells displayed a linear increase in the number of H2AX foci/cell, with the maximum dose displaying a 125x increase compared to control.    </td> </tr> <tr> <td>Dubrova & Plumb, 2002</td> <td> </td> <td> At 1 Gy observe 70 DSBs, 1000 single-strange breaks and 2000 damaged DNA bases per cell per Gy. </td> </tr> <tr> <td>Sabirzhanov et al., 2020</td> <td>In vitro. Rat cortical neurons were exposed to 2, 8 or 32 Gy of X rays (320 kV) at a dose rate of 1.25 Gy/min. Western blot was used to measure γ-H2AX, p-ataxia telangiectasia mutated (ATM) and p- ATM/RAD3-related (ATR) levels.  </td> <td>In rat cortical neurons, p-ATM increased at 2, 8, and 32 Gy, with a 15-fold increase at 8 and 32 Gy. γ-H2AX levels increased at 8 and 32 Gy. </td> </tr> <tr> <td>Geisel et al., 2012 </td> <td>In vivo. Patients with suspected coronary artery disease receiving X-rays from computed tomography or conventional coronary angiography had levels of DSBs assessed in blood lymphocytes by γ-H2AX fluorescence. </td> <td>There was a correlation between effective dose (in mSv) and DSBs. For both conventional coronary angiography and computed tomography, a dose of 10 mSv produced about 2-fold more DNA DSBs than a dose of 5 mSv. </td> </tr> <tr> <td>Ungvari et al., 2013 </td> <td>In vitro. Rat cerebromicrovascular endothelial cells and hippocampal neurons were irradiated with 2-10 Gy of 137Cs gamma rays. DNA strand breaks were assessed with the comet assay. </td> <td>DNA damage increased at all doses (2-10 Gy). In the control, less than 5% of DNA was in the tail, while by 6 Gy, 35% of the DNA was in the tail in cerebromicrovascular endothelial cells and 25% was in the tail in neurons. </td> </tr> <tr> <td>Rombouts et al., 2013 </td> <td>In vitro. EA.hy926 cells and human umbilical vein endothelial cells were irradiated with various doses of X-rays (0.25 Gy/min). γ-H2AX foci were assessed with immunofluorescence. </td> <td>More γ-H2AX foci were observed at higher doses in both cell types. In human umbilical vein endothelial cells, few foci/nucleus were observed at 0.05 Gy, with about 23 at 2 Gy. In EA.hy926 cells, few foci/nucleus were observed at 0.05 Gy, with about 37 at 2 Gy. </td> </tr> <tr> <td>Baselet et al., 2017 </td> <td>In vitro. Human telomerase-immortalized coronary artery endothelial cells were irradiated with various doses of X-rays (0.5 Gy/min). Immunocytochemical staining was performed for γ-H2AX and 53BP1 foci. </td> <td>Doses of 0.05 and 0.1 Gy did not increase the number of γ-H2AX foci, but 0.5 Gy increased foci number by 5-fold and 2 Gy by 15-fold. A dose of 0.05 Gy did not increase the number of 53BP1 foci, but 0.1 Gy, 0.5 Gy and 2 Gy increased levels by 3-fold, 7-fold and 8-fold, respectively. </td> </tr> </tbody> </table>   Time Concordance  <table border="1"> <tbody> <tr> <td> Reference  </td> <td> Experiment Description  </td> <td> Result  </td> </tr> <tr> <td> Rogakou et al., 1999  </td> <td> In vitro. Normal human fibroblasts (IMR90), human breast cancer cells (MCF7), human astrocytoma cells (SF268), Indian muntjac Muntiacus muntjak normal skin fibroblasts, Xenopus laevisA6 normal kidney cells, Drosophila melanogaster epithelial cells, and Saccharomyces cerevisiae were exposed to 0.6, 2, 20, 22, 100, and 200 Gy 137Cs γ-rays. Doses below 20 Gy were delivered at 15.7 Gy/min and other doses were delivered in 1 minute. DNA breaks were visualized using γ-H2AX antibodies and microscopy.  </td> <td> DSBs were present at 3 min and persisted from 15 - 60 min.  </td> </tr> <tr> <td> Hamada & Woloschak, 2017  </td> <td> In vitro. human LECs were exposed to 0.025 Gy X-rays at 0.42 – 0.45 Gy/min. 53BP1 foci were measured via indirect immunofluorescence.  </td> <td> In cells immediately exposed to 0.025 Gy, the level of 53BP1 foci/cell increased to 3.3x relative to control 0.5 h post-irradiation.  </td> </tr> <tr> <td> Hamada et al., 2006  </td> <td> In vitro. Primary normal human diploid fibroblast (HE49) cells were exposed to 0.1, 0.5, and 4 Gy (deposition of energy) at 240 kV with a dose rate of 0.5 Gy/min. The number of H2AX foci/cell, which represented DNA strand breaks, was determined through fluorescence microscopy.  </td> <td> In cells immediately exposed to 0.5 Gy, 11% of cells had 18 foci six min post-irradiation, compared to 90% of controls having 0 foci.   </td> </tr> <tr> <td> Acharya et al., 2010  </td> <td> In vitro. Human neural stem cells were exposed to 1, 2 and 5 Gy of γ-rays at a dose rate of 2.2 Gy/min. The levels of γ-H2AX phosphorylation post irradiation were assessed by immunocytochemistry, fluorescence-activated cell sorting (FACS) analysis and γ-H2AX foci enumeration.  </td> <td> The number of cells positive for nuclear γ-H2AX foci peaked at 20 min post-irradiation. After 1h, this level quickly declined.   </td> </tr> <tr> <td> Schmal et al., 2019  </td> <td> In vivo. Juvenile and adult C57BL/6 mice were exposed to whole body 6-MV photons at 2 Gy/min. Irradiations were done in 5x, 10x, 15x and 20x fractions of 0.1 Gy. Double staining for NeuN and 53BP1 was used to quantify DNA damage foci and the possible accumulation in the hippocampal dentate gyrus.  </td> <td> To assess possible accumulation of persisting 53BP1-foci during fractionated radiation, juvenile and adult mice were examined 72 h after exposure to 5×, 10×, 15×, or 20× fractions of 0.1 Gy, compared to controls. The number of persisting 53BP1-foci increased significantly in both juvenile and adult mice during fractionated irradiation (maximum at 1 m post-IR).  </td> </tr> <tr> <td> Dong et al., 2015  </td> <td> In vivo. C57BL/6J mice were exposed to 2 Gy of X-rays at 2 Gy/min using a 6 MV source. γ-H2AX foci were assessed with immunofluorescence in the brain.  </td> <td> At 0.5 h, about 14 γ-H2AX foci/cell were present. This decreased linearly to about 2 foci/cell at 24 h, with no foci/cell from 48 h to 6 weeks.  </td> </tr> <tr> <td> Barazzuol et al., 2017  </td> <td> In vivo. C57BL/6 mice were exposed to 0.1 or 2 Gy of X-rays (250 kV) at a rate of 0.5 Gy/min. 53BP1 foci were quantified with immunofluorescence in neural stem cells and neuron progenitors in the lateral ventricle.   </td> <td> At both 0.5 and 6 h post-irradiation, increased 53BP1 foci were observed, with the highest level at 0.5 h.  </td> </tr> <tr> <td> Sabirzhanov et al., 2020    </td> <td> In vitro. Rat cortical neurons were exposed to 2, 8 or 32 Gy of X rays (320 kV) at a dose rate of 1.25 Gy/min. Western blot was used to measure γ-H2AX, p-ATM and p-ATR levels.   </td> <td> In rat cortical neurons, γ-H2AX, p-ATM and p-ATR all increased at 30 minutes post-irradiation, with a sustained increase until 6 h.  </td> </tr> <tr> <td> Zhang et al., 2017  </td> <td> In vitro. HT22 hippocampal neuronal cellsT were irradiated with X-rays (320 kVp) at 8 or 12 Gy at a dose rate of 4 Gy/min. The comet assay was preformed to assess the DNA double strand breaks in HT22 cells. Western blot was used to measure γ-H2AX and p-ATM.  </td> <td> At 8 Gy, the comet assay showed an increased tail moment at both 30 minutes and 24 h post-irradiation. At 12 Gy, p-ATM was increased over 4-fold at both 30 minutes and 1 h post-irradiation. γ-H2AX was increased over 3-fold at 30 minutes post-irradiation and almost 2-fold at 1 and 24 h.  </td> </tr> <tr> <td> Geisel et al., 2012  </td> <td> In vivo. Patients with suspected coronary artery disease receiving X-rays from computed tomography or conventional coronary angiography had levels of DSBs assessed in blood lymphocytes by γ-H2AX fluorescence.  </td> <td> DSBs were increased at 1 h post-irradiation and returned to pre-irradiation levels by 24 h.  </td> </tr> <tr> <td> Park et al., 2022  </td> <td> In vitro. Human aortic endothelial cells were irradiated with 137Cs gamma rays at 4 Gy (3.5 Gy/min). γ-H2AX was measured with western blot. p-ATM and 53BP1 were determined with immunofluorescence.  </td> <td> γ-H2AX, p-ATM, and 53BP1 were shown increased at 1 h post-irradiation and slightly decreased for the rest of the 6 h but remained elevated above the control.  </td> </tr> <tr> <td> Kim et al., 2014  </td> <td> In vitro. Human umbilical vein endothelial cells were irradiated with 4 Gy of 137Cs gamma rays. γ-H2AX levels were determined with immunofluorescence.  </td> <td> γ-H2AX foci greatly increased at 1 and 6 h post-irradiation, with the greatest increase at 1 h.  </td> </tr> <tr> <td> Dong et al., 2014  </td> <td> In vitro. Human umbilical vein endothelial cells were irradiated with 2 Gy of 137Cs gamma rays. γ-H2AX levels were determined with immunofluorescence.  </td> <td> γ-H2AX foci increased 8-fold at 3 h, 7-fold at 6 h, and 2-fold at 12 and 24 h post-irradiation.  </td> </tr> <tr> <td> Rombouts et al., 2013  </td> <td> In vitro. EA.hy926 cells and human umbilical vein endothelial cells were irradiated with X-rays (0.25 Gy/min). γ-H2AX foci were assessed with immunofluorescence.  </td> <td> The greatest increase in γ-H2AX foci was observed 30 minutes post-irradiation, while levels were still slightly elevated at 24 h.  </td> </tr> <tr> <td> Nübel et al., 2006  </td> <td> In vitro. Human umbilical vein endothelial cells were irradiated with gamma rays at 20 Gy. DNA strand breaks were assessed with the comet assay and western blot for γ-H2AX.  </td> <td> The olive tail moment increased 5-fold immediately after irradiation and returned to control levels by 4 h. A large increase in γ-H2AX was observed at 0.5 h post-irradiation, with lower levels at 4 h but still above the control.  </td> </tr> <tr> <td> Baselet et al., 2017  </td> <td> In vitro. Human telomerase-immortalized coronary artery endothelial cells were irradiated with various doses of X-rays (0.5 Gy/min). Immunocytochemical staining was performed for γ-H2AX and 53BP1 foci.  </td> <td> Increased γ-H2AX and 53BP1 foci were observed at 0.5 h post-irradiation, remaining elevated at 4 h but returning to control levels at 24 h.  </td> </tr> <tr> <td> Gionchiglia et al., 2021  </td> <td> In vivo. Male CD1 and B6/129 mice were irradiated with X-rays at 10 Gy. Brain sections were single or double-stained with antibodies against γ-H2AX and p53BP1.   </td> <td> In the forebrain, cerebral cortex, hippocampus and subventricular zone (SVZ)/ rostral migratory stream (RMS)/ olfactory bulb (OB), γH2AX and p53BP1 positive cells increased at both 15 and 30 minutes post-irradiation, with the greatest increase at 30 minutes.  </td> </tr> </tbody> </table>

