# Adverse Outcome Pathway on Deposition of Energy Leading to Learning and Memory Impairment

Ahmad Sleiman, Kathleen Miller, Danicia Flores, Jacqueline Kuan, Kaitlyn

Altwasser, Benjamin Smith, Hailey Adams, Tatiana Kozbenko, Robyn

Hocking, Carole Yauk, et al.

► To cite this version:

Ahmad Sleiman, Kathleen Miller, Danicia Flores, Jacqueline Kuan, Kaitlyn Altwasser, et al. "Adverse Outcome Pathway on Deposition of Energy Leading to Learning and Memory Impairment. OECD Series on Adverse Outcome Pathways No. 42, OCDE (Organisation de coopération et de développement économiques). 2025." [PDF] [https://asnr.hal.science/hal-05204389v1](https://asnr.hal.science/hal-05204389v1)

HAL Id: hal-05204389

Submitted on 8 Aug 2025

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>
<figure><img src="image_2.png" /></figure>

<figure><img src="image_3.png" /></figure>

OECD Series on Adverse Outcome Pathways No. 42

# Adverse Outcome Pathway on Deposition of Energy Leading to Learning and Memory Impairment

Ahmad Sleiman,
Kathleen Miller,
Danicia Flores,
Jacqueline Kuan,
Kaitlyn Altwasser,
Benjamin Smith,
Hailey Adams,
Tatiana Kozbenko,
Robyn Hocking,
Carole Yauk,
Ruth Wilkins,
Vinita Chauhan

https://dx.doi.org/10.1787/16c49ced-en
Adverse Outcome Pathway on Deposition of Energy
Leading to Learning and Memory Impairment

Series on Adverse Outcome Pathways No. 42

AOP No. 483 in the AOP-Wiki platform
## Foreword

This Adverse Outcome Pathway (AOP) on Deposition of Energy Leading to Learning and Memory Impairment, has been developed under the auspices of the OECD AOP Development Programme, overseen by the advisory group on Emerging Science in Chemicals Assessment (ESCA), an advisory group under the Working Party of the National Coordinators for the Test Guidelines Programme (WNT) and the Working Party on Hazard Assessment (WPHA) of the Chemicals and Biotechnology Committee.

The scientific review was organised by the Environmental and Molecular Mutagenesis (EMM) Journal following the principles established in the Guidance Document for the scientific review of Adverse Outcome Pathways. The AOP was subsequently submitted to ESCA who confirmed the alignment of the scientific review with the Guidance Document. The AOP was approved by the NEA Committee of Radiological Protection and Public Health (CRPPH) by written procedure on 7 March 2025.

Through approval of this AOP, the CRPPH expresses confidence in the scientific review process that the AOP has undergone and accepts the recommendation of the EMM that the AOP be disseminated publicly. It does not necessarily indicate that the AOP is now considered a tool for direct regulatory application.

The outcome of the scientific review is publicly available in the AOP-Wiki under AOP483 - Scientific review.
**Authors:**

Ahmad Sleiman¹, Kathleen Miller², Danicia Flores³, Jaqueline Kuan³, Kaitlyn Altwasser³, Benjamin Smith³, Hailey Adams⁴, Tatiana Kozbenko³, Robyn Hocking³, Carole Yauk⁵, Ruth Wilkins³, Vinita Chauhan³

(1) Institut de Radioprotection et de Sûreté Nucléaire, St. Paul Lez Durance, Provence, France

(2) Department of Health and Exercise Science, Morrison College Family of Health, University of St. Thomas, Saint Paul, Minnesota, USA

(3) Consumer and Clinical Radiation Protection Bureau, Environmental and Radiation Health Sciences Directorate, Health Canada, Ottawa, Ontario, Canada

(4) Radiation Protection Bureau, Environmental and Radiation Health Sciences Directorate, Health Canada, Ottawa, Ontario, Canada

(5) Department of Biology, University of Ottawa, Ottawa, Ontario, Canada

**Consultants:**

Scott Wood¹, Janice Huff², Christelle-Adam Guillermin³, Nobuyuki Hamada⁴

(1) NASA Johnson Space Center, Houston, Texas, USA

(2) NASA Langley Research Center, Hampton, Virginia, USA

(3) Institut de Radioprotection et de Sûreté Nucléaire, St. Paul Lez Durance, Provence, France

