## Life Stage Applicability

This key event is mainly applicable to all life stages most evidence is derived from adult models (Betlazar et al., 2016; Paladini et al., 2021).

<table><thead><tr><td>Life stage</td><td>Evidence</td></tr></thead><tbody><tr><td>All life stages</td><td></td></tr></tbody></table>

## Sex Applicability

This key event is not sex specific (Betlazar et al., 2016; Paladini et al., 2021).

## Evidence for Perturbation by Prototypic Stressor

Current literature provides ample evidence of tissue resident cell activation being induced by ionizing radiation (Allen et al., 2020; Krukowski et al., 2018; Parihar et al., 2020; Parihar et al., 2018; Parihar et al., 2016; Poulose et al., 2011; Raber et al., 2019; Sumam et al., 2013).

## Key Event Description

Tissue resident cell activation is considered as a hallmark of inflammation irrespective of the tissue type. Strategically placed cells within tissues respond to noxious stimuli, thus regulating the recruitment of neutrophil and the initiation and resolution of inflammation (Kim and Luster, 2015). Examples for these cells are resident immune cells, parenchymal cells, vascular cells, stromal cells, or smooth muscle cells. These cells may be specific for a certain tissue, but they have a common tissue-independent role.

Under healthy conditions there is a homeostatic state, characterized as a generally quiescent cellular milieu. Various danger signals or alarmins that are involved in induction of inflammation like pathogen-associated molecular pattern molecules (PAMPs) and damage-associated molecular pattern molecules (DAMPs) activate these resident cells in affected tissues.

Examples of well-characterized DAMPs (danger signals or alarmins) (Saïd-Sadier and Ojcius, 2012; Roh and Sohn, 2018; Dukay et al., 2019)

<table><thead><tr><td>DAMPs</td><td>Receptors</td><td>Outcome of receptor ligation</td></tr></thead><tbody><tr><td>Extracellular nucleotides (ATP, ADP, adenosine)</td><td>PI, P2X and P2Y receptors (ATP, ADP); AI, A2A, A2B and A3 receptors (adenosine)</td><td>Dendritic cell (DC) maturation, chemotaxis, secretion of cytokines (IL-1β, IL-18), inflammation</td></tr><tr><td>Extracellular heat shock proteins</td><td>CD14, CD91, scavenger receptors, TLR4, TLR2, CD40</td><td>DC maturation, cytokine induction, DC, migration to lymph nodes</td></tr><tr><td>Extracellular HMGB1</td><td>RAGE, TLR2, TLR4</td><td>Chemotaxis, cytokine induction, DC activation, neutrophil recruitment, inflammation, activation of immune cells</td></tr><tr><td>Uric acid crystals</td><td>CD14, TLR2, TLR4</td><td>DC activation, cytokine induction, neutrophil recruitment, gout induction</td></tr><tr><td>Oxidative stress</td><td>Intracellular redox-sensitive proteins</td><td>Cell death, release of endogenous DAMPs, inflammation</td></tr><tr><td>Laminin</td><td>Integrins</td><td>Neutrophil recruitment, chemotaxis</td></tr><tr><td>S100 proteins or calgranulins</td><td>RAGE</td><td>Neutrophil recruitment, chemotaxis, cytokine secretion, apoptosis</td></tr><tr><td>Hyaluronan</td><td>TLR2, TLR4, CD44</td><td>DC maturation, cytokine production, adjuvant activity</td></tr><tr><td>Heat shock proteins (HSPs)</td><td>Scavenger receptors, TLR2, TLR4</td><td>Inflammation, cytokine production</td></tr></tbody></table>

Activation refers to a phenotypic modification of the resident cells that includes alterations in their secretions, activation of biosynthetic pathways, production of pro-inflammatory proteins and lipids, and morphological changes. While these represent a pleiotropic range of responses that can vary with the tissue, there are a number of common markers or signs of activation that are measurable.

Examples of Common markers are

* CD11b

* Iba1
* GFAP CD68 CD86

* Mac-1 NF-kB AP-1

* Jnk

* P38/MAPK

These described commonalities allow the use of this KE as a hub KE in the AOP network. However, despite the similarities in the inflammatory process, the type of reactive cells and the molecules triggering their reactivity may be tissue-specific. Therefore, for practical reasons, a tissue specific description of the reactive cells and of the triggering factors is necessary in order to specify in a tissue-specific manner, which cell should be considered and what should be measured.

## Brain

The most easily detectable feature of brain inflammation or neuroinflammation is activation of microglial cells and astrocytes. It is evidenced by changes in shape, increased expression of certain antigens, and accumulation and proliferation of the glial cells in affected regions (Aschner, 1998; Graeber & Streit, 1990; Monnet-Tschudi et al, 2007; Streit et al, 1999; Kraft and Harry, 2011; Claycomb et al., 2013). Upon stimulation by cytokines, chemokines or inflammogens (e.g. from pathogens or from damaged neurons), both glial cell types activate inflammatory signaling pathways, which result in increased expression and/or release of inflammatory mediators such as cytokines, eicosanoids, and metalloproteinases (Dong & Benveniste, 2001) (cf KE: pro-inflammatory mediators, increased), as well as in the production of reactive oxygen species (ROS) and nitrogen species (RNS) (Brown & Bal-Price, 2003). Different types of activation states are possible for microglia and astrocytes, resulting in pro-inflammatory or anti-inflammatory signaling, and other cellular functions (such as phagocytosis) (Streit et al., 1999; Nakajima and Kohsaka, 2004). Therefore, neuroinflammation can have both neuroprotective/neuroreparative and neurodegenerative consequences (Carson et al., 2006; Monnet-Tschudi et al, 2007; Aguzzi et al., 2013; Glass et al., 2010). Under normal physiological conditions, microglial cells survey the nervous system for neuronal integrity (Nimmerjahn et al, 2005) and for invading pathogens (Aloisi, 2001; Kreutzberg, 1995; Kreutzberg, 1996; Rivest, 2009). They are the first type of cell activated (first line of defense), and can subsequently induce astrocyte activation (Falsig, 2008). Two distinct states of microglial activation have been described (Gordon, 2003; Kigerl et al, 2009; Maresz et al, 2008; Mosser & Edwards, 2008; Perego et al; Ponomarev et al, 2005): The M1 state is classically triggered by interferon-gamma and/or other pro-inflammatory cytokines, and this state is characterized by increased expression of integrin alpha M (Itgam) and CD86, as well as the release of pro-inflammatory cytokines (TNF-alpha, IL-1beta, IL-6), and it is mostly associated with neurodegeneration. The M2 state is triggered by IL-4 and IL-13 (Maresz et al, 2008; Perego et al, 2011; Ponomarev et al, 2007) and induces the expression of mannose receptor 1 (MRC1), arginase1 (Arg 1) and Ym1/2; it is involved in repair processes. The activation of astrocytes by microglia-derived cytokines or TLR agonists resembles the microglial M1 state (Falsig 2006). Although classification of the M1/M2 polarization of microglial cells may be considered as a simplification of authentic microglial reaction states (Ransohoff, 2016), a similar polarization of reactive astrocytes has been described recently (Liddlelow et al., 2017): Interleukin-1 alpha (IL-1a), TNF and subcomponent q (C1q) released by activated microglial cells induce A1-reactive astrocytes, which lose the ability to promote neuronal survival, outgrowth, synaptogenesis and phagocytosis and induce the death of neurons and oligodendrocytes.

## How it is Measured or Detected

Measurement targets are cell surface and intracellular markers; the specific markers may be cell and species-specific.

Available methods include cytometry, immunohistochemistry, gene expression sequencing; western blotting, ELISA, and functional assays.
Neuroinflammation, i.e. the activation of glial cells can be measured by quantification of cellular markers (most commonly), or of released mediators (less common). As multiple activation states exist for the two main cell types involved, it is necessary to measure several markers of neuroinflammation:

Microglial activation can be detected based on the increased numbers of labeled microglia per volume element of brain tissue (due to increase of binding sites, proliferation, and immigration of cells) or on morphological changes. A specific microglial marker, used across different species, is CD11b. Alternatively various specific carbohydrate structures can be stained by lectins (e.g. IB4). Beyond that, various well-established antibodies are available to detect microglia in mouse tissue (F4/80), phagocytic microglia in rat tissue (ED1) or more generally microglia across species (Iba1). Transgenic mice are available with

fluorescent proteins under the control of the CD11b promoter to easily quantify microglia without the need for specific stains.

The most frequently used astrocyte marker is glial fibrillary acidic protein, GFAP (99% of all studies) (Eng et al., 2000). This protein is highly specific for astrocytes in the brain, and antibodies are available for immunocytochemical detection. In neuroinflammatory brain regions, the stain becomes more prominent, due to an upregulation of the protein, a shape change/proliferation of the cells, and/or better accessibility of the antibody. Various histological quantification approaches can be used. Occasionally, alternative astrocytic markers, such as vimentin of the S100beta protein, have been used for astrocyte staining (Struzynska et al., 2007). Antibodies for complement component 3 (C3), the most characteristic and highly upregulated marker of A1 neurotoxic reactive astrocytes are commercially available.

All immunocytochemical methods can also be applied to cell culture models.

In patients, microglial accumulation can be monitored by PET imaging, using [11C]-PK 11195 as a microglial marker (Banati et al., 2002).

Activation of glial cells can be assessed in tissue or cell culture models also by quantification of sets of M1/M2 phenotype markers. This can for instance be done by PCR quantification, immunocytochemistry, immunoblotting.

Itgam, CD86 expression as markers of M1 microglial phenotype Arg1, MRC1, as markers of M2 microglial phenotype

(for descriptions of techniques, see Falsig 2004; Lund 2006; Kuegler 2010; Monnet-Tschudi et al., 2011; Sandström et al., 2014; von Tobel et al., 2014)

## LIVER:

Kupffer cell activation can be measured by means of expressed cytokines, e.g. tissue levels of TNF-a [Vajdova et al, 2004], IL-6 expression, measured by immunoassays or Elisa (offered by various companies), soluble CD163 [Grønbaek et al., 2012; Møller et al., 2012] or increase in expression of Kupffer cell marker genes such as Lyz, Gzmb, and Il1b, (Genome U34A Array, Affymetrix); [Takahara et al., 2006]
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Brain:

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Falsig J, van Beek J, Hermann C, Leist M. Molecular basis for detection of invading pathogens in the brain. J Neurosci Res. 2008 May 15;86(7):1434-47.

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Kigerl KA, Gensel JC, Ankeny DP, Alexander JK, Donnelly DJ, Popovich PG (2009) Identification of two distinct macrophage subsets with divergent effects causing either neurotoxicity or regeneration in the injured mouse spinal cord. J Neurosci 29: 13435-13444
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## Liver:

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Short Name: Increase, Pro-Inflammatory Mediators

Key Event Component

<table><thead><tr><td>Process</td><td>Object</td><td>Action</td></tr></thead><tbody><tr><td>inflammatory response</td><td></td><td>increased</td></tr></tbody></table>

AOPs Including This Key Event

<table><thead><tr><td>AOP Name</td><td>Role of event in AOP</td></tr></thead><tbody><tr><td>AOP: 483 – Deposition of Energy Leading to Learning and Memory Impairment</td><td>Key Event</td></tr></tbody></table>

Biological context

<table><thead><tr><td>Level of Biological Organization</td></tr></thead><tbody><tr><td>Tissue</td></tr></tbody></table>

Domain of Applicability

Taxonomic Applicability

The inflammatory response and increase of the pro-inflammatory mediators has been observed across species from simple invertebrates such as Daphnia to higher order vertebrates (Weavers & Martin, 2020).

<table><thead><tr><td>Term</td><td>Scientific Term</td><td>Evidence</td><td>Link</td></tr></thead><tbody><tr><td>human</td><td>Homo sapiens</td><td>Low</td><td>NCBI</td></tr><tr><td>rat</td><td>Rattus norvegicus</td><td>Low</td><td>NCBI</td></tr><tr><td>mouse</td><td>Mus musculus</td><td>Low</td><td>NCBI</td></tr></tbody></table>

Life Stage Applicability

This key event is not life stage specific (Kalm et al., 2013; Veeraraghan et al., 2011; Hladik & Tapio, 2016).

<table><thead><tr><td>Life stage</td><td>Evidence</td></tr></thead><tbody><tr><td>Not Otherwise Specified</td><td>Moderate</td></tr></tbody></table>

Sex Applicability

Most studies conducted were on male models, although sex-dependent differences in pro-inflammatory markers have been previously reported (Cekanaviciute et al., 2018; Parihar et al., 2020).

<table><thead><tr><td>Term</td><td>Evidence</td></tr></thead><tbody><tr><td>Mixed</td><td>Moderate</td></tr></tbody></table>

Evidence for Perturbation by Prototypic Stressor

There is evidence of the increase of pro-inflammatory mediators following perturbation from a variety of stressors including exposure to ionizing radiation. (Abdel-Magied et al., 2019; Cho et al., 2017; Gaber et al., 2003; Ismail et al., 2016; Kim et al. 2002; Lee et al., 2010; Parihar et al., 2018)

Key Event Description

(Adapted from KE 1493)

Inflammatory mediators are soluble, diffusible molecules that act locally at the site of tissue damage and infection, and at more distant sites. They can be divided into exogenous and endogenous mediators.

Exogenous mediators of inflammation are bacterial products or toxins like endotoxin or lipopolysaccharides (LPS). Endogenous mediators of inflammation are produced from within the (innate and adaptive) immune system itself, as well as other systems. They can be derived from
molecules that are normally present in the plasma in an inactive form, such as peptide fragments of some components of complement, coagulation, and kinin systems. Or they can be released at the site of injury by a number of cell types that either contain them as preformed molecules within storage granules, e.g. histamine, or which can rapidly switch on the machinery required to synthesize the mediators.

Pro-inflammatory mediators can have dual properties of anti-inflammatory and pro-inflammatory effects, dysregulation of the balance can lead to chronic inflammation which is implicated in many diseases such as cardiovascular diseases, neurodegenerative diseases or cancer

Examples of pro-inflammatory mediators are provided below in Table 1.

<table><caption>Table 1: a non-exhaustive list of examples for pro-inflammatory mediators</caption><thead><tr><td>Classes of inflammatory mediators</td><td>Examples</td></tr></thead><tbody><tr><td>Pro-inflammatory cytokines</td><td>TNF-α, Interleukins (IL-1, IL-6, IL-8), Interferons (IFN-γ), chemokines (CXCL, CCL, GRO-α, MCP-1), GM-CSF</td></tr><tr><td>Prostaglandins</td><td>PGE2</td></tr><tr><td>Bioactive peptides</td><td>Bradykinin</td></tr><tr><td>Vasoactive amines</td><td>histamine, serotonin</td></tr><tr><td>Reactive oxygen species (ROS)</td><td>O2-, H2O2</td></tr><tr><td>Reactive nitrogen species (RNS)</td><td>NO, iNOS</td></tr></tbody></table>

The increased production of pro-inflammatory mediators can have negative consequences on the parenchymal cells leading even to cell death, as described for TNF-α or peroxynitrite on neurons (Brown and Bal-Price, 2003). Along with TNF-α, IL-1β and IL-6 have been shown to exhibit negative consequences on neurogenesis and neuronal precursor cell proliferation when overexpressed. IFN-γ is also associated with neuronal damage, although it is not as extensively studied compared to TNF-α, IL-1β and IL-6. These cytokines are normally involved in brain homeostasis and maintaining tissue repair following an injury, although it can have negative consequences (Fan & Pang, 2017). In addition, via a feedback loop, they can act on the reactive resident cells thus maintaining or exacerbating their reactive state; and by modifying elements of their signalling pathways, they can favour the M1 phenotypic polarization and the chronicity of the inflammatory process (Taetzsch et al., 2015).

Studies show that the dysregulation of pro-inflammatory mediators can influence both cancer and non-cancer outcomes. Excessive/persistent pro-inflammatory signaling due to injury or exposure to chronic exposures can create an environment conducive to cellular transformation, proliferation. In autoimmune diseases, aberrant immune responses driven by pro-inflammatory cytokines like IL-6 and TNF-α lead to chronic inflammation, tissue damage, and organ dysfunction. Neurodegenerative disorders, such as Alzheimer's disease, involve dysregulated pro-inflammatory mediators like IL-1β and TNF-α, contributing to neuronal degeneration. Basically, this event occurs equally in various tissues and does not require tissue-specific descriptions. Nevertheless, there are some specificities such as the release of glutamate by brain reactive glial cells (Brown and Bal-Price, 2003; Vesce et al., 2007). The differences may rather reside in the type of insult favouring the increased expression and/or release of a specific class of inflammatory mediators, as well the time after the insult reflecting different stages of the inflammatory process. For these reasons, the analyses of the changes of a battery of inflammatory mediators rather than of a single one is a more adequate measurement of this KE.

## How it is Measured or Detected

Listed below are common methods for detecting the KE, however there may be other comparable methods that are not listed.