There is evidence of a response-response relationship between the deposition of energy and the frequency of DSBs. In studies encompassing a variety of biological models, radiation types and radiation doses, a positive, linear relationship was found between the radiation dose and the number of DSBs (Aufderheide et al., 1987; Sidjanin, 1993; Frankenberg et al., 1999; Sutherland et al., 2000; de Lara et al., 2001; Baumstark-Khan et al., 2003; Rothkamm & Lo, 2003; Kuhne et al., 2005; Rube et al., 2008; Grudzenski et al., 2010; Bannik et al., 2013; Shelke & Das, 2015; Antonelli et al., 2015; Hamada, 2017b; Dalke, 2018; Barazzuol et al., 2017; Geisel et al., 2012; Ungvari et al., 2013; Rombouts et al., 2013; Baselet et al., 2017). There were, however, at least four exceptions reported. When human blood lymphocytes were irradiated with X-rays in vitro, a linear relationship was only found for doses ranging from 6 - 500 mGy; at low doses from 0 - 6 mGy, there was a quadratic relationship reported (Beels et al., 2009). Secondly, simulation studies predicted that there would be a non-linear increase in DSBs as energy deposition increased, with a saturation point at higher LETs (Charlton et al., 1989). Furthermore, primary normal human fibroblasts exposed to 1.2 – 5 mGy X-rays at 5.67 mGy/min showed a supralinear relationship, indicating at low doses, the DSBs are mostly due to radiation-induced bystander effects. Doses above 10 mGy showed a positive linear relationship (Ojima et al., 2008). Finally, in the human lens epithelial cell line SRA01/04, DNA strand breaks appeared immediately after exposure to UVB (0.14 J/cm2) and were repaired after 30 minutes. They then reappeared after 60 and 90 minutes. Both were once again repaired within 30 minutes. However, the two subsequent stages of DNA strand breaks did not occur when exposed to a lower dose of UVB (0.014 J/cm2) (Cencer et al., 2018).