(4) Biology and Environmental Chemistry Division, Sustainable System Research Laboratory, Central Research Institute of Electric Power Industry (CRIEPI), Chiba, Japan

**Point of Contact:**

Vinita Chauhan [email point of contact](mailto:vinita.chauhan@cepi.ird.fr)

© OECD 2025

<figure><img src="image_4.png" /></figure>

Attribution 4.0 International (CC BY 4.0)

This work is made available under the Creative Commons Attribution 4.0 International licence. By using this work, you accept to be bound by the terms of this licence
(https://creativecommons.org/licenses/by/4.0/).

**Attribution** - you must cite the work.

**Translations** - you must cite the original work, identify changes to the original and add the following text: *In the event of any discrepancy between the original work and the translation, only the text of original work should be considered valid.*

**Adaptations** - you must cite the original work and add the following text: *This is an adaptation of an original work by the OECD. The opinions expressed and arguments employed in this adaptation should not be reported as representing the official views of the OECD or of its Member countries.*

**Third-party material** - the licence does not apply to third-party material in the work. If using such material, you are responsible for obtaining permission from the third party and for any claims of infringement.

You must not use the OECD logo, visual identity or cover image without express permission or suggest the OECD endorses your use of the work.

Any dispute arising under this licence shall be settled by arbitration in accordance with the Permanent Court of Arbitration (PCA) Arbitration Rules 2012. The seat of arbitration shall be Paris (France). The number of arbitrators shall be one.
Abstract

The central nervous system (CNS) is the main processing center of the body and is comprised of the brain and spinal cord. Some diseases of the CNS, including neurodegenerative diseases such as cognitive decline and dementia, are associated with advancing age. However, unwanted exposure to stressors may promote or accelerate these disorders. For example, ionizing radiation is an exposure which can disrupt cellular homeostasis in the brain. Herein, an adverse outcome pathway (AOP) is described from the molecular initiating event (MIE) of deposition of energy to the adverse outcome (AO) of learning and memory impairment. This AOP uses well-understood mechanistic events that encompass oxidative stress, DNA damage, tissue resident cell activation, altered stress response signaling, neuroinflammation, and their interactions, leading to eventual abnormal neural remodeling. The empirical evidence to support this AOP is primarily derived from studies that utilize ionizing radiation stressors relevant to space travel and radiotherapy treatments. Following deposition of energy (MIE, KE#1686), the adjacent key events are oxidative stress (KE#1392), tissue resident cell activation (KE#1492) and increased DNA strand breaks (KE#1635). Uncontrolled radical production within the cell has an adjacent connection with increased DNA strand breaks (KE#1635), altered stress response signaling (KE#2244) and tissue resident cell activation (KE#1492). Tissue resident cell activation has an adjacent connection to increased proinflammatory mediators (KE#1493). Prolonged neuroinflammation and altered stress response signaling have adjacent connections with abnormal neural remodeling (KE#2098) and subsequently learning and memory impairment (AO, KE#341). The AOP also includes multiple non-adjacent connections between key events. The overall weight of evidence for this AOP is moderate. Despite multiple knowledge gaps that are present, the evidence demonstrates a high-level of biological plausibility. The quantitative understanding is low as there is high uncertainty in the quantitative predictions between the KEs. This AOP has wide applicability and is particularly relevant to exposures from long-duration space flight and medical exposures using radiation therapy.
Table of contents