<table><thead><tr><td>Assay</td><td>Reference</td><td>Description</td><td>OECD Approved Assay</td></tr></thead><tbody><tr><td>RT-qPCR<br/>Q-PCR</td><td>(Veremeyko et al., 2012; Alwine et al., 1977; Forlenza et al., 2012)</td><td>Measures mRNA expression of cytokines, chemokines and inflammatory markers</td><td>No</td></tr></tbody></table>
<table><tr><td>Immunoblotting (western blotting)</td><td>(Lee et al., 2008)</td><td>Uses antibodies specific to proteins of interest, can used to detect presence of pro-inflammatory mediators in samples of cell or tissue lysate</td><td>No</td></tr><tr><td>Whole blood stimulation assay</td><td>(Thurm & Halsey, 2005)</td><td>Detects inflammatory cytokines in blood</td><td>No</td></tr><tr><td>Imaging tests</td><td>(Rollins & Miskolci, 2014)</td><td>A qualitative technique using a cytokine specific antibodies and fluorophores can be used to visualize expression patterns, subcellular location of the target and protein-protein interactions. Common examples include double immunofluorescence confocal microscopy or other molecular imaging modalities.</td><td>No</td></tr><tr><td>Flow-cytometry</td><td>(Karanikas et al., 2000)</td><td>Detects the intracellular cytokines with stimulation.</td><td>No</td></tr><tr><td>Immunoassays (ex. enzyme-linked immunosorbent assay (ELISA), enzyme-linked immunospot (ELISpot), radioimmunoassay)</td><td>(Amsen et al., 2009; Engvall & Perlmann, 1972; Ji & Forshuber, 2016; Goldsmith, 1975)</td><td>Plate based assay technique using antibodies to detect presence of a protein in a liquid sample. Can be used to identify presence of an inflammatory cytokine of interest especially when in low concentrations.</td><td>No</td></tr><tr><td>Inflammatory cytokine arrays</td><td>(Amsen et al., 2009)</td><td>Similar to the ELISA, except using a membrane-based rather than plate-based approach. Can be used to measure multiple cytokine targets concurrently.</td><td>No</td></tr><tr><td>Immunohistochemistry (IHC)</td><td>(Amsen et al., 2009; Coons et al., 1942)</td><td>Immobilized tissue or cell cultures are stained using antibodies for specificity of ligands of interest. Versions of the assays can be used to visualize localization of inflammatory cytokines.</td><td>No</td></tr></table>
References

Abdel-Magied, N., S. M., Shedid and Ahmed, A. G. (2019), "Mitigating effect of biotin against irradiation-induced cerebral cortical and hippocampal damage in the rat brain tissue", Environmental Science and Pollution Research, Vol. 26/13, Springer, London, https://doi.org/10.1007/S11356-019-04806-X.

Alwine, J. C., D. J. Kemp and G. R. Stark (1977), "Method for detection of specific RNAs in agarose gels by transfer to diazobenzyloxymethyl-paper and hybridization with DNA probes", Proceedings of the National Academy of Sciences of the United States of America, Vol. 74/12, United States National Academy of Sciences, Washington, D.C., https://doi.org/10.1073/pnas.74.12.5350

Amsen, D., de Visser, K. E., and Town, T. (2009), "Approaches to determine expression of inflammatory cytokines", in Inflammation and Cancer, Humana Press, Totowa, https://doi.org/10.1007/978-1-59745-447-6_5

Brown, G. C., and A. Bal-Price (2003), "Inflammatory neurodegeneration mediated by nitric oxide, glutamate, and mitochondria", Molecular Neurobiology, Vol. 27/3, Springer, London, https://doi.org/10.1385/MN:27:3:325

Cekanaviciute, E., S. Rosi and S. Costes. (2018), "Central Nervous System Responses to Simulated Galactic Cosmic Rays", International Journal of Molecular Sciences, Vol. 19/11, Multidisciplinary Digital Publishing Institute (MDPI) AG, Basel, https://doi.org/10.3390/ijms19113669.

Cho, H. J. et al. (2017), "Role of NADPH Oxidase in Radiation-induced Pro-oxidative and Pro-inflammatory Pathways in Mouse Brain", International Journal of Radiation Biology, Vol. 93/11, Informa, London, https://doi.org/10.1080/09553002.2017.1377360.

Coons, A. H. et al. (1942), "The Demonstration of Pneumococcal Antigen in Tissues by the Use of Fluorescent Antibody", The Journal of Immunology, Vol. 45/3, American Association of Immunologists, Minneapolis, pp. 159-169

Engvall, E., and P. Perlmann (1972), "Enzyme-Linked Immunosorbent Assay, Elisa", The Journal of Immunology, Vol. 109/1, American Association of Immunologists, Minneapolis, pp. 129-135

Fan, L. W. and Y. Pang. (2017), "Dysregulation of neurogenesis by neuroinflammation: Key differences in neurodevelopmental and neurological disorders", Neural Regeneration Research, Vol. 12/3, Wolters Kluwer, Alphen aan den Rijn, https://doi.org/10.4103/1673-5374.202926.

Forlenza, M. et al. (2012), "The use of real-time quantitative PCR for the analysis of cytokine mRNA levels" in Cytokine Protocols, Springer, New York, https://doi.org/10.1007/978-1-61779-439-1_2

Gaber, M. W. et al. (2003), "Differences in ICAM-1 and TNF-alpha expression between large single fraction and fractionated irradiation in mouse brain", International Journal of Radiation Biology, Vol. 79/5, Informa, London, https://doi.org/10.1080/0955300031000114738.

Goldsmith, S. J. (1975), "Radioimmunoassay: Review of basic principles", Seminars in Nuclear Medicine, Vol. 5/2, https://doi.org/10.1016/S0001-2998(75)80028-6.

Hladik, D. and S. Tapio. (2016), "Effects of ionizing radiation on the mammalian brain", Mutation Research/Reviews in Mutation Research, Vol. 770, Elsevier B. b., Amsterdam, https://doi.org/10.1016/j.mrrev.2016.08.003.
Ismail, A. F. M., A.A.M. Salem and M.M.T. Eassawy (2016), "Modulation of gamma-irradiation and carbon tetrachloride induced oxidative stress in the brain of female rats by flaxseed oil", Journal of Photochemistry and Photobiology B: Biology, Vol. 161, Elsevier, Amsterdam, https://doi.org/10.1016/J.JPHOTOBIOL.2016.04.031.

Ji, N. and T. G. Forsthuber. (2014), "ELISPOT Techniques" (pp. 63–71), https://doi.org/10.1007/7651_2014_111.

Kalm, M., K. Roughton and K. Blomgren. (2013), "Lipopolysaccharide sensitized male and female juvenile brains to ionizing radiation", Cell Death & Disease, Vol. 4/12, Nature Publishing Group, Berlin, https://doi.org/10.1038/cddis.2013.482.

Karanikas, V. et al. (2000), "Flow cytometric measurement of intracellular cytokines detects immune responses in MUC1 immunotherapy", Clinical Cancer Research, Vol. 6/3, American Association for Cancer Research, Philadelphia, pp. 829–837

Kim, S. H. et al. (2002), "Expression of TNF-alpha and TGF-beta 1 in the rat brain after a single high-dose irradiation", Journal of Korean Medical Science, Vol. 17/2, Korean Medical Association, Seoul, https://doi.org/10.3346/JKMS.2002.17.2.242.

Lee, J. W. et al. (2008), "Neuro-inflammation induced by lipopolysaccharide causes cognitive impairment through enhancement of beta-amyloid generation", Journal of Neuroinflammation, Vol. 5/1, BioMed Central, London, https://doi.org/10.1186/1742-2094-5-37

Lee, W. H. et al. (2010), "Irradiation induces regionally specific alterations in pro-inflammatory environments in rat brain", International Journal of Radiation Biology, Vol. 86/2, Informa, London, https://doi.org/10.3109/09553000903419346.

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Parihar, V. K. et al. (2020), "Sex-Specific Cognitive Deficits Following Space Radiation Exposure", Frontiers in Behavioral Neuroscience, Vol. 14, https://doi.org/10.3389/fnbeh.2020.535885.

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Weavers, H. and P. Martin (2020), “The cell biology of inflammation: From common traits to remarkable immunological adaptations”, Journal of Cell Biology, Vol. 219, Rockefeller University Press, New York, https://doi.org/10.1083/jcb.202004003
Short Name: Abnormal Neural Remodeling

Key Event Component

<table><thead><tr><td>Process</td><td>Object</td><td>Action</td></tr></thead><tbody><tr><td>neurogenesis</td><td></td><td>decreased</td></tr><tr><td>demyelination</td><td></td><td>increased</td></tr><tr><td>neuron death</td><td></td><td>increased</td></tr></tbody></table>

AOPs Including This Key Event

<table><thead><tr><td>AOP Name</td><td>Role of event in AOP</td></tr></thead><tbody><tr><td>AOP: 483:Deposition of Energy Leading to Learning and Memory<br>Impairment</td><td>Key Event</td></tr></tbody></table>

Biological context

<table><thead><tr><td>Level of Biological Organization</td></tr></thead><tbody><tr><td>Tissue</td></tr></tbody></table>

Domain of Applicability

Taxonomic Applicability

The ability to process complex spatiotemporal information through neuronal networking is a fundamental process underlying the behavior of all higher organisms. The most studied are the neuronal networks of vertebrates such as rodents (Cekanaviciute et al., 2018) and primates (Wang and Arnsten, 2015). https://pubmed.ncbi.nlm.nih.gov/26876924/Invertebrates hold neural circuitries in various degrees of complexity and there are studies describing how neurons are organized into functional networks to generate behaviour (Wong and Wong, 2004; Marder, 1994).

<table><thead><tr><td>Term</td><td>Scientific Term</td><td>Evidence</td><td>Link</td></tr></thead><tbody><tr><td>dog</td><td>Canis lupus familiaris</td><td>Low</td><td>NCBI</td></tr><tr><td>rat</td><td>Rattus norvegicus</td><td>Moderate</td><td>NCBI</td></tr><tr><td>mouse</td><td>Mus musculus</td><td>Moderate</td><td>NCBI</td></tr></tbody></table>

Life Stage Applicability

This key event is applicable to all life stages; most evidence is derived from studies in adults (Cekanaviciute et al., 2018; Hladik & Tapio, 2016).

<table><thead><tr><td>Life stage</td><td>Evidence</td></tr></thead><tbody><tr><td>Juvenile</td><td>Low</td></tr><tr><td>Adult</td><td>Moderate</td></tr></tbody></table>

Sex Applicability

This key event is not sex specific (Hladik & Tapio, 2016).

<table><thead><tr><td>Term</td><td>Evidence</td></tr></thead><tbody><tr><td>Male</td><td>Moderate</td></tr><tr><td>Female</td><td>Low</td></tr><tr><td>Unspecific</td><td>Low</td></tr></tbody></table>

Evidence for Perturbation by Prototypic Stressor

Current literature provides ample evidence of neural remodeling being induced by stressors including ionizing radiation (Allen et al., 2015; Cekanaviciute et al., 2018; J. R. Fike et al., 1984; John R. Fike et al., 1988; Hladik & Tapio, 2016; Kiffer et al., 2020; Mizumatsu et al., 2003; Okamoto et al., 2009; Vipan K. Parihar et al., 2016; Vipan K. Parihar; Rola et al., 2005; Tiller-Borcich et al., 1987).
## Key Event Description

(Adapted from KE: 618)

Abnormal neural remodeling is a normal process that allows for the encoding of new information and experiences, and it is essential in the functional and structural adaptation of the central nervous system (CNS) (Wang et al., 2010). Remodeling of neural cells can be adaptive but stressors and stimuli that lead to persistent inflammation can degenerate brain cell types like neurons, dendrites, glial cells, astrocytes and oligodendrocytes (Hladik & Tapio, 2016; Makale et al., 2017). Abnormal neural remodeling can encompass a broad range of processes (Marc et al., 2003). Key processes include changes in neurogenesis, synaptic plasticity, and myelination, which are all measurable. Neurogenesis involves the generation of new neurons from neural stem cells, primarily occurring in neurogenic niches such as the hippocampus (Hladik & Tapio, 2016). Synaptic plasticity refers to the ability of synapses to undergo structural and functional modifications in response to activity, facilitating learning and memory formation. This includes processes like long-term potentiation (LTP) and long-term depression (LTD), which enhances or weakens synaptic strength, respectively. Myelination, primarily mediated by oligodendrocytes in the CNS, involves the formation of myelin sheaths around axons, facilitating efficient signal transmission (Stadelmann et al., 2019).

Exposure to environmental toxins or substances during critical developmental periods can negatively influence the many processes involved in abnormal neural remodeling. Prenatal exposure to neurotoxic substances, for instance, may disrupt fetal neurogenesis. Prolonged stress, hormonal imbalances, and the natural aging process can also contribute to abnormal neural remodeling. Studies show that the dendrites of neurons are an important structure for maintaining synaptic plasticity. Changes in dendritic spine density and structure, including decreases in dendritic branch points, length, and area, are correlated with changes in excitatory synaptic transmission strength which can impair brain function (Jandial et al., 2018; Auffret et al., 2009). Dendritic protein synthesis is also required for many types of long-term synaptic plasticity (Sutton & Schuman 2006). Changes to the levels of protein synthesis can greatly affect neuronal communication. When dendritic complexity decreases, there can be a decline in neurogenesis and an increase in neurodegeneration. Neurogenesis is the creation of mature cells from neural stem cells (NSCs) which are involved in learning and memory, and decreased neurogenesis can impair the brain's function (Hladik & Tapio, 2016). Together these events provoke changes in synaptic plasticity and propagations of action potentials, ultimately leading to the disruption of neuronal signaling (Cekanaviciute et al., 2018). Other types of changes related to abnormal neural remodeling include demyelination of neurons and white matter necrosis which have been associated with altered brain function such as decreased long-term memory formation (Makale et al., 2017; Tomé et al., 2015).

## How it is Measured or Detected

<table><thead><tr><td>Method of Measurement</td><td>References</td><td>Description</td><td>OECD-Approved Assay</td></tr></thead><tbody><tr><td>MRI Scan</td><td>Jiang et al., 2014</td><td>Magnetic resonance imaging (MRI) is an imaging technique used to visualize organs and tissues in the body. MRI can be used to view demyelination.</td><td>No</td></tr><tr><td>Fluoro-Jade stain</td><td>Schmued and Hopkins, 2000</td><td>Detects and labels degenerating neurons.</td><td>No</td></tr><tr><td>3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) Assay – colorimetric assay used to assess cell metabolic activity based on the reduction of (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide.</td><td>Riss et al., 2004</td><td>Cell viability and proliferation assays can be used to measure increased levels of neurodegeneration or decreased levels of neurogenesis.</td><td>Yes</td></tr><tr><td>Bromodeoxyuridine (BrdU) labeling</td><td>Vallieres et al., 2002</td><td>Staining method used to identify proliferating cells and measures neurogenesis.</td><td>No</td></tr><tr><td>SYNPLA</td><td>Dore et al., 2020</td><td>Synaptic proximity ligation assay (SYNPLA) is a technique that detects learning-induced synaptic plasticity.</td><td>No</td></tr></tbody></table>
<table><tr><td>ELISA</td><td>Falsig et al., 2003; Lund et al., 2006; Monnet-Tschudi et al., 2011</td><td>The enzyme-linked immunosorbent assay (ELISA) is a technique that detects and quantifies levels of macromolecules such as peptides, proteins, antibodies, and hormones. It can be used to detect specific molecules in neurons that represent loss in integrity such as PSD-95, synapsin 1 or drebrin.</td><td>No</td></tr><tr><td>Immunoassay/microscopy</td><td>Falsig et al., 2003; Lund et al., 2006; Monnet-Tschudi et al., 2011</td><td>Various methods that use the specificity of antigen-antibody binding for detection and quantification of target molecules such as PSD-95, synpasin 1, Ki-67 and drebrin.</td><td>No</td></tr><tr><td>Western Blot</td><td>Yang and Mahmood, 2012</td><td>Protein identification from a complex mixture after size separation, transfer to solid support and marking target protein. Specific markers include PSD-95, synpasin 1, Ki-67 and drebrin.</td><td>No</td></tr><tr><td>Golgi-Cox Method</td><td>Zaqout and Kaindl, 2016</td><td>Visualizes neuronal morphology in vivo.</td><td>No</td></tr><tr><td>Whole-cell electrophysiology</td><td>Hill and Stephens, 2021</td><td>Measures intracellular electrical properties by visualizing ionic currents.</td><td>No</td></tr><tr><td>Terminal deoxynucleotidyl transferase-mediated dUTP nick end-labeling (TUNEL) assay</td><td>Kressel and Groscurth, 1994</td><td>Apoptosis is detected with the TUNEL method to assay the endonuclease cleavage products by enzymatically end-labeling the DNA strand breaks.</td><td>Yes</td></tr></table>
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Kressel, M. and P. Groscurth (1994), “Distinction of apoptotic and necrotic cell death by in situ labelling of fragmented DNA”, Cell and tissue research, Vol. 278/3, Nature, https://doi.org/10.1007/BF00331373.