Data from temporal response studies suggests that DSBs likely occur within seconds to minutes of energy deposition by ionizing radiation. In a variety of biological models, the presence of DSBs has been well documented within 10 - 30 minutes of radiation exposure (Rogakou et al., 1999; Rube et al., 2008; Beels et al., 2009; Kuefner et al., 2009; Grudzenski et al., 2010; Antonelli et al., 2015; Acharya et al., 2010; Dong et al., 2015; Barazzuol et al., 2017; Sabirzhanov et al., 2020; Rombouts et al., 2013; Nübel et al., 2006; Baselet et al., 2017; Zhang et al., 2017; Gionchiglia et al., 2021); there is also evidence that DSBs may actually be present within 3 - 5 minutes of irradiation (Kleiman, 1990; Rogakou et al., 1999; Rothkamm & Lo, 2003; Rube et al., 2008; Grudzenski et al., 2010; Cencer et al., 2018). Interestingly, one study that focussed on monitoring the cells before, during and after irradiation by taking photos every 5, 10 or 15 seconds found that foci indicative of DSBs were present 25 and 40 seconds after collision of the alpha particles and protons with the cell, respectively. The number of foci were found to increase over time until plateauing at approximately 200 seconds after alpha particle exposure and 800 seconds after proton exposure (Mosconi et al., 2011). After the 30 minute mark, DSBs have been shown to rapidly decline in number. By 24 hours post-irradiation, DSB numbers had declined substantially in systems exposed to radiation doses between 40 mGy and 80 Gy (Aufderheide et al., 1987; Baumstark-Khan et al., 2003; Rothkamm & Lo, 2003; Rube et al., 2008; Grudzenski et al., 2010; Bannik et al., 2013; Markiewicz et al., 2015; Russo et al., 2015; Antonelli et al., 2015; Dalke, 2018; Bains, 2019; Barnard, 2019; Ahmadi et al., 2021; Dong et al., 2015; Dong et al., 2014; Sabirzhanov et al., 2020; Rombouts et al., 2013; Baselet et al., 2017; Gionchiglia et al., 2021), with the sharpest decrease documented within the first 5 h (Kleiman, 1990; Sidjanin, 1993; Rogakou et al., 1999; Rube et al., 2008; Kuefner et al., 2009; Grudzenski et al., 2010; Bannik, 2013; Markiewicz et al., 2015; Shelke and Das, 2015; Cencer et al., 2018; Acharya et al., 2010; Park et al., 2022; Kim et al., 2014; Nübel et al., 2006). Interestingly, DSBs were found to be more persistent when they were induced by higher LET radiation (Aufderheide et al., 1987, Baumstark-Khan et al., 2003; Antonelli et al., 2015).