<table><tr><td>Adverse Outcome Pathway on Deposition of Energy Leading to Learning and Memory Impairment</td><td>1</td></tr><tr><td>Foreword</td><td>2</td></tr><tr><td>Abstract</td><td>4</td></tr><tr><td>Background</td><td>7</td></tr><tr><td>Graphical representation</td><td>9</td></tr><tr><td>Summary of the AOP</td><td>10</td></tr><tr><td>Events</td><td>10</td></tr><tr><td>Key Event Relationships</td><td>10</td></tr><tr><td>Overall Assessment of the AOP</td><td>12</td></tr><tr><td>Domain of Applicability</td><td>16</td></tr><tr><td>Essentiality of the Key Events</td><td>17</td></tr><tr><td>Weight of Evidence Summary</td><td>20</td></tr><tr><td>Quantitative Understanding</td><td>25</td></tr><tr><td>Considerations for Potential Applications of the AOP</td><td>27</td></tr><tr><td>Appendix 1 – List of MIE, KEs and AO</td><td>38</td></tr><tr><td>List of MIEs in this AOP</td><td>38</td></tr><tr><td>Event: 1686: Deposition of Energy</td><td>38</td></tr><tr><td>List of Key Events in the AOP</td><td>42</td></tr><tr><td>Event: 1392: Oxidative Stress</td><td>42</td></tr><tr><td>Event: 2244: Altered Stress Response Signaling</td><td>51</td></tr><tr><td>Event: 1492: Tissue resident cell activation</td><td>59</td></tr><tr><td>Event: 2097: Increase, Pro-Inflammatory Mediators</td><td>69</td></tr><tr><td>Event: 2098: Increase, Abnormal Neural Remodeling</td><td>75</td></tr><tr><td>Event: 1635: Increase, DNA strand breaks</td><td>80</td></tr><tr><td>List of Adverse Outcomes in this AOP</td><td>87</td></tr><tr><td>Event: 341: Impairment, Learning and memory</td><td>87</td></tr><tr><td>Appendix 2 – List of Key Event Relationships in the AOP</td><td>94</td></tr><tr><td>List of Adjacent Key Event Relationships</td><td>94</td></tr><tr><td>Relationship: 2769: Energy Deposition leads to Oxidative Stress</td><td>95</td></tr><tr><td>Relationship: 2832: Energy Deposition leads to Tissue resident cell activation</td><td>116</td></tr><tr><td>Relationship: 3316: Oxidative Stress leads to Altered Stress Response Signaling</td><td>127</td></tr><tr><td>Relationship: 2833: Oxidative Stress leads to Tissue resident cell activation</td><td>140</td></tr><tr><td>Relationship: 2834: Tissue resident cell activation leads to Increase, Pro-Inflammatory Mediators</td><td>148</td></tr><tr><td>Relationship: 2835: Increase, Pro-Inflammatory Mediators leads to Abnormal Neural Remodeling</td><td>159</td></tr><tr><td>Relationship: 2836: Abnormal Neural Remodeling leads to Impairment, Learning and memory</td><td>167</td></tr><tr><td>Relationship: 3321: Altered Stress Response Signaling leads to Abnormal Neural Remodeling</td><td>178</td></tr></table>
<table><tr><td>Relationship: 2841: Increase, DNA strand breaks leads to Abnormal Neural Remodeling</td><td>190</td></tr><tr><td>Relationship: 2811: Oxidative Stress leads to Increase, DNA strand breaks</td><td>197</td></tr><tr><td>Relationship: 1977: Energy Deposition leads to Increase, DNA strand breaks</td><td>206</td></tr><tr><td>Relationship: 3315: Increase, DNA strand breaks leads to Altered Stress Response Signaling</td><td>224</td></tr><tr><td>List of Non-Adjacent Key Event Relationships</td><td>237</td></tr><tr><td>Relationship: 2837 – Energy Deposition leads to Abnormal Neural Remodeling</td><td>237</td></tr><tr><td>Relationship: 2838 – Energy Deposition leads to Impairment, Learning and memory</td><td>247</td></tr><tr><td>Relationship: 2839 - Increase, Pro-Inflammatory Mediators leads to Impairment, Learning and memory</td><td>262</td></tr></table>
# Background