Kukurba, K. R. and S. B. Montgomery. (2015), “RNA Sequencing and Analysis”, Cold Spring Harbor Protocols, Vol. 2015/11, https://doi.org/10.1101/pdb.top084970.

Jandial, R. et al. (2018), “Space-brain: The negative effects of space exposure on the central nervous system”, Surgical Neurology International, Vol. 9/1, https://doi.org/10.4103/sni.sni_250_17.

Jiang, X. et al. (2014), “A GSK-3β Inhibitor Protects Against Radiation Necrosis in Mouse Brain”, International Journal of Radiation Oncology*Biology*Physics, Vol. 89/4, Elsevier, Amsterdam, https://doi.org/10.1016/j.ijrobp.2014.04.018.

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Lund, S. et al. (2006), “The dynamics of the LPS triggered inflammatory response of murine microglia under different culture and in vivo conditions”, Journal of Neuroimmunology, Vol. 180/1–2, Elsevier, Amsterdam, https://doi.org/10.1016/j.jneuroim.2006.07.007.

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Monnet-Tschudi, F. et al. (2011), “Methods to Assess Neuroinflammation”, Current Protocols in Toxicology, Vol. 50/1, John Wiley & Sons, Inc., Hoboken, https://doi.org/10.1002/0471140856.tx1219s50.

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Short Name: Increase, DNA strand breaks

Key Event Component

<table><thead><tr><td>Process</td><td>Object</td><td>Action</td></tr></thead><tbody><tr><td>DNA Strand Break</td><td>Deoxyribonucleic acid</td><td>increased</td></tr></tbody></table>

AOPs Including This Key Event

<table><thead><tr><td>AOP Name</td><td>Role of event in AOP</td></tr></thead><tbody><tr><td>AOP: 296 - Oxidative DNA damage leading to chromosomal aberrations and mutations</td><td>Key Event</td></tr><tr><td>AOP: 272 - Deposition of energy leading to lung cancer</td><td>Key Event</td></tr><tr><td>AOP: 322 - Alkylation of DNA leading to reduced sperm count</td><td>Key Event</td></tr><tr><td>AOP: 216 - Deposition of energy leading to population decline via DNA strand breaks and follicular atresia</td><td>Key Event</td></tr><tr><td>AOP: 238 - Deposition of energy leading to population decline via DNA strand breaks and oocyte apoptosis</td><td>Key Event</td></tr><tr><td>AOP: 478 - Deposition of energy leading to occurrence of cataracts</td><td>Key Event</td></tr><tr><td>AOP: 483 - Deposition of Energy Leading to Learning and Memory Impairment</td><td>Key Event</td></tr><tr><td>AOP: 470 - Deposition of energy leads to abnormal vascular remodeling</td><td>Key Event</td></tr></tbody></table>

Biological context

<table><tr><td>Level of Biological Organization</td></tr><tr><td>Molecular</td></tr></table>

Domain of Applicability

Taxonomic Applicability

DNA strand breaks are relevant to all species, including vertebrates such as humans, that contain DNA (Cannan & Pederson, 2016)

<table><thead><tr><td>Term</td><td>Scientific Term</td><td>Evidence</td><td>Link</td></tr></thead><tbody><tr><td>human and other cells in culture</td><td>human and other cells in culture</td><td></td><td>NCBI</td></tr></tbody></table>

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).

<table><thead><tr><td>Life stage</td><td>Evidence</td></tr></thead><tbody><tr><td>All life stages</td><td>High</td></tr></tbody></table>

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).

<table><thead><tr><td>Term</td><td>Evidence</td></tr></thead><tbody><tr><td>Unspecific</td><td>High</td></tr></tbody></table>

Evidence for Perturbation by Prototypic 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).
## Key Event Description

DNA strand breaks are a type of damage resulting from the hydrolysis of phosphodiester groups in the backbone of DNA molecules (Gates, 2009) and can occur on a single strand (single strand breaks; SSBs) or both strands (double strand breaks; DSBs). SSBs arise when the sugar phosphate backbones connecting adjacent nucleotides in DNA are simultaneously hydrolyzed such that the hydrogen bonds between complementary bases are not able to hold the two strands together. 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), as well as other normal cellular processes where DSBs act as genetic shufflers to generate genetic diversity for V(D)J recombination in lymphoid cells, and chromatin remodeling in both somatic cells and germ cells, and meiotic recombination in gametes.

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, particularly 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).

## How it is Measured or Detected

Please refer to the table below for details regarding these and other methodologies for detecting DNA DSBs.

<table><thead><tr><td>Method of Measurement</td><td>References</td><td>Description</td><td>OECD Approved Method?</td></tr></thead><tbody><tr><td>Comet Assay (Single Cell Gel Electrophoresis - Alkaline)</td><td>Collins, 2004; Olive and Banath, 2006; Platel et al., 2011; Nikolova et al., 2017</td><td>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>Yes</td></tr><tr><td>γ-H2AX Foci Quantification - Flow Cytometry</td><td>Rothkamm and Horn, 2009; Bryce et al., 2016</td><td>Measurement of γ-H2AX immunostaining in cells by flow cytometry, normalized to total levels of H2AX</td><td>No</td></tr><tr><td>γ-H2AX Foci Quantification - Western Blot</td><td>Burma et al., 2001; Revet et al., 2011</td><td>Measurement of γ-H2AX immunostaining in cells by Western blotting, normalized to total levels of H2AX</td><td>No</td></tr><tr><td>γ-H2AX Foci Quantification - Microscopy</td><td>Redon et al., 2010; Mah et al., 2010; Garcia-Canton et al., 2013</td><td>Quantification of γ-H2AX immunostaining by counting γ-H2AX foci visualized with a microscope</td><td>No</td></tr><tr><td>γ-H2AX Foci Quantification - ELISA</td><td>Ji et al., 2017</td><td>Measurement of γ-H2AX in cells by ELISA, normalized to total levels of H2AX</td><td>No</td></tr><tr><td>Pulsed Field Gel Electrophoresis (PFGE)</td><td>Ager et al., 1990; Gardiner et al., 1985; Herschleb et al., 2007; Kawashima et al., 2017</td><td>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>No</td></tr></tbody></table>
<table><tr><td>The TUNEL (Terminal Deoxynucleotidyl Transferase dUTP Nick End Labeling) Assay</td><td>Loo, 2011</td><td>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</td><td>No</td></tr><tr><td>In Vitro DNA Cleavage Assays using Topoisomerase</td><td>Nitiss, 2012</td><td>Cleavage of DNA can be achieved using purified topoisomerase; DNA strand breaks can then be separated and quantified using gel electrophoresis</td><td>No</td></tr><tr><td>PCR assay</td><td>Figueroa-González & Pérez-Plasencia, 2017</td><td>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>No</td></tr><tr><td>Sucrose density gradient centrifuge</td><td>Raschke et al. 2009</td><td>Division of DNA pieces by density, increased fractionation leads to lower density pieces, with the use of a sucrose cushion</td><td>No</td></tr><tr><td>Alkaline Elution Assay</td><td>Kohn, 1991</td><td>Cells lysed with detergent-solution, filtered through membrane to remove all but intact DNA</td><td>No</td></tr><tr><td>Unwinding Assay</td><td>Nacci et al. 1992</td><td>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>Yes</td></tr><tr><td>STRIDE assay</td><td>Zilio and Ulrich, 2021</td><td>STRIDE (SensiTive Recognition of Individual DNA Ends) combines in situ nick translation with the proximity ligation assay (PLA) to detect single-strand breaks (sSTRIDE) or double-strand breaks (dSTRIDE). In this process, lesions labeled through nick translation with biotinylated nucleotides are identified by a PLA signal, which arises from the interaction of two anti-biotin antibodies from different species.</td><td>No</td></tr><tr><td>sBLISS</td><td>Bouwmann et al. 2020</td><td>sBLISS (in-suspension breaks labeling in situ and sequencing) labels double-strand breaks (DSBs) in cells immobilized on glass coverslips, using double-stranded oligonucleotide adaptors that facilitate selective linear amplification through T7-mediated in vitro transcription (IVT), followed by next-generation sequencing (NGS) library preparation</td><td>No</td></tr></table>
References

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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 al. (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.

Bouwman, B. et al. (2020), "Genome-wide detection of DNA double-strand breaks by in-suspension BLISS", Nature protocols, 15/12, Springer Nature, London, https://doi.org/10.1038/s41596-020-0397-2

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.

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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.133(6), Spandidos Publications, Athens, https://doi.org/10.3892/ol.2017.6002.

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## Event: 341: Impairment, Learning and memory

**Short Name:** Impairment, Learning and memory

**Key Event Component**

<table><thead><tr><td>Process</td><td>Object</td><td>Action</td></tr></thead><tbody><tr><td>learning</td><td></td><td>decreased</td></tr><tr><td>memory</td><td></td><td>decreased</td></tr></tbody></table>

## AOPs Including This Key Event

<table><thead><tr><td>AOP Name</td><td>Role of event in AOP</td></tr></thead><tbody><tr><td>AOP: 13 - Chronic binding of antagonist to N-methyl-D-aspartate receptors (NMDARs) during brain development induces impairment of learning and memory abilities</td><td>Adverse Outcome</td></tr><tr><td>AOP: 48 - Binding of agonists to ionotropic glutamate receptors in adult brain causes excitotoxicity that mediates neuronal cell death, contributing to learning and memory impairment.</td><td>Adverse Outcome</td></tr><tr><td>AOP: 54 - Inhibition of Na+/I- symporter (NIS) leads to learning and memory impairment</td><td>Adverse Outcome</td></tr><tr><td>AOP: 77 - Nicotinic acetylcholine receptor activation contributes to abnormal foraging and leads to colony death/failure 1</td><td>Key Event</td></tr><tr><td>AOP: 78 - Nicotinic acetylcholine receptor activation contributes to abnormal role change within the worker bee caste leading to colony death failure 1</td><td>Key Event</td></tr><tr><td>AOP: 87 - Nicotinic acetylcholine receptor activation contributes to abnormal foraging and leads to colony loss/failure</td><td>Key Event</td></tr><tr><td>AOP: 88 - Nicotinic acetylcholine receptor activation contributes to abnormal foraging and leads to colony loss/failure via abnormal role change within caste</td><td>Key Event</td></tr><tr><td>AOP: 89 - Nicotinic acetylcholine receptor activation followed by desensitization contributes to abnormal foraging and directly leads to colony loss/failure</td><td>Key Event</td></tr><tr><td>AOP: 90 - Nicotinic acetylcholine receptor activation contributes to abnormal roll change within the worker bee caste leading to colony loss/failure 2</td><td>Key Event</td></tr><tr><td>AOP: 12 - Chronic binding of antagonist to N-methyl-D-aspartate receptors (NMDARs) during brain development leads to neurodegeneration with impairment in learning and memory in aging</td><td>Adverse Outcome</td></tr><tr><td>AOP: 99 - Histamine (H2) receptor antagonism leading to reduced survival</td><td>Key Event</td></tr><tr><td>AOP: 17 - Binding of electrophilic chemicals to SH(thiol)-group of proteins and /or to seleno-proteins involved in protection against oxidative stress during brain development leads to impairment of learning and memory</td><td>Adverse Outcome</td></tr><tr><td>AOP: 475 - Binding of chemicals to ionotropic glutamate receptors leads to impairment of learning and memory via loss of drebrin from dendritic spines of neurons</td><td>Adverse Outcome</td></tr><tr><td>AOP: 483 - Deposition of Energy Leading to Learning and Memory Impairment</td><td>Adverse Outcome</td></tr><tr><td>AOP: 490 - Co-activation of IP3R and RyR leads to reduced IQ through non-cholinergic mechanisms</td><td>Adverse Outcome</td></tr><tr><td>AOP: 499 - Activation of MEK-ERK1/2 leads to deficits in learning and cognition via disrupted neurotransmitter release</td><td>Adverse Outcome</td></tr><tr><td>AOP: 500 - Activation of MEK-ERK1/2 leads to deficits in learning and cognition via ROS and apoptosis</td><td>Adverse Outcome</td></tr><tr><td>AOP: 520 - Retinoic acid receptor agonism during neurodevelopment leading to impaired learning and memory</td><td>Adverse Outcome</td></tr><tr><td>AOP: 525 - Reduced oligodendrocyte differentiation during neurodevelopment leading to impaired learning and memory</td><td>Adverse Outcome</td></tr><tr><td>AOP: 533 - Retinoic acid receptor antagonism during neurodevelopment leading to impaired learning and memory</td><td>Adverse Outcome</td></tr><tr><td>AOP: 535 - Binding and activation of GPER leading to learning and memory impairments</td><td>Adverse Outcome</td></tr></tbody></table>

## Biological context

<table><tr><td>Level of Biological Organization</td></tr><tr><td>Individual</td></tr></table>

## Domain of Applicability

### Taxonomic Applicability
Basic forms of learning behavior such as habituation have been found in many taxa from worms to humans (Alexander, 1990). More complex cognitive processes such as executive function likely reside only in higher mammalian species such as non-human primates and humans. Recently, larval zebrafish has also been suggested as a model for the study of learning and memory (Roberts et al., 2013).

<table><thead><tr><td>Term</td><td>Scientific Term</td><td>Evidence</td><td>Link</td></tr></thead><tbody><tr><td>human</td><td>Homo sapiens</td><td>High</td><td>NCBI</td></tr><tr><td>rat</td><td>Rattus norvegicus</td><td>High</td><td>NCBI</td></tr><tr><td>fruit fly</td><td>Drosophila melanogaster</td><td>High</td><td>NCBI</td></tr><tr><td>zebrafish</td><td>Danio rerio</td><td>High</td><td>NCBI</td></tr><tr><td>gastropods</td><td>Physa heterostropha</td><td>High</td><td>NCBI</td></tr><tr><td>mouse</td><td>Mus musculus</td><td>High</td><td>NCBI</td></tr></tbody></table>

## Life Stage Applicability

This key event is applicable to various life stages such as during brain development and maturity (Hladik & Tapio, 2016).

<table><thead><tr><td>Life stage</td><td>Evidence</td></tr></thead><tbody><tr><td>During brain development</td><td>High</td></tr><tr><td>Adult, reproductively mature</td><td>High</td></tr></tbody></table>

## Sex Applicability

This key event is not sex specific (Cekanaviciute et al., 2018), although sex-dependent cognitive outcomes have been recently; Parihar et al., 2020).

<table><thead><tr><td>Term</td><td>Evidence</td></tr></thead><tbody><tr><td>Mixed</td><td>High</td></tr></tbody></table>

## Evidence for Perturbation by Prototypic Stressor

Current literature provides ample evidence of impaired learning and memory being induced by ionizing radiation (Cekanaviciute et al., 2018; Hladik & Tapio, 2016).

## Key Event Description

(Adapted from KE: 341)

Learning can be defined as the process by which new information is acquired to establish knowledge by systematic study or by trial and error (Ono, 2009). Two types of learning are considered in neurobehavioral studies: a) associative learning and b) non-associative learning. Associative learning is based on making associations between different events. In associative learning, a subject learns the relationship among two different stimuli or between the stimulus and the subject's behavior. On the other hand, non-associative learning can be defined as an alteration in the behavioral response that occurs over time in response to a single type of stimulus. Habituation and sensitization are some examples of non-associative learning.

The memory formation requires acquisition, retention and retrieval of information in the brain, which is characterized by the non-conscious recall of information (Ono, 2009). There are three main categories of memory, including sensory memory, short-term or working memory (up to a few hours) and long-term memory (up to several days or even much longer).

Learning and memory depend upon the coordinated action of different brain regions and neurotransmitter systems constituting functionally integrated neural networks (D'Hooze and DeDeyn, 2001). Among the many brain areas engaged in the acquisition of, or retrieval of, a learned event, the hippocampal-based memory systems have received the most study. For example, the hippocampus has been shown to be critical for spatial-temporal memory, visio-spatial memory, verbal and narrative memory, and episodic and autobiographical memory (Burgess et al., 2000; Vorhees and Williams, 2014). However, there is substantial evidence that fundamental learning and memory functions are not
mediated by the hippocampus alone but require a network that includes, in addition to the
hippocampus, anterior thalamic nuclei, mammillary bodies cortex, cerebellum and basal ganglia
(Aggleton and Brown, 1999; Doya, 2000; Mitchell et al., 2002, Toscano and Guilarte, 2005; Gilbert
et al., 2006, 2016). Thus, damage to variety of

brain structures can potentially lead to impairment of learning and memory. The main learning areas
and pathways are similar in rodents and primates, including man (Eichenbaum, 2000; Stanton and
Spear, 1990). While the prefrontal cortex and frontostriatal neural circuits have been identified as the
primary sites of higher-order cognition in vertebrates, invertebrates utilize paired mushroom bodies,
shown to contain ~300,000 neurons in honey bees (Menzel, 2012; Puig et al., 2014).