Not identified.

High Unspecific

High

All life stages

High High High Low Low Low

This KER is plausible in all life stages, sexes, and organisms with DNA. The majority of the evidence is from In vivo adult mice and human In vitro models that do not specify the sex.

#<Reference::ActiveRecord_Associations_CollectionProxy:0x00007b42eb268fc8> AOPWiki 2019-08-26T12:00:06

2023-05-15T13:35:01

<upstream-id>efbb5ace-1e19-40ab-8744-e25d1645f8d1</upstream-id> <downstream-id>7f173d50-1f65-4d3a-8232-d1804aad3edd</downstream-id>

#<Reference::ActiveRecord_Associations_CollectionProxy:0x00007b42eb2c1718> AOPWiki 2022-03-01T15:58:49

2022-03-01T15:58:49

<upstream-id>7f173d50-1f65-4d3a-8232-d1804aad3edd</upstream-id> <downstream-id>2be30b90-999e-4e2c-b7cb-96b9f08b6527</downstream-id>

#<Reference::ActiveRecord_Associations_CollectionProxy:0x00007b42eb321910> AOPWiki 2020-04-30T16:44:14

2020-04-30T16:44:14

<upstream-id>2be30b90-999e-4e2c-b7cb-96b9f08b6527</upstream-id> <downstream-id>f1cd90b2-6194-4543-ab4b-841ef69aa327</downstream-id>

#<Reference::ActiveRecord_Associations_CollectionProxy:0x00007b42eb3860b8> AOPWiki 2022-03-01T12:49:10

2022-03-01T12:49:10

<upstream-id>f1cd90b2-6194-4543-ab4b-841ef69aa327</upstream-id> <downstream-id>3952ddde-373a-4ba0-8e33-ade09d9d8c4e</downstream-id> SEE BIOLOGICAL PLAUSIBILITY BELOW

Updated 03/20/2017

Using a relatively simple density-dependent population model and assuming constant young of year survival with no immigration/emigration, reductions in cumulative fecundity have been predicted to yield declines in population size over time (Miller and Ankley 2004). Under real-world environmental conditions, outcomes may vary depending on how well conditions conform with model assumptions. Nonetheless, cumulative fecundity can be considered one vital rate that contributes to overall population trajectories (Kramer et al. 2011).

<ul> <li>Using a relatively simple density-dependent population model and assuming constant young of year survival with no immigration/emigration, reductions in cumulative fecundity have been predicted to yield declines in population size over time (Miller and Ankley 2004). However, it should be noted that the model was constructed in such a way that predicted population size is dependent on cumulative fecundity, therefore this is a fairly weak form of empirical support.</li> <li>In a study in which an entire lake was treated with 17alpha-ethynyl estradiol, Kidd et al. (2007) declines in fathead minnow population size were associated with signs of reduced fecundity.</li> </ul>

<ul> <li>Wester et al. (2003) and references cited therein suggest that although egg production is an endpoint of demographic significance, incomplete reductions of egg production may not translate in a simple manner to population reductions. Compensatory effects of reduced predation and reduced competition for limited food and/or habitat resources may offset the effects of incomplete reductions in egg production.</li> <li>Fish and other egg laying animals employ a diverse range of reproductive strategies and life histories. The nature of the relationship between reduced spawning frequency and cumulative fecundity and overall population trajectories will depend heavily on the life history and reproductive strategy of the species in question. Relationships developed for one species will not necessarily hold for other species, particularly those with differing life histories.</li> </ul>

<ul> <li>Cumulative fecundity is one example of a vital rate that can influence population size over time. A variety of population model constructs can be adapted to utilize measurements or estimates of cumulative fecundity as a predictor of population trends over time (e.g., (Miller and Ankley 2004; Miller et al. 2013).</li> <li>The model of Miller et al. 20014 uses a relatively simple density-dependent population model and assuming constant young of year survival with no immigration/emigration, use measures of cumulative fecundity to predict relative change in in population size over time (Miller and Ankley 2004).</li> </ul>

Not Specified Unspecific

Not Specified

All life stages

Moderate

Spawning generally refers to the release of eggs and/or sperm into water, generally by aquatic or semi-aquatic organisms. Consequently, by definition, this KER is likely applicable only to organisms that spend a portion of their life-cycle in or near aquatic environments.