## AOP Development Strategy - Context

Understanding the impact of ionizing radiation on CNS is essential as there are many possibilities for humans to be exposed to ionizing radiation including from medical procedures, accidental or wartime exposures, and occupational exposures, such as industrial radiographers or astronaut crewmembers. Various studies have reported cognitive deficits after high-doses of radiation exposure from radiotherapy, though there is a reported individual variability in human cohorts (Greene-Schloesser et al., 2012; Katsura et al., 2021; Turnquist et al., 2020). In preclinical animal models, studies suggest that even low-to-moderate doses of ionizing radiation from heavy ions can cause structural and functional impairments to the CNS including reductions in neurogenesis, changes in dendritic properties, activation of glial cells, leading to neural remodeling (Cekanaviciute et al., 2018; Kiffer et al., 2019b). However, how key changes in structural and functional properties of the CNS from ionizing radiation exposure are related to changes in cognitive function have yet to be delineated. Furthermore, preclinical studies also suggest that ionizing radiation may impact two major cognitive processes: learning and memory. Learning is the ability to create new associative or non-associative relationships and memory is the ability to recall sensory, short-term or long-term information (Desai et al., 2022, Kiffer et al., 2019b). Both learning and memory involve multiple brain areas including the hippocampal region, as well as the amygdala, the prefrontal cortex and the basal ganglia (Cucinotta et al., 2014; Desai et al., 2022; NCRP Commentary, 2016). The link between learning and memory is complexly intertwined, as their processes share mechanisms such as changes in neuronal plasticity, alternations in neurotransmitter release and reuptake and alterations in gray and white matter structure (Toricelli et al., 2021). Thus far, direct pathways linking ionizing radiation to key cellular and molecular events leading to an AO of impaired learning and memory have not been established.

This AOP can serve as a foundational pathway for expansion to other cognitive disorders and CNS diseases from an MIE of deposition of energy. The strength of this AOP is in its rigorous and systematic collection and evaluation of evidence with moderate to high levels of qualitative evidence supporting the KERs.

## AOP Development Strategy - Strategy

The development strategy for this AOP has been described by Kozbenko et al., 2022. In brief, a structured literature search was conducted that included screening and prioritization of the references. Initial searches involved study inclusion through key words relevant to the MIE and AO, followed by focused searches for each of the KEs and KERs. Studies at all levels of biological organization, regardless of the species, life stage, or sex, were considered. References were excluded using a Population, Exposure, Outcome, Endpoint (PEOE) statement. Studies were included if they met definitions of a population (human, mouse, rat, etc.), exposure (i.e., radiation), and/or mention of one of the key events (KEs) or outcome (AO) of interest. Studies were excluded if they lacked full text, and/or were not a peer-reviewed manuscript (i.e., thesis/dissertations, presentations, posters or conference abstracts). Non-English studies were included provided the data could be identified within the abstract. Relevant studies were identified in the context of the modified Bradford Hill criteria, which contain biological plausibility, temporal-, dose-, incidence-concordance, and essentiality.

The research strategy for this AOP has been described by Kozbenko et al., 2022. In brief, all data went through a systematic screening process for its collection and inclusion into the AOP. This included structured literature searches as well as additional screenings and prioritization of the references. Initial searches included key words for the MIE and AO, followed by focused searches for each of the keywords involved in the KEs and KERs. Studies at all levels of biological organization, regardless of
the species, life stage, or sex, were considered. References were further screened using a Population, Exposure, Endpoint, and Outcome (PEOE) statement. Studies were excluded if they did not contain definitions of a population (human, mouse, rat, etc.), exposure (i.e., ionizing radiation), and/or mention of one of the key events (KEs) or outcome (AO) of interest. Studies were also excluded if they lacked full text, and/or were not a peer-reviewed manuscript (i.e., thesis/dissertations, presentations, posters or conference abstracts). Non-English studies were included provided the data could be identified within the abstract. Relevant studies were identified in the context of the modified Bradford Hill criteria, which contain biological plausibility, temporal-, dose-, incidence-concordance, and essentiality.