For the purposes of this KE (AO), impaired learning and memory is defined as an organism's inability to establish new associative or non-associative relationships, or sensory, short-term or long-term memories which can be measured using different behavioral tests described below.

How it is Measured or Detected

In laboratory animals: in rodents, a variety of tests of learning and memory have been used to probe the integrity of hippocampal function. These include tests of spatial learning like the radial arm maze (RAM), the Barnes maze, Hebb-Williams maze, passive avoidance and Spontaneous alternation and most commonly, the Morris water maze (MWM). Test of novelty such as novel object recognition, and fear based context learning are also sensitive to hippocampal disruption. Finally, trace fear conditioning which incorporates a temporal component upon traditional amygdala-based fear learning engages the hippocampus. A brief description of these tasks follows.

RAM, Barnes, MWM, Hebb-Williams maze are examples of spatial tasks, animals are required to learn the location of a food reward (RAM); an escape hole to enter a preferred dark tunnel from a brightly lit open field area (Barnes maze), or a hidden platform submerged below the surface of the water in a large tank of water (MWM) (Vorhees and Williams, 2014). The Hebb-Williams maze measures an animal's problem solving abilities by providing no spatial cues to find the target (Pritchett & Mulder, 2004).

Novel Object recognition. This is a simpler task that can be used to probe recognition memory. Two objects are presented to animal in an open field on trial 1, and these are explored. On trial 2, one object is replaced with a novel object and time spent interacting with the novel object is taken evidence of memory retention – I have seen one of these objects before, but not this one (Cohen and Stackman, 2015).

Contextual Fear conditioning is a hippocampal based learning task in which animals are placed in a novel environment and allowed to explore for several minutes before delivery of an aversive stimulus, typically a mild foot shock. Upon reintroduction to this same environment in the future (typically 24-48 hours after original training), animals will limit their exploration, the context of this chamber being associated with an aversive event. The degree of suppression of activity after training is taken as evidence of retention, i.e., memory (Curzon et al., 2009).

Trace fear conditioning. Standard fear conditioning paradigms require animals to make an association between a neutral conditioning stimulus (CS, a light or a tone) and an aversive stimulus (US, a footshock). The unconditioned response (CR) that is elicited upon delivery of the footshock US is freezing behavior. With repetition of CS/US delivery, the previously neutral stimulus comes to elicit the freezing response. This type of learning is dependent on the amygdala, a brain region associated with, but distinct from the hippocampus. Introducing a brief delay between presentation of the neutral CS and the aversive US, a trace period, requires the engagement of the amygdala and the hippocampus (Shors et al., 2001).

Operant Responding. Performance on operant responding reflects the cortex' ability to organize processes (Rabin et al., 2002).
In humans: A variety of standardized learning and memory tests have been developed for human neuropsychological testing, including children (Rohlman et al., 2008). These include episodic autobiographical memory, perceptual motor tests, short and long term memory tests, working memory tasks, word pair recognition memory; object location recognition memory. Some have been incorporated in general tests of intelligence (IQ) such as the Wechsler Adult Intelligence Scale (WAIS) and the Wechsler.

Modifications have been made and norms developed for incorporating of tests of learning and memory in children. Examples of some of these tests include:

Rey Osterieth Complex Figure test (RCFT) which probes a variety of functions including as visuospatial abilities, memory, attention, planning, and working memory (Shin et al., 2006).

Children's Auditory Verbal Learning Test (CAVLT) is a free recall of presented word lists that yields measures of Immediate Memory Span, Level of Learning, Immediate Recall, Delayed Recall, Recognition Accuracy, and Total Intrusions. (Lezak 1994; Talley, 1986).

Continuous Visual Memory Test (CVMT) measures visual learning and memory. It is a free recall of presented pictures/objects rather than words but that yields similar measures of Immediate Memory Span, Level of Learning, Immediate Recall, Delayed Recall, Recognition Accuracy, and Total Intrusions. (Lezak, 1984; 1994).

Story Recall from Wechsler Memory Scale (WMS) Logical Memory Test Battery, a standardized neuropsychological test designed to measure memory functions (Lezak, 1994; Talley, 1986).

Autobiographical memory (AM) is the recollection of specific personal events in a multifaceted higher order cognitive process. It includes episodic memory—remembering of past events specific in time and place, in contrast to semantic autobiographical memory is the recollection of personal facts, traits, and general knowledge. Episodic AM is associated with greater activation of the hippocampus and a later and more gradual developmental trajectory. Absence of episodic memory in early life (infantile amnesia) is thought to reflect immature hippocampal function (Herold et al., 2015; Fivush, 2011).

Staged Autobiographical Memory Task. In this version of the AM test, children participate in a staged event involving a tour of the hospital, perform a series of tasks (counting footprints in the hall, identifying objects in wall display, buy lunch, watched a video). It is designed to contain unique event happenings, place, time, visual/sensory/perceptual details. Four to five months later, interviews are conducted using Children's Autobiographical Interview and scored according to standardized scheme (Willoughby et al., 2014).

Attentional set-shifting (ATSET) task. Measures the ability to relearn cues over various schedules of reinforcement (Heisler et al., 2015).

In Honey Bees: For over 50 years an assay for evaluating olfactory conditioning of the proboscis extension reflex (PER) has been used as a reliable method for evaluating appetitive learning and memory in honey bees (Guirfa and Sandoz, 2012; LaLone et al., 2017). These experiments pair a conditioned stimulus (e.g., an odor) with an unconditioned stimulus (e.g., sucrose) provided immediately afterward, which elicits the proboscis extension (Menzel, 2012). After conditioning, the odor alone will lead to the conditioned PER. This methodology has aided in the elucidation of five types of olfactory memory phases in honey bee, which include early short-term memory, late short-term memory, mid-term memory, early long-term memory, and late long-term memory (Guirfa and Sandoz, 2012). These phases are dependent on the type of conditioned stimulus, the intensity of the unconditioned stimulus, the number of conditioning trials, and the time between trials. Where formation of short-term memory occurs minutes after conditioning and decays within minutes, memory consolidation or stabilization of a memory trace after initial acquisition leads to mid-term memory, which lasts 1 d and is characterized by activity of the cAMP-dependent PKA (Guirfa and Sandoz, 2012). Multiple conditioning trials increase the duration of the memory after learning and coincide with increased Ca2+-calmodulin-dependent PKC activity (Guirfa and Sandoz, 2012). Early long-term memory, where a conditioned response can be evoked days to weeks after conditioning
requires translation of existing mRNA, whereas late long-term memory requires de novo gene
transcription and can last for weeks (Guirfa and Sandoz, 2012)."

Regulatory Significance of the Adverse Outcome

A prime example of impairments in learning and memory as the adverse outcome for regulatory action
is developmental lead exposure and IQ function in children (Bellinger, 2012). Most methods are well
established in the published literature and many have been engaged to evaluate the effects of
developmental thyroid disruption. The US EPA and OECD Developmental Neurotoxicity (DNT)
Guidelines (OCSPP 870.6300 or OECD TG 426) as well as OECD TG 443 (OECD, 2018) both require
testing of learning and memory (USEPA, 1998; OECD, 2007) advising to use the following tests
passive avoidance, delayed-matching-to-position for the adult rat and for the infant rat, olfactory
conditioning, Morris water maze, Biel or Cincinnati maze, radial arm maze, T-maze, and acquisition
and retention of schedule-controlled behavior. These DNT Guidelines have been deemed valid to
identify developmental neurotoxicity and adverse neurodevelopmental outcomes (Makris et al., 2009).

Also, in the frame of the OECD GD 43 (2008) on reproductive toxicity, learning and memory testing
may have potential to be applied in the context of developmental neurotoxicity studies. However,
many of the learning and memory tasks used in guideline studies may not readily detect subtle
impairments in cognitive function associated with modest degrees of developmental thyroid disruption
(Gilbert et al., 2012).
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# Appendix 2 – List of Key Event Relationships in the AOP

## List of Adjacent Key Event Relationships

### Relationship: 2769: Energy Deposition leads to Oxidative Stress

#### AOPs Referencing Relationship

<table><thead><tr><td>AOP Name</td><td>Adjacency</td><td>Weight of Evidence</td><td>Quantitative Understanding</td></tr></thead><tbody><tr><td>AOP: 470 - Deposition of energy leads to abnormal vascular remodeling</td><td>adjacent</td><td>High</td><td>High</td></tr><tr><td>AOP: 483 - Deposition of Energy Leading to Learning and Memory Impairment</td><td>adjacent</td><td>High</td><td>Moderate</td></tr><tr><td>AOP: 482 - Deposition of energy leading to occurrence of bone loss</td><td>adjacent</td><td>High</td><td>Moderate</td></tr><tr><td>AOP: 478 - Deposition of energy leading to occurrence of cataracts</td><td>adjacent</td><td>High</td><td>High</td></tr></tbody></table>

#### Evidence Supporting Applicability of this Relationship

Most evidence is derived from in vitro studies, predominantly using rabbit models. Evidence in humans and mice is moderate, while there is considerable available data using rat models. The relationship is applicable in both sexes; however, males are used more often in animal studies. No studies demonstrate the relationship in preadolescent animals, while adolescent animals were used very often, and adults were used occasionally in in vivo studies.

#### Taxonomic Applicability

<table><thead><tr><td>Term</td><td>Scientific Term</td><td>Evidence</td><td>Link</td></tr></thead><tbody><tr><td>human</td><td>Homo sapiens</td><td>Moderate</td><td>NCBI</td></tr><tr><td>mouse</td><td>Mus musculus</td><td>Moderate</td><td>NCBI</td></tr><tr><td>rat</td><td>Rattus norvegicus</td><td>High</td><td>NCBI</td></tr><tr><td>rabbit</td><td>Oryctolagus cuniculus</td><td>Low</td><td>NCBI</td></tr></tbody></table>

#### Life Stage Applicability

<table><thead><tr><td>Term</td><td>Evidence</td></tr></thead><tbody><tr><td>Juvenile</td><td>High</td></tr><tr><td>Adult</td><td>Moderate</td></tr></tbody></table>

#### Sex Applicability

<table><thead><tr><td>Sex</td><td>Evidence</td></tr></thead><tbody><tr><td>Male</td><td>High</td></tr><tr><td>Female</td><td>Moderate</td></tr><tr><td>Unspecific</td><td>High</td></tr></tbody></table>

#### Key Event Relationship Description

Energy deposited onto biomolecules stochastically in the form of ionizing and non-ionizing radiation can cause direct and indirect molecular-level damage. As energy is deposited in an aqueous solution, water molecules can undergo radiolysis, breaking bonds to produce reactive oxygen species (ROS) (Ahmadi et al., 2021; Karimi et al., 2017) or directly increase function of enzymes involved in ROS generation (i.e. catalaze). Various species of ROS can be generated with differing degrees of biological effects. For example, singlet oxygen, superoxide, and hydroxyl radical are highly unstable, with short half-lives and react close to where they are produced, while species like H2O2 are much more stable and membrane permeable, meaning they can travel from the site of production, reacting elsewhere as a much weaker oxidant (Spector, 1990). In addition, enzymes involved in reactive oxygen and nitrogen species (RONS) production can be directly upregulated following the deposition of energy (de Jager,
Cockrell and Du Plessis, 2017). Although less common than ROS, reactive nitrogen species (RNS) can also be produced by energy deposition resulting in oxidative stress (Cadet et al., 2012; Tangvarasittichai & Tangvarasittichai, 2019), a state in which the amount of ROS and RNS, collectively known as RONS, overwhelms the cell's antioxidant defence system. This loss in redox homeostasis can lead to oxidative damage to macromolecules including proteins, lipids, and nucleic acids (Schoenfeld et al., 2012; Tangvarasittichai & Tangvarasittichai, 2019; Turner et al., 2002).

### Evidence Supporting this KER

The strategy for collating the evidence 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: High

### Biological Plausibility

A large body of literature supports the linkage between the deposition of energy and oxidative stress. Multiple reviews describe the relationship in the context of ROS production (Marshall, 1985; Balasubramanian, 2000; Jurja et al., 2014), antioxidant depletion (Cabrera et al., 2011; Fletcher, 2010; Ganea & Harding, 2006; Hamada et al., 2014; Spector, 1990; Schoenfeld et al., 2012; Wegener, 1994), and overall oxidative stress (Eaton, 1994, Tangvarasittichai & Tangvarasittichai, 2019). This includes investigations into the mechanism behind the relationship (Ahmadi et al., 2021; Balasubramanian, 2000; Cencer et al., 2018; Eaton, 1994; Fletcher, 2010; Jiang et al., 2006; Jurja et al., 2014; Padgaonkar et al., 2015; Quan et al., 2021; Rong et al., 2019; Slezak et al., 2015; Soloviev & Kizub, 2019; Tian et al., 2017; Tahimic & Globus, 2017; Varma et al., 2011; Venkatesulu et al., 2018; Wang et al., 2019a; Yao et al., 2008; Yao et al., 2009; Zigman et al., 2000).

Water radiolysis is a main source of free radicals. Energy ionizes water and free radicals are produced that combine to create more stable ROS, such as hydrogen peroxide, hydroxide, superoxide, and hydroxyl (Eaton, 1994; Rehman et al., 2016; Tahimic & Globus, 2017; Tian et al., 2017; Varma et al., 2011; Venkatesulu et al., 2018). ROS formation causes ensuing damage to the body, as ~80% of tissues are comprised of water (Wang et al., 2019a). Ionizing radiation (IR) is a source of energy deposition, it can also interact with molecules, such as nitric oxide (NO), to produce less common free radicals, including RNS (Slezak et al., 2015; Tahimic & Globus, 2017; Wang et al., 2019a). Free radicals can diffuse throughout the cell and damage vital cellular components, such as proteins, lipids, and DNA, as well as dysregulate cellular processes, such as cell signaling (Slezak et al., 2015; Tian et al., 2017).

ROS are also commonly produced by nicotinamide adenine dinucleotide phosphate (NADPH) oxidase (NOX). Deposition of energy can activate NOX and induce expression of its catalytic and cytosolic components, resulting in increased intracellular ROS (Soloviev & Kizub, 2019). Intracellular ROS production can also be initiated through the expression of protein kinase C, which in turn activates NOX through phosphorylation of its cytosolic components (Soloviev & Kizub, 2019). Alternatively, ROS are often formed at the electron transport chain (ETC) of the mitochondria, due to IR-induced electron leakage leading to ionization of the surrounding O2 to become superoxide (Soloviev & Kizub, 2019). Additionally, energy reaching a cell can be absorbed by an unstable molecule, often NADPH, known as a chromophore, which leads to the production of ROS (Balasubramanian, 2000; Cencer et al., 2018; Jiang et al., 2006; Jurja et al., 2014; Padgaonkar et al., 2015; Yao et al., 2009; Zigman et al., 2000).

Energy deposition can also weaken a cell's antioxidant defence system through the depletion of certain antioxidant enzymes, such as superoxide dismutase (SOD) and catalase (CAT). Antioxidants are consumed during the process of neutralizing ROS, so as energy deposition stimulates the formation of ROS it begins to outpace the rate at which antioxidants are replenished; this results in an increased risk of oxidative stress when their concentrations are low (Belkacémi et al., 2001; Giblin et al., 2002; Ji et al., 2014; Kang et al., 2020; Karimi et al., 2017; Padgaonkar et al., 2015; Rogers et al., 2004; Slezak et al., 2015; Tahimic & Globus, 2017; Wang et al., 2019a; Wegener, 1994; Weinreb & Dovrat,
1996; Zhang et al., 2012; Zigman et al., 1995; Zigman et al., 2000). When the amount of ROS overwhelms the antioxidant defence system, the cell will enter oxidative stress leading to macromolecular and cellular damage (Tangvarasittichai & Tangvarasittichai, 2019).

## Empirical Evidence

The relationship between energy deposition and oxidative stress is strongly supported by primary research on the effects of IR on ROS and antioxidant levels (Bai et al., 2020; Cervelli et al., 2017; Hatoum et al., 2006; Huang et al., 2018; Huang et al., 2019; Karam & Radwan, 2019; Kook et al., 2015; Liu et al., 2018; Liu et al., 2019; Mansour, 2013; Philipp et al., 2020; Ramadan et al., 2020; Sharma et al., 2018; Shen et al., 2018; Soltani et al., 2016; Soucy et al., 2010; Soucy et al., 2011; Ungvari et al., 2013; Wang et al., 2016; Wang et al., 2019b; Zhang et al., 2018; Zhang et al., 2020). Of note is that the relationship is demonstrated across studies conducted using various cell types, models and using broad dose ranges as summarized below. Much evidence is available and described to help discern the quantitative understanding of the relationship, since it is well established.

## Dose Concordance

It is well-accepted that any dose of radiation will deposit energy onto matter. Doses as low as 1 cGy support this relationship (Tseung et al., 2014). Following the deposition of energy, markers of oxidative stress are observed in the form of RONS, a change in levels of antioxidants, and oxidative damage to macromolecules. These effects have been shown across various organs/tissues and cell types as described below.