#<Reference::ActiveRecord_Associations_CollectionProxy:0x00007b42eb3ed060> AOPWiki 2016-11-29T18:41:33

2017-03-20T13:49:05

Deposition of energy leading to population decline via DNA strand breaks and oocyte apoptosis

Deposition of energy leading to population decline via DSB and apoptosis

Agnes Aggy

You Song1, Knut Erik Tollefsen1,2,3 1Norwegian Institute for Water Research (NIVA), Økernveien 94, 0579 Oslo, Norway 2Centre for Environmental Radioactivity (CERAD), Norwegian University of Life Sciences (NMBU), Post box 5003, N-1432 Ås, Norway 3Norwegian University of Life Sciences (NMBU), Faculty of Environmental Sciences and Natural Resource Management (MINA), Post box 5003, N-1432 Ås, Norway

BY-SA

1.0

It is well documented that ionizing radiation( (eg. X-rays, gamma, photons, alpha, beta, neutrons, heavy ions) leads to energy deposition on the atoms and molecules of the substrate. Many studies, have demonstrated that the type of radiation and distance from source has an impact on the pattern of energy deposition (Alloni, et al. 2014). High linear energy transfer (LET) radiation has been associated with higher-energy deposits (Liamsuwan et al., 2014) that are more densely-packed and cause more complex effects within the particle track (Hada and Georgakilas, 2008; Okayasu, 2012ab; Lorat et al., 2015; Nikitaki et al., 2016) in comparison to low LET radiation. Parameters such as mean lineal energy, dose mean lineal energy, frequency mean specific energy and dose mean specific energy can impact track structure of the traversed energy into a medium (Friedland et al., 2017). The detection of energy deposition by ionizing radiation can be demonstrated with the use of fluorescent nuclear track detectors (FNTDs). FNTDs used in conjunction with fluorescent microscopy, are able to visualize radiation tracks produced by ionizing radiation (Niklas et al., 2013; Kodaira et al., 2015; Sawakuchi and Akselrod, 2016). In addition, these FNTD chips can quantify the LET of primary and secondary radiation tracks up to 0.47 keV/um (Sawakuchi and Akselrod, 2016). This co-visualization of the radiation tracks and the cell markers enable the mapping of the radiation trajectory to specific cellular compartments, and the identification of accrued damage (Niklas et al., 2013; Kodaira et al., 2015). There are no known chemical initiators or prototypes that can mimic the MIE.

Cumulative fecundity is the most apical endpoint considered in the OECD 229 Fish Short Term Reproduction Assay. The OECD 229 assay serves as screening assay for endocrine disruption and associated reproductive impairment (<a href="http://www.oecd-ilibrary.org/environment/test-no-229-fish-short-term-reproduction-assay_9789264185265-en">OECD 2012</a>). Fecundity is also an important apical endpoint in the Medaka Extended One Generation Reproduction Test (MEOGRT; <a href="http://www.oecd-ilibrary.org/environment/test-no-240-medaka-extended-one-generation-reproduction-test-meogrt_9789264242258-en">OECD Test Guideline 240</a>; OECD 2015). A variety of fish life cycle tests also include cumulative fecundity as an endpoint (<a href="http://www.oecd.org/officialdocuments/publicdisplaydocumentpdf/?cote=env/jm/mono(2008)22&doclanguage=en">OECD 2008</a>).

Maintenance of sustainable fish and wildlife populations (i.e., adequate to ensure long-term delivery of valued ecosystem services) is a widely accepted regulatory goal upon which risk assessments and risk management decisions are based.

adjacent

Not Specified

Not Specified adjacent

Not Specified

Not Specified adjacent

Not Specified

Not Specified adjacent

Not Specified

Not Specified adjacent

Not Specified

High Female

High

Adult, reproductively mature

High Not Specified

High

AOPWiki 2017-06-29T08:00:09

2023-09-25T16:26:57