Pre-screening was completed using SWIFT Review (http://www.sciome.com/swift-review/version 1.43). In SWIFT, software generated tags were created based on study abstracts that helped group references and create lists to aid in prioritizing relevant studies. Reviewers could include or exclude references based on the tags and abstracts. DistillerSR (Evidence Partners. www.evidencepartners.com/products/distillersr-systematic-reviewsoftware released 12.06.2020 version 2.34.0R) was then used in a three-level screening exercise: Title and Abstract (Level 1), Full-Text (Level 2), and Data Extraction (Level 3). Screeners used the PEOE statement to assess relevance for inclusion or exclusion. At the data extraction level, screeners extracted data supporting the Bradford Hill criteria, taxonomic applicability, and life-stage applicability. A final screening of all studies was done manually to ensure data was relevant to the KERs in the pathway in the context of the Bradford Hill criteria. Note that not all types of stressors and associated exposure parameters support each KER. Since KERs are independent units from the rest of the AOP and can support multiple AOs, some macromolecular KERs may include studies from cell types (e.g., lens cells) and stressors (e.g., UV) not directly relevant to the AO.
<figure><img src="image_5.png" /><figcaption>**Figure 1:** Flow chart of AOP 483 from deposition of energy to impaired learning and memory. The molecular initiating event (MIE) is the first interaction between a stressor and a biomolecule within an organism. Subsequent key events (KEs) leading to the adverse outcome (AO) were identified. Both adjacent key event relationships (KERs) and non-adjacent KERs are included in this pathway. Adjacent KERs demonstrate the causal relationship between two KEs. Non-adjacent KERs can be used to support the weight of evidence (WOE) of the whole AOP by bypassing KEs with less evidence.</figcaption></figure>
# Summary of the AOP

## Events

### Molecular Initiating Events (MIE), Key Events (KE), Adverse Outcomes (AO)

<table><thead><tr><td>Sequence</td><td>Type</td><td>Event ID</td><td>Title</td><td>Short name</td></tr></thead><tbody><tr><td>1</td><td>MIE</td><td>1686</td><td>Deposition of Energy</td><td>Energy Deposition</td></tr><tr><td>2</td><td>KE</td><td>1392</td><td>Oxidative Stress</td><td>Oxidative Stress</td></tr><tr><td>3</td><td>KE</td><td>2244</td><td>Altered Stress Response Signaling</td><td>Altered Stress Response Signaling</td></tr><tr><td>4</td><td>KE</td><td>1492</td><td>Tissue resident cell activation</td><td>Tissue resident cell activation</td></tr><tr><td>5</td><td>KE</td><td>2097</td><td>Increase, Pro-Inflammatory Mediators</td><td>Increase, Pro-Inflammatory Mediators</td></tr><tr><td>6</td><td>KE</td><td>2098</td><td>Increase, Abnormal Neural Remodeling</td><td>Abnormal Neural Remodeling</td></tr><tr><td>7</td><td>KE</td><td>1635</td><td>Increase, DNA strand breaks</td><td>Increase, DNA strand breaks</td></tr><tr><td></td><td>AO</td><td>341</td><td>Impairment, Learning and memory</td><td>Impairment, Learning and memory</td></tr></tbody></table>

## Key Event Relationships

<table><thead><tr><td>Upstream Event</td><td>Relationship Type</td><td>Downstream Event</td><td>Evidence</td><td>Quantitative Understanding</td></tr></thead><tbody><tr><td>Deposition of Energy</td><td>adjacent</td><td>Oxidative Stress</td><td>High</td><td>Moderate</td></tr><tr><td>Deposition of Energy</td><td>adjacent</td><td>Tissue resident cell activation</td><td>Moderate</td><td>Moderate</td></tr><tr><td>Oxidative Stress</td><td>adjacent</td><td>Altered Stress Response Signaling</td><td>High</td><td>Low</td></tr><tr><td>Oxidative Stress</td><td>adjacent</td><td>Tissue resident cell activation</td><td>Moderate</td><td>Low</td></tr><tr><td>Tissue resident cell activation</td><td>adjacent</td><td>Increase, Pro-Inflammatory Mediators</td><td>Moderate</td><td>Low</td></tr><tr><td>Increase, Pro-Inflammatory Mediators</td><td>adjacent</td><td>Abnormal Neural Remodeling</td><td>Moderate</td><td>Low</td></tr><tr><td>Abnormal Neural Remodeling</td><td>adjacent</td><td>Impairment, Learning and Memory</td><td>Moderate</td><td>Low</td></tr><tr><td>Altered Stress Response Signaling</td><td>adjacent</td><td>Abnormal Neural Remodeling</td><td>Moderate</td><td>Low</td></tr><tr><td>Increase, DNA strand breaks</td><td>adjacent</td><td>Abnormal Neural Remodeling</td><td>Moderate</td><td>Low</td></tr><tr><td>Oxidative Stress</td><td>adjacent</td><td>Increase, DNA strand breaks</td><td>Moderate</td><td>Moderate</td></tr><tr><td>Energy Deposition</td><td>adjacent</td><td>Increase, DNA strand breaks</td><td>High</td><td>High</td></tr><tr><td>Increase, DNA strand breaks</td><td>adjacent</td><td>Altered Stress Response Signaling</td><td>Moderate</td><td>Low</td></tr></tbody></table>
<table><tr><td><a href="">Deposition of Energy</a></td><td>non-adjacent</td><td>Abnormal Neural Remodeling</td><td>Moderate</td><td>Low</td></tr><tr><td><a href="">Deposition of Energy</a></td><td>non-adjacent</td><td>Impairment, Learning and Memory</td><td>Moderate</td><td>Low</td></tr><tr><td><a href="">Increase, Pro-Inflammatory<br>Mediators</a></td><td>non-adjacent</td><td>Impairment, Learning and Memory</td><td>Moderate</td><td>Low</td></tr></table>