### RONS

#### Cardiovascular tissue:

There is a considerable amount of evidence to support this relationship in cell types and tissues of relevance to the cardiovascular system. Recent studies have shown a linear increase in ROS in human umbilical vein endothelial cells (HUVECs) following 0-5 Gy gamma irradiation (Wang et al., 2019b). HUVECs irradiated with 0.25 Gy X-rays (Cervelli et al., 2017) and 9 Gy 250kV photons (Sharma et al., 2018) show increased ROS. Gamma ray irradiated rats at 5 Gy display increased ROS levels in the aorta (Soucy et al., 2010). A study using cerebromicrovascular endothelial cell (CMVECs) showed a dose-dependent increase in ROS from 0-8 Gy gamma irradiation (Ungvari et al., 2013). Additionally, telomerase-immortalized coronary artery endothelial (TICAE) and telomerase-immortalized microvascular endothelial (TIME) cells irradiated with 0.1 and 5 Gy of X-rays displayed increased ROS production (Ramadan et al., 2020). Gut arterioles of rats showed increased ROS following multiple fractions of 2.5 Gy X-ray rat irradiation (Hatoum et al., 2006). Additionally, rats irradiated with 1 Gy of 56Fe expressed increased ROS levels in the aorta (Soucy et al., 2011).

#### Brain tissue:

Markers of oxidative stress have also been consistently observed in brain tissue. Human neural stem cells subjected to 1, 2 or 5 Gy gamma rays showed a dose-dependent increase in RONS production (Acharya et al., 2010). A dose-dependent increase in ROS was observed in rat brains following 1-10 Gy gamma rays (Collins-Underwood et al., 2008). Neural precursor cells exposed to 0-10 Gy of X-irradiation showed increased ROS levels (Giedzinski et al., 2005; Limoli et al., 2004). Mice brain tissue displayed increased ROS following proton irradiation (Baluchamy et al., 2012; Giedzinski et al., 2005). Neural processor cells expressed linearly increased ROS levels following doses of 56Fe (Limoli et al., 2007). A dose-dependent increase in RONS was also observed after exposure to 1-15 cGy 56Fe irradiation in mice neural stem/precursor cell (Tseng et al., 2014). Human neural stem cells exposed to 5-100 cGy of various ions demonstrated a dose-dependent increase in RONs (Baulch et al., 2015).

#### Eye tissue:

The eye is also sensitive to the accumulation of free radicals, in a state of antioxidant decline. It has been shown in human lens epithelial cells (HLECs) and HLE-B3 following gamma irradiation of 0.25
and 0.5 Gy that ROS levels are markedly increased (Ahmadi et al., 2021). Exposure to non-ionizing radiation, such as ultraviolet (UV)-B, has also led to increased ROS in HLECs and mouse lenses (Ji et al., 2015; Kubo et al., 2010; Rong et al., 2019; Yang et al., 2020).

**Bone tissue:**

Rat bone marrow-derived mesenchymal stem cell (bmMSCs) irradiated with 2, 5 and 10 Gy gamma rays and murine MC3T3-E1 osteoblast cells irradiated with 2, 4, and 8 Gy of X-rays have shown a dose-dependent increase in ROS levels (Bai et al., 2020; Kook et al., 2015). Murine RAW264.7 cells and rat bmMSC irradiated with 2 Gy of gamma rays displayed increased ROS levels (Huang et al., 2019; Huang et al., 2018; hang et al., 2020). Human bone marrow-derived mesenchymal stem cell (hBMMSCs) irradiated with 2 or 8 Gy X-rays showed increased ROS (Liu et al., 2018; Zhang et al., 2018). Similarly, murine MC3T3-E1 osteoblast-like cells irradiated with 6 Gy of X-rays also displayed increased ROS (Wang et al., 2016). Finally, whole-body irradiation of mice with 2 Gy of 31.6 keV although LET 12C heavy ions showed increased ROS (Liu et al., 2019).

**Antioxidants**

**Blood:**

Workers exposed to X-rays at less than 1 mSv/year for an average of 15 years showed around 20% decreased antioxidant activity compared to unexposed controls (Klucinski et al., 2008). Similarly, adults exposed to high background irradiation of 260 mSv/year showed about 50% lower antioxidant activity power compared to controls (Attar, Kondolousy and Khansari, 2007).

**Cardiovascular tissue:**

Heart tissue of rats following gamma irradiation of rats at 5 and 6 Gy resulted in a decrease in antioxidant levels (Karam & Radwan, 2019; Mansour, 2013). Similarly, HUVECs (Soltani, 2016) and TICAE cells (Philipp et al., 2020) irradiated at 2 Gy and 0.25-10 Gy gamma rays, respectively, displayed decreased antioxidant levels. Mice exposed to 18 Gy of X-ray irradiation showed decreased antioxidants in the aorta (Shen et al., 2018).

**Brain tissue:**

Mice brain tissue following 2, 10 and 50 cGy whole-body gamma irradiation revealed a dose-dependent change in SOD2 activity (Veeraraghan et al., 2011). Mice brain tissue showed decreased glutathione (GSH) and SOD levels following proton irradiation (Baluchamy et al., 2012).

**Eye tissue:**

Rats exposed to 15 Gy gamma rays demonstrated decreased antioxidants in the lens tissue (Karimi et al., 2017). Neutron irradiation of rats at 3.6 Sv resulted in a decrease in antioxidants in lens (Chen et al., 2021). A few studies found a dose concordance between UV irradiation and decreased antioxidant levels (Hua et al., 2019; Ji et al., 2015; Zigman et al., 2000; Zigman et al., 1995). HLECs following UVB exposure from 300 J/m2 to 14,400 J/m2 in HLECs showed linear decreases in antioxidant activity (Ji et al., 2015). Similarly, HLEC exposed to 4050, 8100 and 12,150 J/m2 found decreased antioxidant levels (Hua et al., 2019). Following UV irradiation of rabbit and squirrel lens epithelial cells (LECs) showed a linear decrease of antioxidant level, CAT (Zigman et al., 2000; Zigman et al., 1995). Mice exposed to UV irradiation found decreased antioxidant levels in lens (Zhang et al., 2012). Similarly, SOD levels decreased following 0.09 mW/cm² UVB exposure of HLECs (Kang et al., 2020).

**Bone tissue:**

Rat bmMSCs irradiated with 2, 5 and 10 Gy gamma rays and Murine MC3T3-E1 osteoblast cells irradiated with 2, 4, and 8 Gy of X-rays showed a dose-dependent decrease in antioxidant levels (Bai et al., 2020; Kook et al., 2015). hBMMSCs irradiated with 8 Gy X-rays also showed a decrease in antioxidant, SOD, levels (Liu et al., 2018).
## Oxidative Damage

Cardiovascular tissue:

HUVECs and rat hearts irradiated by gamma rays at 2 and 6 Gy, respectively, resulted in increased levels of oxidative stress markers, such as malondialdehyde (MDA), and thiobarbituric reactive substances (TBARS) (Mansour, 2013; Soltani, 2016).

Brain tissue:

Mice brain tissue were shown to have increased lipid peroxidation (LPO) as determined by MDA measurements, following proton irradiation at 1 and 2 Gy (Baluchamy et al., 2012). Neural precursor cells from rat hippocampus exposed to 0, 1, 5 and 10 Gy of X- irradiation resulted in increased lipid peroxidation (Limoli et al., 2004).

Eye tissue:

Rats exposed to 15 Gy gamma rays demonstrated increased MDA in lens tissue (Karimi et al., 2017). Neutron irradiation of rats at 3.6 Sv resulted in an initial decrease, followed by an increase in MDA in lens (Chen et al., 2021). Following UV irradiation at 300, 4050, 8100 and 12,150 J/m2, there was an increase in LPO in human lens (Chitchumroonchokchai et al., 2004; Hua et al., 2019). Similarly, LPO increased following 0.09 mW/cm2 UVB exposure of HLECs (Kang et al., 2020).

## Time Concordance

It is well-accepted that deposition of energy into matter results in immediate vibrational changes to molecules or ionization events. Deposition of energy is therefore an upstream event to all follow-on latent events like oxidative stress.

## RONS

Cardiovascular tissue:

In TICAE and TIME cells, ROS increased at 45 minutes after X-ray irradiation (Ramadan et al., 2020). Superoxide and peroxide production were increased 1 day after 2-8 Gy of gamma irradiation in CMVECs (Unvari et al., 2013).

Bone tissue:

hBMMSCs irradiated with X-rays at 2 Gy showed peak ROS production at 2-8h post-irradiation (Zhang et al., 2018). Murine RAW264.7 cells (can undergo osteoclastogenesis) irradiated with 2 Gy of gamma rays showed increased ROS at 2-8h post-irradiation (Huang et al., 2018).

Brain tissue:

In human lymphoblast cells exposed to 2 Gy of X-rays, ROS were increased at various times between 13 and 29 days post-irradiation (Rugo and Schiestl, 2004). RONS were increased in human neural stem cells at 12-48h post-irradiation with 2 and 5 Gy of gamma rays (Acharya et al., 2010). ROS levels were increased in rat neural precursor cells at 6-24h after irradiation with 1-10 Gy of protons (Giedzinksi et al., 2005). Both 56Fe (1.3 Gy) and gamma ray (2 Gy) irradiation of mice increased ROS levels after 2 months post-irradiation in the cerebral cortex (Suman et al., 2013). ROS were also increased 12 months after 56Fe irradiation (Suman et al., 2013). RONS increased as early as 12h post-irradiation continuing to 8 weeks with 2-200 cGy doses of 56Fe irradiation of mouse neural stem/precursor cells (Tseng et al., 2014). The same cell type irradiated with 1 and 5 Gy of 56Fe irradiation showed increased ROS at 6h post-irradiation, with the last increase observed 25 days post-irradiation (Limoli et al., 2004).

Eye tissue:

Mice exposed to 11 Gy of X-rays showed increased ROS at 9 months post-irradiation in lenses (Pendergrass et al., 2010). In human lens cells, ROS were found increased at 1h after 0.25 Gy gamma ray irradiation (Ahmadi et al., 2021), 15 minutes after 30 mJ/cm2 UV radiation (Jiang et al., 2006),
2.5-120 minutes after 0.014 and 0.14 J/cm2 UV radiation (Cencer et al., 2018), and 24h after 30 mJ/cm2 UVB-radiation (Yang et al., 2020).

Antioxidants

Cardiovascular tissue:

CAT antioxidant enzyme was decreased in mice aortas as early as 3 days post-irradiation, remaining decreased until 84 days after irradiation with 18 Gy of X-rays (Shen et al., 2018). The antioxidant enzymes peroxiredoxin 5 (PRDX5) and SOD were both shown to have the greatest decrease at 24h after 2 Gy gamma irradiation of TICAE cells (Philipp et al., 2020).

Eye tissue:

Bovine lenses irradiated with 44.8 J/cm2 of UVA radiation showed decreased CAT levels at 48-168h post-irradiation (Weinreb and Dovrat, 1996). UV irradiation of mice at 20.6 kJ/m2 led to decreased GSH at both 1 and 16 months post-irradiation in the lens (Zhang et al., 2012). Bovine lens cells exposed to 10 Gy of X-rays showed decreased levels of the antioxidant GSH at 24 and 120h after exposure (Belkacemi et al., 2001).

Oxidative damage markers

Cardiovascular tissue:

Oxidative damage markers 4-hydroxynonemal (4-HNE) and 3-Nitrotyosine (3-NT) were both significantly increased in the aorta of mice at 3 days post-irradiation, remaining increased until 84 days after irradiation with 18 Gy of X-rays (Shen et al., 2018).

Essentiality

Radiation has been found to induce oxidative stress above background levels. Many studies have shown that lower doses of ionizing radiation resulted in decreased levels in markers of oxidative stress in multiple cell types (Acharya et al., 2010; Ahmadi et al., 2021; Bai et al., 2020; Baluchamy et al., 2012; Chen et al., 2021; Collins-Underwood et al., 2008; Giedzinski et al., 2005; Kook et al., 2015; Kubo et al., 2010; Philipp et al., 2020; Ramadan et al., 2020; Ungvari et al., 2013; Veeraraghan et al., 2011; Wang et al., 2019b; Zigman et al., 2000; Zigman et al., 1995). The essentiality of deposition of energy can be assessed through the removal of deposited energy, a physical stressor that does not require to be metabolized in order to elicit downstream effects on a biological system. Studies that do not deposit energy are observed to have no downstream effects.

Uncertainties and Inconsistencies

There are several uncertainties and inconsistencies in this KER.

* Chen et al. (2021) found that radiation can have adaptive responses. The study used three neutron radiation doses, 0.4 and 1.2 Sv, and 3.6 Sv. After 0.4 and 1.2 Sv, the activity of antioxidant enzymes GSH and SOD increased, and the concentration of malondialdehyde, a product of oxidative stress, decreased. After 3.6 Sv, the opposite was true.

* While the concentration of most antioxidant enzymes decreases after energy deposition, there is some uncertainty with SOD. Certain papers have found that its concentration decreases with dose (Chen et al., 2021; Hua et al., 2019; Ji et al., 2015; Kang et al., 2020) while others found no difference after irradiation (Rogers et al., 2004; Zigman et al., 1995). Several studies have also found that higher levels of SOD do not increase resistance to UV radiation (Eaton, 1994; Hightower, 1995).

* At 1-week post-irradiation with 10 Gy of 60Co gamma rays, TICAE cells experienced a significant increase in levels of the antioxidant, PRDX5, contrary to the decrease generally seen in antioxidant levels following radiation exposure (Philipp et al., 2020).
* Various studies found an increase in antioxidant SOD levels within the brain after radiation exposure (Acharya et al., 2010; Baluchamy et al., 2012; Baulch et al., 2015; Veeraraghan et al., 2011).

* Chien et al. (2015) found no changes to ROS levels in hippocampal neurons five days after 0.2 Gy of electron radiation.

* Antioxidants that increase in expression are indicative of the presence of RONS. When antioxidants decrease in expression/activity, this is most likely due to the overwhelming of the antioxidant defence mechanisms

* There is limited data to support an understanding of deposition of energy leading to oxidative stress at low doses.

## Known modulating factors

<table><thead><tr><td>Modulating Factors</td><td>MF details</td><td>Effects on the KER</td><td>References</td></tr></thead><tbody><tr><td>Antioxidants</td><td>CAT, GSH-Px, SOD, PRDX, vitamin E, C, carotene, lutein, zeaxanthin, selenium, zinc, alpha-lipoic acid, melatonin, ginko biloba leaf, fermented ginkobiloba leaf, Nigella sativa oil, thymoquinone, and ferulic acid</td><td>Adding or withholding antioxidants will decrease or increase the level of oxidative stress respectively</td><td>(Zigman et al., 1995; Belkacémi et al., 2001; Chitchumroonchokchai et al., 2004; Fatma et al., 2005; Jiang et al., 2006; Fletcher, 2010; Karimi et al., 2017; Hua et al., 2019; Kang et al., 2020; Yang et al., 2020; Manda et al., 2008; Limoli et al., 2007; Manda et al., 2007; Taysi et al., 2012; Ismail et al., 2016; Demir et al., 2020; Chen et al., 2021)</td></tr><tr><td>Age</td><td>Increased age</td><td>Antioxidant levels are lower and show a greater decrease after radiation in older organisms. This compromises their defence system, resulting in ROS increases and therefore, an increased likelihood of oxidative stress</td><td>(Marshall, 1985; Spector, 1990; Giblin et al., 2002; Kubo et al., 2010; Pendergrass et al., 2010; Zhang et al., 2012; Hamada et al., 2014; Tangvarasittichai & Tangvarasittichai, 2019)</td></tr><tr><td>Oxygen</td><td>Increased oxygen levels</td><td>Higher oxygen concentrations increase sensitivity to ROS</td><td>(Hightower et al., 1992; Eaton, 1994; Huang et al., 2006; Zhang et al., 2010; Schoenfeld et al., 2012)</td></tr></tbody></table>

## Quantitative Understanding of the Linkage

The table below provides some representative examples of quantitative linkages between the two key events. It was difficult to identify a general trend across all the studies due to differences in experimental design and reporting of the data. All data is statistically significant unless otherwise stated.

### Response-response Relationship

#### Dose Concordance

<table><thead><tr><td>Reference</td><td>Experiment Description</td><td>Result</td></tr></thead><tbody><tr><td>Attar, Kondolousy and Khansari, 2007</td><td>In vivo. One hundred individuals between 20 and 50 years old in two villages in Iran exposed to background IR at 260 mSv/year had antioxidant levels measured. The control group was from two villages not exposed to the high background radiation. The total antioxidant levels in the blood were determined by the ferric reducing/antioxidant power assay.</td><td>The total antioxidant level was significantly reduced from 1187±199 µmol in the control to 686±170 µmol in the exposed group.</td></tr><tr><td>Klucinski et al., 2008</td><td>In vivo. A group of 14 men and 31 women aged 25–54 years working X-ray equipment (receiving doses of less than 1 mSv/year) for an average of 15.3 years (range of 2-33 years) were compared to a control group for antioxidant activity. Antioxidant activity of SOD,</td><td>Enzymes (SOD, GSH, CAT) showed significantly decreased antioxidant activity in the workers.<br>In the controls (U/g of Hb):<ul><li>SOD: 1200 ± 300</li><li>GSH-Px: 39 ± 7</li></ul></td></tr></tbody></table>
<table>
  <tr>
    <td></td>
    <td>glutathione peroxidase (GSH-Px), and CAT in erythrocytes were measured in U/g of hemoglobin.</td>
    <td>
      <ul>
        <li>CAT: 300 ± 60</li>
        <li>In the workers (U/g of Hb):</li>
        <li>SOD: 1000 ± 200</li>
        <li>GSH-Px: 29 ± 4</li>
        <li>CAT: 270 ± 50</li>
      </ul>
    </td>
  </tr>
  <tr>
    <td>Limoli et al., 2007</td>
    <td>In vitro. Neural precursor cells isolated from rat hippocampi was exposed to 0.25-5 Gy of 56Fe irradiation at dose rates of 0.5-1.0 Gy/min. ROS were measured 6h post-irradiation.</td>
    <td>At a low dose of 0.25 Gy and 0.5 Gy, relative ROS levels were significantly elevated and showed a linear dose response (from ~1 to ~2.25 relative ROS levels) until 1 Gy, where it reached its peak (~3 relative ROS levels). At higher doses, the relative ROS levels decreased.</td>
  </tr>
  <tr>
    <td>Tseng et al., 2014</td>
    <td>In vitro. Neural stem/precursor cells isolated from mouse subventricular and hippocampal dentate subgranular zones were exposed to 1-15 cGy of 56Fe irradiation at dose rates ranging from 5-50 cGy/min. RONS levels were measured.</td>
    <td>A dose-dependent and significant rise in RONS levels was detected after 56Fe irradiation. 12 h post-irradiation, a steady rise was observed and reached a 6-fold peak after 15 cGy.</td>
  </tr>
  <tr>
    <td>Limoli et al., 2004</td>
    <td>In vitro. Neural precursor cells from rat hippocampus were exposed to 0, 1, 5 and 10 Gy of X-irradiation at a dose rate of 4.5 Gy/min. ROS levels were measured. In vivo. MDA was used to quantify oxidative stress.</td>
    <td>A dose-dependent increase in ROS levels was seen in the first 12 h post-irradiation, with relative maximums at 12 h after 5 Gy (35% increase) and 24 h after 1 Gy (31% increase). ROS levels measured 1 week after 5 Gy were increased by 180% relative to sham-irradiated controls. MDA levels increased significantly (approximately 1.3-fold) after exposure to 10 Gy.</td>
  </tr>
  <tr>
    <td>Collins-Underwood et al., 2008</td>
    <td>In vitro. Immortalized rat brain microvascular endothelial cells were exposed to 1-10 Gy of 137Cs-irradiation at a dose rate of 3.91 Gy/min. Intracellular ROS and O2-production were both measured.</td>
    <td>Irradiation resulted in a significant dose-dependent increase in intracellular ROS generation from 1-10 Gy. At 5 Gy, there was an approximate 10-fold increase in ROS levels, and at 10 Gy there was an approximate 20-fold increase.</td>
  </tr>
  <tr>
    <td>Giedzinski et al., 2005</td>
    <td>In vitro. Neural precursor cells were irradiated with 1, 2, 5 and 10 Gy of 250 MeV protons (1.7-1.9 Gy/min) and X-irradiation (4.5 Gy/min). ROS levels were measured.</td>
    <td>There was a rapid increase in ROS at 6, 12, 18 and 24h after proton irradiation, with an exception at the 1 Gy 18h point. Most notably, at 6h post-irradiation, a dose-dependent increase in relative ROS levels from 1 to 10 Gy was seen that ranged from 15% (at 1 Gy) to 65% (at 10 Gy). Linear regression analysis showed that at ≤2 Gy, ROS levels increased by 16% per Gy. The linear dose response obtained at 24h showed that proton irradiation increased the relative ROS levels by 3% per Gy.</td>
  </tr>
  <tr>
    <td>Veeraraghan et al., 2011</td>
    <td>In vivo. Adult mice were exposed to 2, 10 or 50 cGy of whole-body gamma irradiation at 0.81 Gy/min. Brain tissues were harvested 24h post-irradiation. SOD2 levels and activity were measured.</td>
    <td>Compared to the controls, the levels of SOD2 expression increased in the brain after 2, 10 and 50 cGy. Analysis revealed a significant and dose-dependent change in SOD2 activity. More specifically, SOD2 activity showed significant increases after 10 (~25% increase above control) and 50 cGy (~60% increase above control), but not 2 cGy.</td>
  </tr>
  <tr>
    <td>Baluchamy et al., 2012</td>
    <td>In vivo. Male mice were exposed to whole-body irradiation with 250 MeV protons at 0.01, 1 and 2 Gy and the whole brains were dissected out. ROS, LPO, GSH and total SOD were measured.</td>
    <td>Dose-dependent increases in ROS levels was observed compared to controls, with a two-fold increase at 2 Gy. A 2.5 to 3-fold increase in LPO levels was also seen at 1 and 2 Gy, respectively, which was directly correlated with the increase in ROS levels. Additionally, results showed a significant reduction in GSH (~70% decrease at 2 Gy) and SOD activities (~2-fold decrease) following irradiation that was dose-dependent.</td>
  </tr>
  <tr>
    <td>Acharya et al., 2010</td>
    <td>In vitro. Human neural stem cells were subjected to 1, 2 or 5 Gy of gamma irradiation at a dose rate of 2.2 Gy/min. RONS and superoxide levels were determined.</td>
    <td>Intracellular RONS levels increased by approximately 1.2 to 1.3-fold compared to sham-irradiated controls and was found to be reasonable dose-responsive. At 12h, levels of superoxide increased 2 and 4-fold compared to control for 2 and 5 Gy, respectively. At 24h and 48h, there was a dose-dependent increase in RONS levels. At 7 days, levels of RONS increased approximately 3 to 7-fold for 2 and 5 Gy, respectively.</td>
  </tr>
  <tr>
    <td>Baulch et al., 2015</td>
    <td>In vitro. Human neural stem cells were exposed to 5-100 cGy of 16O, 28Si, 48Ti or 56Fe particles (600 MeV) at 10 50 cGy/min. RONS and superoxide levels were determined.</td>
    <td>3 days post-irradiation, oxidative stress was found to increase after particle irradiation. Most notably, exposure to 56Fe resulted in a dose-dependent increase with 100% increase in RONS levels at 100 cGy. Dose-dependent increase was also seen in superoxide levels after 56Fe irradiation. At 7 days post-irradiation, 56Fe irradiation induced significantly lower nitric oxide levels by 47% (5 cGy), 55% (25 cGy) and 45% (100 cGy).</td>
  </tr>
</table>
<table>
  <tr>
    <td>Bai et al., 2020</td>
    <td>In vitro. bmMSCs were taken from 4-week-old, male Sprague-Dawley rats. After extraction, cells were then irradiated with 2, 5, and 10 Gy of 137Cs gamma rays. Intracellular ROS levels and relative mRNA expression of the antioxidants, SOD1, SOD2, and CAT2, were measured to assess the extent of oxidative stress induced by IR.</td>
    <td>Cellular ROS levels increased significantly in a dose-dependent manner from 0-10 Gy. Compared to sham-irradiated controls, ROS levels increased by ~15%, ~55%, and ~105% after exposure to 2, 5, and 10 Gy, respectively. Antioxidant mRNA expression decreased in a dose-dependent manner from 0-10 Gy, with significant increases seen at doses 2 Gy for SOD1 and CAT2 and 5 Gy for SOD2. Compared to sham-irradiated controls, SOD1 expression decreased by ~9%, ~18%, and ~27% after exposure to 2, 5, and 10 Gy, respectively. SOD2 expression decreased by ~31% and ~41% after exposure to 5 and 10 Gy, respectively. CAT2 expression decreased by ~15%, ~33%, and ~58% after exposure to 2, 5, and 10 Gy, respectively.</td>
  </tr>
  <tr>
    <td>Liu et al., 2018</td>
    <td>In vitro. hBMMSCs were irradiated with 8 Gy of X-rays at a rate of 1.24 Gy/min. Intracellular ROS levels and SOD activity were measured to analyze IR-induced oxidative stress.</td>
    <td>Compared to sham-irradiated controls, hBMMSCs irradiated with 8 Gy of X-rays experienced a significant increase to intracellular ROS levels. hBMMSCs irradiated with 8 Gy of X-rays experienced a ~46% reduction in SOD activity.</td>
  </tr>
  <tr>
    <td>Kook et al., 2015</td>
    <td>In vitro. Murine MC3T3-E1 osteoblast cells were irradiated with 2, 4, and 8 Gy of X-rays at a rate of 1.5 Gy/min. Intracellular ROS levels and the activity of antioxidant enzymes, including GSH, SOD, CAT, were measured to assess the extent of oxidative stress induced by IR exposure.</td>
    <td>Compared to sham-irradiated controls, irradiated MC3T3-E1 cells experienced a dose-dependent increase in ROS levels, with significant increases at 4 and 8 Gy (~26% and ~38%, respectively). Antioxidant enzyme activity initially increased by a statistically negligible amount from 0-2 Gy and then decreased in a dose-dependent manner from 2-8 Gy. SOD activity decreased significantly at 4 and 8 Gy by ~29% and ~59%, respectively. GSH activity similarly decreased significantly at 4 and 8 Gy by ~30% and ~48%, respectively. CAT activity did not change by a statistically significant amount.</td>
  </tr>
  <tr>
    <td>Liu et al., 2019</td>
    <td>In vivo. 8-10-week-old, juvenile, female SPF BALB/c mice underwent whole-body irradiation with 2 Gy of 31.6 keV/µm 12C heavy ions at a rate of 1 Gy/min. ROS levels were measured from femoral bone marrow mononuclear cells of the irradiated mice to analyze IR-induced oxidative stress.</td>
    <td>Compared to sham-irradiated controls, irradiated mice experienced a ~120% increase in ROS levels.</td>
  </tr>
  <tr>
    <td>Zhang et al., 2020</td>
    <td>In vitro. Murine RAW264.7 osteoclast precursor cells were irradiated with 2 Gy of 60Co gamma rays at a rate of 0.83 Gy/min. ROS levels were measured to determine the extent of oxidative stress induced by IR exposure.</td>
    <td>Compared to sham-irradiated controls, ROS levels in irradiated RAW264.7 cells increased by ~100%.</td>
  </tr>
  <tr>
    <td>Wang et al., 2016</td>
    <td>In vitro. Murine MC3T3-E1 osteoblast-like cells were irradiated with 6 Gy of X-rays. Intracellular ROS production was measured to assess oxidative stress from IR exposure.</td>
    <td>Compared to sham-irradiated controls, intracellular ROS production increased by ~81%.</td>
  </tr>
  <tr>
    <td>Huang et al., 2018</td>
    <td>In vitro. Murine RAW264.7 osteoblast-like cells were irradiated with 2 Gy of gamma rays at a rate of 0.83 Gy/min. ROS levels were measured to analyze IR-induced oxidative stress.</td>
    <td>Compared to sham-irradiated controls, ROS levels in RAW264.7 cells increased by ~138% by 2 h post-irradiation.</td>
  </tr>
  <tr>
    <td>Zhang et al., 2018</td>
    <td>In vitro. hBMMSCs were irradiated with 2 Gy of X-rays at a rate of 0.6 Gy/min. Relative ROS concentration was measured to assess the extent of oxidative stress induced by IR.</td>
    <td>Compared to sham-irradiated controls, irradiated hBMMSCs experienced a maximum increase of ~90% to ROS levels at 3 h post-irradiation.</td>
  </tr>
  <tr>
    <td>Huang et al., 2019</td>
    <td>In vitro. Rat bmMSC were irradiated with 2 Gy of 60Co gamma rays at a rate of 0.83 Gy/min. ROS levels were measured to assess IR-induced oxidative stress.</td>
    <td>Compared to sham-irradiated controls, ROS levels in irradiated bone marrow stromal cells increased by approximately 2-fold.</td>
  </tr>
  <tr>
    <td>Soucy et al., 2011</td>
    <td>In vivo. 7- to 12-month-old, adult, male Wistar rats underwent whole-body irradiation with 1 Gy of 56Fe heavy ions. ROS production in the aorta was measured along with changes in activity of the ROS-producing enzyme xanthine oxidase (XO) to assess IR-induced oxidative stress.</td>
    <td>Compared to sham-irradiated controls, irradiated mice experienced a 74.6% increase in ROS production (from 4.84 to 8.45) and XO activity increased by 36.1% (6.12 to 8.33).</td>
  </tr>
  <tr>
    <td>Soucy et al., 2010</td>
    <td>In vivo. 4-month-old, adult, male Sprague-Dawley rats underwent whole-body irradiation with 5 Gy of 137Cs gamma rays. Changes in XO activity and ROS production</td>
    <td>Compared to sham-irradiated controls, irradiated mice experienced a ~68% increase in ROS production and a ~46% increase in XO activity.</td>
  </tr>
</table>
<table>
  <tr>
    <td>Karam & Radwan, 2019</td>
    <td>In vivo. Adult male Albino rats underwent irradiation with 5 Gy of 137Cs gamma rays at a rate of 0.665 cGy/s. Activity levels of the antioxidants, SOD and CAT, present in the heart tissue were measured to assess IR-induced oxidative stress.</td>
    <td>Compared to the sham-irradiated controls, SOD and CAT activity decreased by 57% and 43%, respectively, after irradiation.</td>
  </tr>
  <tr>
    <td>Cervelli et al., 2017</td>
    <td>In vitro. HUVECs were irradiated with 0.25 Gy of X-rays at a rate of 91 mGy/min. ROS production was measured to analyze IR-induced oxidative stress.</td>
    <td>Compared to the sham-irradiated controls, irradiated mice experienced a ~171% increase in ROS production (not significant).</td>
  </tr>
  <tr>
    <td>Mansour, 2013</td>
    <td>In vivo. Male Wistar rats underwent whole-body irradiation with 6 Gy of 137Cs gamma rays at a rate of 0.012 Gy/s. MDA was measured from heart homogenate, along with the antioxidants: SOD, GSH, and GSH-Px.</td>
    <td>Compared to sham-irradiated controls, MDA increased by 65.9%. SOD, GSH-Px, and GSH decreased by 33.8%, 42.4%, and 50.0%, respectively.</td>
  </tr>
  <tr>
    <td>Soltani, 2016</td>
    <td>In vitro. HUVECs were irradiated with 2 Gy of 60Co gamma rays at a dose rate of 0.6 Gy/min. Markers of oxidative stress, including reduced GSH and TBARS, were measured to assess GSH depletion and LPO, respectively.</td>
    <td>Compared to non-irradiated controls, sham-irradiated cells experienced a ~28% decrease in GSH and a ~433% increase in TBARS.</td>
  </tr>
  <tr>
    <td>Wang et al., 2019b</td>
    <td>In vitro. HUVECs were irradiated with 0.2, 0.5, 1, 2, and 5 Gy of 137Cs gamma rays. ROS production was measured to assess IR-induced oxidative stress.</td>
    <td>Compared to sham-irradiated controls, ROS production increase significantly ~32% at 5 Gy. While changes to ROS production were insignificant at doses &lt;2 Gy, following a linear increase from 0-5 Gy.</td>
  </tr>
  <tr>
    <td>Sharma et al., 2018</td>
    <td>In vitro. HUVECs were irradiated with 9 Gy of photons. ROS production was measured to determine the effects of IR on oxidative stress.</td>
    <td>Compared to sham-irradiated controls, irradiated HUVECs displayed ~133% increase in ROS production.</td>
  </tr>
  <tr>
    <td>Hatoum et al., 2006</td>
    <td>In vivo. Sprague-Dawley rats were irradiated with 9 fractions of 2.5 Gy of X-rays for a cumulative dose of 22.5 Gy at a rate of 2.43 Gy/min. Production of the ROS superoxide and peroxide in gut arterioles were measured to determine the level of oxidative stress caused by irradiation.</td>
    <td>ROS production started increasing compared to the sham-irradiated control after the second dose and peaked at the fifth dose. By the ninth dose, superoxide production increased by 161.4% and peroxide production increased by 171.3%.</td>
  </tr>
  <tr>
    <td>Phillip et al., 2020</td>
    <td>In vitro. Human TICAE cells were irradiated with 0.25, 0.5, 2, and 10 Gy of 60Co gamma rays at a rate of 0.4 Gy/min. Levels of the antioxidants, SOD1 and PRDX5 were measured to assess oxidative stress from IR exposure.</td>
    <td>While SOD1 levels did not follow a dose-dependent pattern. At 2 Gy, SOD1 decreased about 0.5-fold. At 1 week post-irradiation, PRDX5 remained at approximately control levels for doses &lt;2 Gy but increased by ~60% from 2-10 Gy. PRDX5 only decreased at 2 Gy and 24h post-irradiation.</td>
  </tr>
  <tr>
    <td>Ramadan et al., 2020</td>
    <td>In vitro. Human TICAE/TIME cells were irradiated with 0.1 and 5 Gy of X-rays at a dose rate of 0.5 Gy/min. Intracellular ROS production was measured to determine the extent of IR-induced oxidative stress.</td>
    <td>ROS production saw a dose-dependent increase in both TICAE and TIME cells. By 45 min post-irradiation, 0.1 Gy of IR had induced increases to ROS production of ~3.6-fold and ~8-fold in TICAE and TIME cells, respectively, compared to sham-irradiated controls. 5 Gy of IR caused more significant increases to ROS production of ~18-fold and ~17-fold in TICAE and TIME cells, respectively, compared to sham-irradiated controls.</td>
  </tr>
  <tr>
    <td>Shen et al., 2018</td>
    <td>In vivo. 8-week-old, female, C57BL/6 mice were irradiated with 18 Gy of X-rays. Levels of the oxidative markers, 4-HNE and 3-NT, and the antioxidants, CAT and heme oxygenase 1 (HO-1) were measured in the aortas of the mice.</td>
    <td>Compared to sham-irradiated controls, irradiated mice saw maximum increases of ~1.75-fold on day 14 and ~2.25-fold on day 7 to 4-HNE and 3-NT levels, respectively. While CAT levels decreased up to 0.33-fold on day 7, HO-1 levels increased by ~1.9-fold on day 7.</td>
  </tr>
  <tr>
    <td>Ungvari et al., 2013</td>
    <td>In vitro. The CMVECs of adult male rats were irradiated with 2, 4, 6, and 8 Gy of 137Cs gamma rays. Production of the reactive oxygen species, peroxide and O2-., were measured to assess the extent of IR-induced oxidative stress.</td>
    <td>Compared to sham-irradiated controls, production of peroxide in CMVECs of irradiated mice 1 day post exposure increased in a dose-dependent manner from 0-8 Gy, with significant changes observed at doses &gt;4 Gy. At 8 Gy, peroxide production had increased ~3.25-fold. Production of O2.- followed a similar dose-dependent increase with significant observed at doses &gt;6 Gy. At 8 Gy, O2.- production increased ~1.6-fold. 14 days post-exposure, IR-induced changes to ROS production were not significant for either peroxide or O2.- and did not show a dose-dependent pattern. ROS production progressively decreased from 0-4 Gy and then recovered from 6-8 Gy back to control levels.</td>
  </tr>
  <tr>
    <td>Ahmadi et al., 2021</td>
    <td>In vitro. HLEC and HLE-B3 cells were exposed to 0.1, 0.25 and 0.5 Gy of gamma irradiation at 0.3 and 0.065 Gy/min. Intracellular ROS levels were measured.</td>
    <td>In HLE-B3 cells, there were about 7 and 17% ROS-positive cells 1 h after exposure to 0.25 and 0.5 Gy respectively at 0.3 Gy/min.</td>
  </tr>
</table>
<table>
  <tr>
    <td></td>
    <td></td>
    <td>24 h after exposure there were about 10% ROS-positive cells after 0.5 Gy at 0.3 Gy/min.<br/>1 h after exposure there were about 13 and 17% ROS-positive cells at 0.25 and 0.5 Gy and 0.065 Gy/min.<br/>24 h after exposure there were 8% ROS-positive cells after 0.5 Gy and 0.065 Gy/min.<br/>In human lens epithelial cells 1 h after exposure there were about 10 and 19% ROS-positive cells after 0.25 and 0.5 Gy at 0.3 Gy/min.<br/>After exposure to 0.5 Gy at 0.065 Gy/min there were about 16 and 9% ROS-positive cells one and 24 h after exposure.</td>
  </tr>
  <tr>
    <td>Ji et al, 2015</td>
    <td>In vitro. HLECs were exposed to UVB irradiation (297 nm 2 W/m2) for 0 – 120 min. Total antioxidative capability (T-AOC), ROS levels, MDA, and SOD were measured at various time points at 5-120 min.</td>
    <td>HLECs exposed to 1 W/m2 UVB for 0 - 120 min (representative of dose) showed a gradual increase in ROS levels that began to plateau 105 min post-irradiation at an ROS level 750 000x control.</td>
  </tr>
  <tr>
    <td>Hua et al, 2019</td>
    <td>In vitro. HLECs were exposed to 4050, 8100 and 12,150 J/m2 of UVB-irradiation at 1.5, 3.0 and 4.5 W/m2. MDA, SOD, GSH-Px, and GSH were measured.</td>
    <td>MDA activity as a ratio of the control increased about 1.5 at 3.0 W/m2 and about 3 at 4.5 W/m2.<br/>SOD activity as a ratio of the control decreased about 0.1 at 1.5 W/m2, 0.2 at W/m2, and 0.3 at 4.5 W/m2.<br/>GSH-Px activity as a ratio of the control decreased about 0.02 at 3.0 W/m2 and 0.2 at 4.5 W/m2.<br/>GSH activity as a ratio of the control decreased about 0.2 at 3.0 W/m2 and 0.7 at 4.5 W/m2.</td>
  </tr>
  <tr>
    <td>Chen et al, 2021</td>
    <td>In vivo. Male rats were irradiated with 0, 0.4, 1.2 and 3.6 Sv of neutron-irradiation at 14, 45 and 131 mSv/h. In rat lenses, MDA, GSH, and SOD, were measured.</td>
    <td>MDA concentration decreased by about 1.5 nmol/mg protein at 1.2 Sv and increased by about 7.5 nmol/mg protein relative to the control at 3.6 Sv.<br/>GSH concentration increased by about 3.5 µg/mg protein and decreased by about 1 µg/mg protein relative to the control at 3.6 Sv (neutron radiation).<br/>SOD activity decreased by about 0.08 U/mg protein relative to the control at 3.6 Sv.<br/>It should be noted that Sv is not the correct unit when investigating animals and cultured cells, radiation should have been measured in Gy (ICRU, 1998).</td>
  </tr>
  <tr>
    <td>Zigman et al., 2000</td>
    <td>In vitro. Rabbit LECs were exposed to 3-12 J/cm2 of UVA-irradiation (300-400 nm range, 350 nm peak). CAT activity was assayed to demonstrate oxidative stress.</td>
    <td>Rabbit LECs exposed to 3 – 12 J/cm2 UVA showed an approximately linear decrease in catalase activity (indicative of increased oxidative stress) with the maximum dose displaying a 3.8x decrease.</td>
  </tr>
  <tr>
    <td>Chitchumroonchokchai et al, 2004</td>
    <td>In vitro. HLECs were exposed to 300 J/m2 of UVB-irradiation at 3 mW/cm2. MDA and HAE were used to measure oxidative stress.</td>
    <td>The concentration of MDA and HAE increased by about 900 pmol/mg protein compared to the control after irradiation with 300 J/m2 UVB.</td>
  </tr>
  <tr>
    <td>Zigman et al, 1995</td>
    <td>In vitro. Rabbit and squirrel LECs were exposed to 6, 9, 12, 15 and 18 J/m2 of UV-irradiation at 3 J/cm2/h (300-400 nm range, 350 nm peak). CAT was used to measure oxidative stress levels.</td>
    <td>The CAT activity was 10% of the control activity at 6 J/cm2, and then decreased to 0% of the control activity at 18 J/cm2 (99.9% UV-A and 0.1% UV-B).</td>
  </tr>
  <tr>
    <td>Karimi et al, 2017</td>
    <td>In vivo. Adult rats were exposed to 15 Gy of gamma 60Co-irradiation at a dose rate of 98.5 cGy/min. In lens tissue, MDA, thiobarbituric acid (TBA), and GSH levels were used to indicate oxidative stress.</td>
    <td>MDA concentration increased from 0.37 +/- 0.03 to 1.60 +/- 0.16 nmol/g of lens after irradiation.<br/>GSH concentration decreased from 0.99 +/- 0.06 to 0.52 +/- 0.16 µmol/g of lens after exposure.</td>
  </tr>
  <tr>
    <td>Rong et al., 2019</td>
    <td>In vitro. HLECs were exposed to UVB-irradiation (297 nm 2 W/m2 for 10 min). Intracellular H2O2 and superoxide levels were measured.</td>
    <td>The amount of ROS was measured as the dichlorofluoroscein (DCFH-DA) fluorescence density, which increased about 10-fold relative to the control.<br/>A similar test but with dihydroethidium (DHE) staining showed a fluorescence density increase of about 3-fold relative to the control.</td>
  </tr>
  <tr>
    <td>Kubo et al., 2010</td>
    <td>In vitro. Lenses isolated from mice were exposed to 400 or 800 J/m2 of UVB-irradiation. ROS levels were measured.</td>
    <td>The ratio of ROS level/survived LECs increased from about 175 to 250% after exposure to 400 and 800 J/m2 UVB respectively.</td>
  </tr>
</table>
<table><tr><td>Kang et al., 2020</td><td>In vitro. HLECs were exposed to 0.09 mW/cm2 UVB-irradiation (275-400 nm range, 310 nm peak) for 15 min. MDA and SOD activity were measured.</td><td>MDA activity increased about 30% compared to control after 15 min of 0.09 mW/cm2 UVB exposure. SOD activity decreased about 50% compared to control under the same conditions.</td></tr><tr><td>Yang et al., 2020</td><td>In vitro. HLEs were irradiated with 30 mJ/cm2 of UVB-irradiation. ROS levels were determined.</td><td>The level of ROS production in HLEs increased approximately 5-fold as determined by 2',7'-dichlorofluorescein diacetate after exposure to 30 mJ/cm2 UVB.</td></tr><tr><td>Zhang et al., 2012</td><td>In vivo. Adult mice were exposed to 20.6 kJ/m2 UV-irradiation (313 nm peak; 1.6 mW/cm2). GSH levels were measured in lens homogenates.</td><td>Decrease in GSH of about 1 and 2 µmol/g wet weight compared to control after 1 and 16 months respectively after 20.6 kJ/m2 UV (313 nm peak) at 1.6 mW/cm2.</td></tr></table>