Prototypical Stressors

Name

Ionizing Radiation
# Overall Assessment of the AOP

This AOP was derived from data that investigates the CNS of humans, animals and cellular models following predominantly exposure to ionizing radiation. The AOP is qualitative in nature and not intended to be specific to any particular exposure parameter. The exposure parameters informing the AOP include doses of moderate-high (>1 Gy) and both high and low-LET radiation qualities. However, the extent to which cognitive deficits exist at low-to-moderate ionizing radiation doses (0.1 Gy - 1 Gy) across all the KEs in the AOP remains incompletely understood as limited empirical evidence was retrieved to support this understanding. Since KERs are independent units from the rest of the AOP and can support multiple AOs, some macromolecular KERs may include studies from cell types (e.g., lens cells) and stressors (e.g., UV) not relevant to the AO.

The goal of this AOP is to identify the qualitative biological perturbations of the MIE of deposition of energy through the molecular, cellular and tissue-level KEs that lead to abnormal neural remodeling and the AO of impaired learning and memory. While neural remodeling is a natural process that allows the brain to continue to adapt, long-term exposure to stressors such as the space environment (e.g., microgravity and space radiation) may lead to chronic inflammation and possible changes in structure and function of neural cells ultimately resulting in cognitive deficits. The progression of KEs along the proposed hypothetical AOP is driven by persistent oxidative stress and chronic release of pro-inflammatory markers, creating an environment of neuroinflammation. The KEs chosen for this AOP had adequate empirical evidence, however, other KEs may be added later to incorporate new mechanisms and AOs into its broader network. Since the AOP is stressor agnostic, this pathway is applicable to impaired learning and memory in the context of multiple stressors of deposition of energy including ionizing radiation exposure from space travel and radiotherapy.

## Biological Plausibility

The overall biological plausibility in this AOP is high. The KERs in the AOP have either moderate or high evidence for the mechanistic understanding of the relationships between the upstream and downstream KEs. The KEs are well-studied, and an understanding of the structural and functional linkages are well-established.

This AOP is initiated with deposition of energy. Deposition of energy can damage DNA via direct mechanisms, by which the electrons ionize DNA molecules themselves, or via indirect mechanisms, by which the ionization of water produces hydroxyl radicals that can damage DNA bases causing DNA strand breaks (Nikjoo et al., 2016; Wilkinson et al., 2023) or directly upregulating enzymes involved in reactive oxygen and nitrogen species (RONS) production (i.e., catalase) (de Jager, Cockrell and Du Plessis, 2017). Both reactive oxygen species (ROS) as well as reactive nitrogen species (RNS) (Ahmadi et al., 2022; Karimi et al., 2017; Slezak et al., 2015; Tahimic & Globus, 2017; Wang et al., 2019a) may be produced after deposition of energy. If RONS cannot be eliminated quickly and efficiently by the cell's defense system, oxidative stress ensues (Balasubramanian, 2000; Ganea & Harding, 2006; Karimi et al., 2017). Within the brain, oxidative stress can lead to the activation of microglial cells (Fishman et al., 2009; Schnegg et al., 2012; Zhang et al., 2017) and astrocytes (Daverey & Agrawal, 2016; Wang et al., 2017). These cells then release pro-inflammatory mediators and initiate antioxidant defenses (Lee, Cha & Lee, 2021; Simpson & Oliver, 2020). However, if the antioxidant capacity is overwhelmed, chronic inflammation may result.

Oxidative stress can also lead to altered stress response signaling. Directly, ROS causes oxidation of amino acid residues resulting in conformational changes, protein expansion, and protein degradation. This can cause changes in the activity and level of signaling proteins (Ping et al., 2020; Li et al., 2013).
Oxidation of key functional amino acids can also alter the activity of signaling proteins, resulting in downstream alterations in signaling pathways (Ping et al., 2020; Schmidt-Ullrich et al., 2000; Valerie et al., 2007; Lehtinen & Bonni, 2006; Ramalingam & Kim, 2012). DNA strand breaks from oxidative damage can activate DNA damage response signaling and modify the expression of other signaling proteins (Ping et al., 2020; Nagane et al., 2021; Schmidt-Ullrich et al., 2000; Valerie et al., 2007).

Both increased pro-inflammatory mediators and altered stress response signaling can lead to abnormal neural remodeling. Various pro-inflammatory cytokines can affect neural activity/function, the most common being IL-1β, TNF-α, IL-6 and IFN-γ. During an inflammatory response, these cytokines act on different receptors to initiate several signaling pathways to induce neuronal degeneration, apoptosis or to propagate further pro-inflammatory responses (Mousa & Bakhiet, 2013; Prieto & Cotman, 2018). These signaling pathways include, but are not limited to PI3K/Akt pathways, MAPK pathways, senescence signaling, and apoptosis pathways. The PI3K/Akt and MAPK pathways are involved in many processes in neurons, including cell survival, morphology, proliferation, differentiation, and synaptic activity (Davis and Laroche, 2006; Falcicchia et al., 2020; Long et al., 2021; Mazzucchelli and Brambilla, 2000; Mielke and Herdegen, 2000; Nebreda and Porras, 2000; Rai et al., 2019; Rodgers and Theibert, 2002; Sherrin, Blank, and Todorovic, 2011). The apoptosis pathway decreases cell number, while senescence signaling can influence the regenerative potential of the cell and therefore, neurogenesis (Betlazar et al., 2016; McHugh and Gil, 2018; Mielke and Herdegen, 2000). Disruptions to components of these pathways will lead to abnormal neural remodeling, which includes alterations in both morphological properties and functional properties of the neurons (Betlazar et al., 2016; Davis and Laroche, 2006; Mazzucchelli and Brambilla, 2000; Nebreda and Porras, 2000). However, the biological changes that follow perturbation of these pathways is not understood in every context and cell type, making the biological plausibility for this relationship moderate (Nebreda and Porras, 2000). Decreased morphological properties of neurons, including reductions in dendritic complexities and spine densities, as well as altered functional properties of neurons including altered synaptic signaling and neurogenesis, has been associated with learning and memory impairment (Bálentová & Adamkov, 2020; Hladik & Tapio, 2016; Monje & Palmer, 2003; Romanella et al., 2020; Tomé et al., 2015).

## Empirical Support (Temporal, Dose, and Incidence Concordance)

This AOP demonstrates moderate empirical evidence to support the modified Bradford Hill criteria. Overall, many studies demonstrated that upstream KEs occurred at lower or the same doses and at earlier or the same times as downstream KEs. There were some inconsistencies where the KEs were only measured at one dose or time. The evidence collected was gathered from various studies using in vitro and in vivo rat, mice, rabbit, squirrel, bovine and human models. Various stressors were applied, including UV, UVB, UVA, gamma ray, X-ray, protons, alpha particle, neutron, and heavy ion irradiation.