Time-scale

Time Concordance

<table><thead><tr><td>Reference</td><td>Experiment Description</td><td>Result</td></tr></thead><tbody><tr><td>Tseng et al., 2014</td><td>In vitro. Neural stem/precursor cells isolated from mouse subventricular and hippocampal dentate subgranular zones were exposed to 1-200 cGy of 56Fe irradiation at dose rates ranging from 5-50 cGy/min. RONS were measured from 1 to 8 weeks post-irradiation.</td><td>Compared to sham-irradiated controls, a trend toward increasing oxidative stress was seen, particularly at 1- and 4-weeks post-irradiation where RONS levels showed dose-responsive increases. The greatest rise was also seen at 10 cGy where relative RONS levels increased ~2-fold from 1 to 4 weeks, ~3-fold from 4 to 6 weeks and ~2-fold from 6 to 8 weeks. RONS were also found increased at doses as low as 2 cGy at 12 and 24h post-irradiation.</td></tr><tr><td>Suman et al., 2013</td><td>In vivo. Female mice were exposed to either 1.3 Gy of 56Fe irradiation (1 GeV/nucleon; dose rate of 1 Gy/min) or 2 Gy of gamma irradiation (dose rate of 1 Gy/min). ROS were measured in cerebral cortical cells at 2 and 12 months.</td><td>ROS levels showed statistically significant increases after 56Fe irradiation at both 2 and 12 months, while gamma irradiation led to an increase at only 2 months. The percent fluorescence intensity of ROS levels for control, gamma irradiated and 56Fe-irradiated were approximately 100, 115 and 140 at 2 months, and 100, 90 and 125 at 12 months, respectively.</td></tr><tr><td>Limoli et al., 2004</td><td>In vitro. Neural stem/precursor cells isolated from mouse subventricular and hippocampal dentate subgranular zones were exposed to 1 or 5 Gy of 56Fe irradiation at dose rates ranging from 4.5 Gy/min. RONS were measured at various time points until 33 days post-exposure.</td><td>ROS levels exhibited statistically significant fluctuations, increasing over the first 12h before dropping at 18h and rising again at 24h. At 5 Gy, ROS levels fluctuated with a peak at 7 days, a decrease at 13 days, an increase at 25 days, and a decrease below control levels at 33 days. At 1 Gy, ROS levels peaked at 25 days and also decreased below control at 33 days.</td></tr><tr><td>Gledzinski et al., 2005</td><td>In vitro. Neural precursor cells derived from rats were irradiated with 1, 2, 5 and 10 Gy of proton (1.7-1.9 Gy/min). ROS levels were determined at 5-25h post-irradiation.</td><td>Proton irradiation led to a rapid rise in ROS levels, with the increase most marked at 6h (approximately 10-70% for 1 and 10 Gy, respectively). The increase in ROS persisted for 24h, mainly for 10 Gy where the ROS levels were around 30% above control at the 12, 18 and 24h mark.</td></tr><tr><td>Acharya et al., 2010</td><td>In vitro. Human neural stem cells were subjected to 1, 2 or 5 Gy of gamma irradiation at a dose rate of 2.2 Gy/min. RONS and superoxide levels were measured at various time points until 7 days.</td><td>Intracellular RONS and superoxide levels showed significant increase from 2- to 4-fold at 12h. At 7 days, levels of RONS increased and were dose-responsive, elevated by ~3- to 7-fold and 3- to 5-fold, respectively, over sham-irradiated controls.</td></tr><tr><td>Rugo and Schiestl, 2004</td><td>In vitro. Human lymphoblast cell lines (TK6 and TK6 E6) were irradiated with 2 Gy of X-irradiation at a dose rate of 0.72 Gy/min. ROS levels were measured at various time points until 29 days.</td><td>In the TK6 E6 clones, there was only a significant ROS increase at day 29 (45.7 DCF fluorescence units). In the TK6 clones, there were significant ROS increases at days 13 (26.0 DCF fluorescence units), 15 (26.3 DCF fluorescence units) and 20 (38.1 DCF fluorescence units), with a strong trend of increased ROS in the treated group at day 25. On day 18, ROS levels decreased in the irradiated group, and there was no significant difference at day 29.</td></tr><tr><td>Huang et al., 2018</td><td>In vitro. Murine RAW264.7 cells were irradiated with 2 Gy of gamma rays at a rate of 0.83 Gy/min. ROS levels were measured at 2 and 8 h post-irradiation.</td><td>ROS levels in irradiated RAW264.7 cells decreased by ~10% from 2 h post-exposure to 8 h post-exposure (from ~138% above control at 2 h to ~98% above control at 8).</td></tr><tr><td>Zhang et al., 2018</td><td>In vitro. hBMMSCs were irradiated with 2 Gy of X-rays at a rate of 0.6 Gy/min. Relative ROS concentration was measured at 0, 0.5, 2, 3, 6, 8, and 12 h post-irradiation.</td><td>ROS levels increased in time dependent manner until a peak of ~90% above control level at 3 h-post irradiation, and then steadily declined back to approximately control levels at 12 h post-irradiation.</td></tr></tbody></table>
<table>
   <tr>
    <td>Phillip et al., 2020</td>
    <td>In vitro. Human TICAE cells were irradiated with 0.25, 0.5, 2, and 10 Gy of 60Co gamma rays at a rate of 400 mGy/min. Levels of the antioxidants, SOD1 and PRDX5 were measured at 4 h, 24 h, 48 h, and 1-week post-irradiation to assess oxidative stress from IR exposure.</td>
    <td>SOD1 levels did not follow a time-dependent pattern. However, SOD1 decreased at 2 Gy for every timepoint post-irradiation. While PRDX5 levels stayed at approximately baseline levels for the first two days after exposure to 10 Gy of radiation, levels elevated by ~1.6-fold after 1 week.</td>
   </tr>
   <tr>
    <td>Ramadan et al., 2020</td>
    <td>In vitro. Human TICAE/TIME cells were irradiated with 0.1 and 5 Gy of X-rays at a rate of 0.5 Gy/min. Intracellular ROS production was measured at 45 min, 2 h, and 3 h post-irradiation.</td>
    <td>After irradiation, ROS production saw time-dependent decreases in both TICAE and TIME cells from 45 min to 3 h post-exposure. ROS production was elevated at 45 min but returned to approximately baseline levels at 2 and 3 h.</td>
   </tr>
   <tr>
    <td>Shen et al., 2018</td>
    <td>In vivo. 8-week-old, female, C57BL/6 mice were irradiated with 18 Gy of X-rays. Levels of the oxidative markers, 4-HNE and 3-NT, and the antioxidants, CAT and heme HO-1 were measured the aortas of the mice at 3, 7, 14, 28, and 84 days post-irradiation.</td>
    <td>Significant changes were observed in 4-HNE, 3-NT, CAT, and HO-1 levels of irradiated mice after 3 days. 3-NT and HO-1 levels increased from days 3 to 7 and then progressively decreased, while 4-HNE levels followed the same pattern but with a peak at day 14. CAT levels were at their lowest at day 3 and followed a time dependent increase until day 84.</td>
   </tr>
   <tr>
    <td>Ungvari et al., 2013</td>
    <td>In vitro. The CMVECs of adult male rats were irradiated with 2, 4, 6, and 8 Gy of 137Cs gamma rays. Production of the reactive oxygen species, peroxide and superoxide, were measured at 1- and 14-days post-irradiation.</td>
    <td>ROS production was generally higher at day 1 than day 14, with the difference becoming progressively more significant from 2-8 Gy. Peroxide production was reduced from a ~3.25-fold increase compared to controls at day 1 back to baseline levels at day 14. Superoxide production had a ~1.6-fold increase at day 1 recover to baseline levels at day 14.</td>
   </tr>
   <tr>
    <td>Ahmadi et al., 2021</td>
    <td>In vitro. HLEC and HLE-B3 cells were exposed to 0.1, 0.25 and 0.5 Gy of gamma irradiation at 0.3 and 0.065 Gy/min. ROS levels were measured.</td>
    <td>In human LECs immediately exposed to 0.25 Gy gamma rays, the level of ROS positive cells increased by 5%, relative to control, 1 h post-irradiation.</td>
   </tr>
   <tr>
    <td>Jiang et al., 2006</td>
    <td>In vitro. HLECs were exposed to UV-irradiation at a wavelength over 290 nm (30 mJ/cm2). ROS levels were measured.</td>
    <td>Approximately 10-fold increase in ROS generation 15 min after exposure to 30 mJ/cm2 UV.</td>
   </tr>
   <tr>
    <td>Pendergrass et al., 2010</td>
    <td>In vivo. Female mice were irradiated with 11 Gy of X-irradiation at a dose rate of 2 Gy/min. ROS levels in the lenses were used to represent oxidative stress.</td>
    <td>9 months after irradiation with 11 Gy X-rays at 2 Gy/min there's 2250% cortical ROS relative to the control. 3 months after there was no significant change.</td>
   </tr>
   <tr>
    <td>Belkacemi et al., 2001</td>
    <td>In vitro. Bovine lens cells were exposed to 10 Gy of X-irradiation at 2 Gy/min. GSH levels were measured.</td>
    <td>The intracellular GSH pool was measured by a decrease of about 15% monobromobimane fluorescence relative to the control 24 h after exposure to 10 Gy X-rays at 2 Gy/min and there was a decrease of about 40% relative to the control by 120 h.</td>
   </tr>
   <tr>
    <td>Weinreb and Dovrat, 1996</td>
    <td>In vitro. Bovine lenses were irradiated with 22.4 J/cm2 (10 min) and 44.8 J/cm2 (100 min) of UVA-irradiation at 8.5 mW/cm2. CAT levels were determined.</td>
    <td>CAT activity decreased from 1.75 (control) to 0.5 U/mg protein at 48-168 h after exposure to 44.8 J/cm2 UV-A.</td>
   </tr>
   <tr>
    <td>Cencer et al., 2018</td>
    <td>In vitro. HLECs were exposed to 0.014 and 0.14 J/cm² of UVB-irradiation at 0.09, 0.9 mW/cm² for 2 and 5 min. ROS levels (mainly H₂O₂) were measured.</td>
    <td>About 5 min after exposure to both 0.09 and 0.9 mW/cm2 UVB for 2.5 min there is an increase of about 4 average brightness minus control (densitometric fluorescence scanning for ROS, mostly indicating H₂O₂). About 90 and 120 min after exposure to 0.9 mW/cm² the average brightness minus control is about 35 and 20 respectively.</td>
   </tr>
   <tr>
    <td>Yang et al., 2020</td>
    <td>In vitro. HLECs were irradiated with 30 mJ/cm2 of UVB-irradiation. Intracellular ROS levels were measured.</td>
    <td>The level of ROS production in HLECs increased approximately 5-fold as determined by 2',7'-dichlorofluorescein diacetate 24 h after exposure to 30 mJ/cm2 UVB.</td>
   </tr>
   <tr>
    <td>Zhang et al., 2012</td>
    <td>In vivo. Adult mice were exposed to 20.6 kJ/m2 UV-irradiation (313 nm peak; 1.6 mW/cm2). GSH levels were measured in lens homogenates.</td>
    <td>Decrease in GSH of about 1 and 2 µmol/g wet weight compared to control after 1 and 16 months respectively after 20.6 kJ/m2 UV (313 nm peak) at 1.6 mW/cm2.</td>
   </tr>
  </table>
Known Feedforward/Feedback loops influencing this KER

The relationship between deposition of energy and increased oxidative stress leads to several feedforward loops. Firstly, ROS activates the transforming growth factor beta (TGF)-β, which increases the production of ROS. This process is modulated in normal cells containing PRDX-6, or cells with added MnTBAP, which will both prevent TGF-β from inducing ROS formation (Fatma et al., 2005). Secondly, ROS can damage human mitochondrial DNA (mtDNA), this can then cause changes to the cellular respiration mechanisms, leading to increased ROS production (Turner et al., 2002; Zhang et al., 2010; Tangvarasittichai & Tangvarasittichai, 2019, Ahmadi et al., 2021; Yves, 2000). Some other feedback loops through which deposition of energy causes oxidative stress are discussed by Soloviev & Kizub (2019).
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## AOPs Referencing Relationship

<table><thead><tr><td>AOP Name</td><td>Adjacency</td><td>Weight of Evidence</td><td>Quantitative Understanding</td></tr></thead><tbody><tr><td>Deposition of Energy Leading to Learning and Memory Impairment</td><td>adjacent</td><td>Moderate</td><td>Moderate</td></tr></tbody></table>

## Evidence Supporting Applicability of this Relationship

The domain of applicability is related to any vertebrates and invertebrates with an innate immune system regardless of sex (Beck & Habicht, 1996, Sonetti et al., 1994, Rowley, 1996). The deposition of energy is most detrimental in utero because tissue resident cells and their pro-inflammatory responses can cause permanent tissue damage (Heiervang et al., 2010, McCollough et al., 2007, Kannan et al., 2007).

## Taxonomic Applicability

<table><thead><tr><td>Term</td><td>Scientific Term</td><td>Evidence</td><td>Link</td></tr></thead><tbody><tr><td>human</td><td>Homo sapiens</td><td>Low</td><td>NCBI</td></tr><tr><td>mouse</td><td>Mus musculus</td><td>Moderate</td><td>NCBI</td></tr><tr><td>rat</td><td>Rattus norvegicus</td><td>Moderate</td><td>NCBI</td></tr></tbody></table>

## Life Stage Applicability

<table><thead><tr><td>Term</td><td>Evidence</td></tr></thead><tbody><tr><td>All life stages</td><td>Moderate</td></tr></tbody></table>

## Sex Applicability

<table><thead><tr><td>Sex</td><td>Evidence</td></tr></thead><tbody><tr><td>Unspecific</td><td>Moderate</td></tr></tbody></table>

## Key Event Relationship Description

Deposition of energy refers to particles that have sufficient energy to penetrate biological tissue leading to ionization events that can break water molecules and form free radicals. These can damage sensitive macromolecules such as DNA, protein and lipids (Chen, Oyarzabal & Hong, 2016; Mavragani et al., 2016). Ionization events occur from many types of radiation including, X-rays, gamma-rays, alpha particles, beta particles, heavy ions, and neutrons. X-rays and gamma rays induce sparse ionization events and energy is exponentially absorbed by tissues. Conversely, energetic charged particles can cause dense ionization events, leading to clustered damage and secondary ionization events (Niemantsverdriet et al., 2012).

When sufficient energy is deposited it can damage the cellular environment; this releases danger signals either passively when the ionization events induce cell death, or actively by cells undergoing life threatening stress (Denning et al., 2019; Vénéreau, Ceriotti & Bianchi, 2015). These signaling molecules, such as alarmins or damage-associated molecular pattern molecules (DAMPs), promote an inflammatory and regenerative environment by activating tissue resident cells (Chen, Oyarzabal & Hong, 2016; Vénéreau, Ceriotti & Bianchi, 2015). Resident immune cells, such as macrophages and dendritic cells, use pattern recognition receptors on their surfaces to detect alarmins and DAMPs which initiate their activation and proliferation (Chen, Oyarzabal & Hong, 2016; Mavragani et al., 2016). Activated cells can then regulate the recruitment of circulating immune cells and initiate inflammation to remove damaged cells, eliminate harmful stimuli, and promote tissue repair (Schaue et al., 2015; Roh & Sohn, 2018). However, uncontrolled inflammation can then lead to a state of disease progression.
*Evidence Supporting this KER*

The strategy for collating the evidence 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: Moderate

**Biological Plausibility**

There is strong biological evidence and mechanistic understanding linking deposition of energy to tissue resident activation. It is widely accepted that deposition of energy can cause the activation of resident tissue cells (Di Maggio et al., 2015; Frey et al., 2015; Mavragani et al., 2016; Multhoff & Radons, 2012; Pinto et al., 2016; Rodel et al., 2012; Schaue et al., 2015; Yahyapour et al., 2018; Zhao & Robbins, 2009; Rienecker et al., 2021). Ionization of local tissue leads to direct tissue damage, reduced cellular homeostasis, genotoxic stress, and oxidative stress (Mavragani et al., 2016; Yahyapour et al., 2018). This damage can initiate tissue resident cell activation (Davies et al., 2013; Langston, Shibata & Horng, 2017; Rienecker et al., 2021). Primary damage and follow-on free-radical events typically occur within microseconds, but the inflammatory response carries on the damage through waves of reactive oxygen species generation as well as cytokine and chemokine release (Schaue et al., 2015). The resultant loss of cellular homeostasis, as well as primary and secondary cellular damage leads to the release of DAMPs (Mavragani et al., 2016; Yahyapour et al., 2018). Resident cells then use pattern recognition receptors to detect DAMPs resulting in their activation through a series of intracellular signaling cascades (Mavragani et al., 2016; Yahyapour et al., 2018).

There are many resident cells that become activated in response to radiation damage including lymphocytes, neutrophils, endothelial cells, and dendritic cells. Among the resident cells, macrophages are present in virtually all tissues and are the first line of defense against foreign pathogens and stressors. Resident macrophages have a ramified morphology with long, dynamic processes and are constantly surveying for signals of injury or infection (Betlazar et al., 2016; Paladini et al., 2021). They are also scavenger cells which engulf metabolites and debris from surrounding apoptotic cells to maintain healthy organs and tissues. When damage is detected, local macrophages become activated and move to the site of injury, where they signal other immune cells and release cytokines, chemokines, and other soluble molecules to mediate wound healing and initiate an inflammatory response (Hladik & Tapio, 2016; Paladini et al., 2021; Yahyapour et al., 2016; Rienecker et al., 2021). Resident macrophages detect endogenous cellular components released from damaged, stressed, or dying cells through pattern recognition receptors such as toll-like receptors (TLRs) (Chen, Oyarzabal & Hong, 2016; Yahyapour et al., 2016). TLRs can detect a wide variety of DAMPs including those potentially formed by deposition of energy (i.e., oxidized DNA, uric acid, ATP and high-mobility group box 1 protein) (Yahyapour et al., 2016). When TLRs detect DAMPs in the extracellular environment, they initiate intracellular signaling cascades that lead to the nuclear translocation of transcription factors, such as nuclear factor-κB (NF-κB), to induce the production of proinflammatory cytokines and chemokines (Chen, Oyarzabal & Hong, 2016; Yahyapour et al., 2018). The resident macrophages also initiate granulocyte-macrophage colony formation and recruitment of early myeloid progenitors to the site of injury (Schaue et al., 2015).

This response has been shown to occur across organs and tissue types using the same underlying mechanisms (Chen, Oyarzabal & Hong, 2016, Mavragani et al., 2016, Schaue et al., 2015). However, tissues are distinct in the types of activated cells and the resulting inflammatory responses. For example, the liver hosts the largest population of macrophages (Kupper cells) and is enriched with T lymphocytes or natural killer cells (Szabo, Mandrekar & Dolganiuc, 2007). Local Kupper cells use pattern recognition receptors to detect local radiation damage which leads to their activation (Szabo, Mandrekar & Dolganiuc, 2007). Activated cells secrete proinflammatory mediators, recruit macrophages and regulate the response of local T lymphocytes (Szabo, Mandrekar & Dolganiuc, 2007). In the lungs, radiation damage is first detected by local epithelial cells that produce pro-inflammatory mediators including cytokines and reactive oxygen species (Chen et al., 2018). These
mediators stimulate mucus secretion by goblet cells and recruit macrophages and dendritic cells to initiate inflammation (Moldoveanu et al., 2009). In some organs, such as the brain, resident immune cells are abundant because the organ is separated from the immune system by the blood brain barrier to protect it from infection by foreign cells (Banks & Erickson, 2010). It has been shown that brain exposure to ionizing radiation can initiate activation of other types of resident immune cells, such as microglia and astrocytes (Betlazar et al., 2016). Microglial cells are the first line of defense in response to radiation damage and become activated in response to DAMPs released from local damaged cells (Betlazar et al., 2016). Microglia cells release pro-inflammatory mediators to regulate an inflammatory response and recruit additional immune cells to the site of injury (Betlazar et al., 2016). Microglia can subsequently induce astrocyte activation via the COX-2 pathway in the presence of a stressor (Betlazar et al., 2016; Cucinotta et al., 2014; Paladini et al., 2021). When damage is detected, astrocytes proliferate and form scar tissue via reactive gliosis (Makale et al., 2017).

## Empirical Evidence

The empirical evidence surrounding this KER comes from research using in vitro and in vivo models. All organ systems are vulnerable to tissue resident activation from deposition of energy, however, provided below are consistent example of evidence from brain studies. Tissue resident cell activation is typically determined in the brain through the observation of the activation or proliferation of brain-resident immune cells, microglia and astrocytes.

The data consistently shows that direct deposition of energy can elicit damage to tissues and induce resident immune cell activation. The literature space is populated with studies examining effects of high doses (>2 Gy) of radiation with sparse studies examining effects for lower dose exposures (<1 Gy). Much of the high dose evidence is from work exposing rodent models to doses between 0 and 200 cGy of heavy ions and/or protons via whole body irradiation (Allen et al., 2020; Krukowski et al., 2018a; Parihar et al., 2020; Parihar et al., 2018; Parihar et al., 2016; Poulose et al., 2011; Raber et al., 2019; Sumam et al., 2013). Some studies exposing rodents to high energy particles use high dose ranges (up to 4 Gy) (Cummings et al., 2007; Rola et al., 2008). Also included are studies using high doses (1-10 Gy) of X-rays or gamma rays used in a clinical setting (Acharya et al., 2016; Casciati et al., 2016; Chen et al., 2016; Hua et al., 2012; Hwang et al., 2006; Mizumatsu et al., 2003; Monje et al., 2002; Rola et al., 2007; Rola et al., 2004). In addition, very high-dose studies, using doses up to 25-45 Gy were included which showed consistent tissue resident activation following deposition of energy (Chiang, McBride & Withers, 1993; Dey et al., 2020; Kyrkanides et al., 1999; Moravan et al., 2011).

## Dose Concordance

The literature supports the dose-concordance of the relationship between energy deposition and tissue resident cell activation, specifically glial cells, following exposure to ionizing radiation. Some studies, using exposures involving 16O, 48Ti, 4He and protons, observed significant increases in activation at doses of 5, 15, 30 or 50 cGy (Allen et al., 2020; Krukowski et al., 2018a; Parihar et al., 2016; Parihar et al., 2018; Parihar et al., 2020). These studies report an approximate 1.25- to 5-fold increase in microglia markers post-irradiation. Astrocyte activation was not reported in these studies. Other lower dose studies observed a radiation dose-dependent 1.3- to 14-fold increase in markers indicating activation of astrocytes and/or microglia (Casiati et al., 2016; Cummings et al., 2007; Poulose et al., 2011; Raber et al., 2019; Rola et al., 2008; Suman et al., 2013). These studies used 56Fe, protons, 16O or 28 Si, gamma rays and X-rays at doses ranging from 1-4 Gy. Various stressors at moderate doses further support the dose concordance of energy deposition and activation of tissue resident cells (Acharya et al., 2016; Dey et al., 2020; Hua et al., 2012; Monje et al., 2002; Rola et al., 2007; Rola et al., 2004). Consistency in the dose-response relationship was mostly exhibited at the higher doses (2-10 Gy), with reports showing a steady dose-dependent increase in resident tissue activation (Chen et al., 2016; Casciati et al., 2016; Hwang et al., 2006; Rola et al., 2008). With very high doses of radiation (up to 45 Gy), significant increases of GFAP and Mac-I levels in glia are observed (Chiang, McBride & Withers, 1993; Kyrkanides et al., 1999; Mizumatsu et al., 2003; Moravan et al., 2011). Additionally, increase in CD68+ cells have been shown following a total dose of 26 Gy (Dey et al., 2020). Further