Regarding time concordance, deposition of energy occurs immediately following irradiation, and downstream events will always occur at a later time-point. DNA damage occurs within nanoseconds of deposition of energy with DNA strand breaks measured from seconds to minutes later and altered signaling measured minutes to days later (Acharya et al., 2010; Antonelli et al., 2015; Mosconi et al., 2011; Rogakou et al., 1999; Rothkamm and Lo, 2003; Sabirzhanov et al., 2020; Zhang et al., 2017). Rapid increases in ROS (Limoli et al., 2004; Giedzinski et al., 2005; Suman et al., 2013) and activation of microglia and astrocytes have been observed within hours of irradiation and can persist for 12 months (Kyrkanides et al., 1999; Hwang et al., 2006; Suman et al., 2013). For tissue resident cell activation and increase in pro-inflammatory mediators, studies generally show that these events occur at a similar time frame (Parihar et al., 2018; Liu et al., 2010; Dong et al., 2015; Lee et al., 2010; Zhou et al., 2017). The alteration of signaling pathways is a molecular-level KE like oxidative stress, and both can occur concurrently (Xu et al., 2019), although increased ROS levels can be initiated significantly before altered stress response signaling (Suman et al., 2013). Abnormal neural remodeling has been observed
at various time points from hours to months after exposure to a stressor, and its upstream KEs (altered signaling and increased pro-inflammatory mediators) generally appear earlier (Kanzawa et al., 2006; Limoli et al., 2004; Pius-Sadowska et al., 2016) or at similar times, respectively (Zonis et al., 2015; Wong et al., 2004, Green et al., 2012; Ryan et al., 2013; Vallieres et al., 2002). In response to irradiation, impaired learning and memory is typically observed at similar time-points as markers of abnormal neural remodeling due to the timing of measurements (Raber et al., 2004; Parihar et al., 2016; Madsen et al., 2003; Winocur et al., 2006; Rola et al., 2004).

Regarding dose concordance, multiple studies also demonstrate that the upstream KEs occur at lower or the same doses as downstream KEs as energy is deposited immediately at any dose of radiation. Some studies report a linear-dose-dependent increase in DNA strand breaks for a large range of doses (Antonelli et al., 2015; Hamada et al., 2006; Rübe et al., 2008). In addition, neural precursor cells irradiated with protons at 1, 2, 5 and 10 Gy showed a dose-dependent increase in ROS levels (Giedzinski et al., 2005). In another study, activation of microglia and astrocytes were seen at doses as low as 5 cGy that persisted to 30 cGy (Parihar et al., 2018). However, dose concordance is not consistently observed across studies, which can be attributed to differences in experimental design. Some studies also only measured the KEs at one dose, which presented further inconsistencies.

Few studies showed incidence concordance where the upstream KE demonstrated a greater change than the downstream KE following a stressor. Not all KERs displayed an incident-concordant relationship, but for those that did, only a small proportion of the empirical evidence supported this relationship. For example, mice exposed to 2 Gy of gamma irradiation showed increases of pro-apoptotic markers p53 and BAX by 8.4- and 2.3-fold, respectively. A 0.6-fold decrease in Bcl-2 (anti-apoptotic marker) was also observed, and gamma rays cause a decrease in cortical thickness by 0.9-fold (Suman et al., 2013).

## Uncertainties, Inconsistencies, and Data Gaps

There are a few inconsistencies in this AOP. Some studies show sex-specific changes in the KEs. For example, two studies reported that tissue resident cell activation was not affected in female mice after 0.3 and 0.5 Gy of radiation (Krukowski et al., 2018a; Parihar et al., 2020) while a separate study showed that only female mice had activated cells after 2 Gy (Raber et al., 2019). Another study reported a greater radiation-induced reduction in neurogenesis in male mice compared with female mice (Kalm et al., 2013). More research is necessary to identify if these results are sex-specific or due to other modulating factors.

There have been some inconsistencies reported in the KER Deposition of Energy (KE#1686) to Increase DNA Strand Breaks (KE#1635). For example, dose-rates and radiation quality may influence dose-response relationships (Brooks et al., 2016, Sutherland et al., 2000; Nikjoo et al., 2001; Jorge et al., 2012). More research is necessary to understand the impact low-doses of ionizing radiation exposure on DNA damage as some studies report low-dose exposures may invoke protection against spontaneous genomic damage (as reviewed by ICRP (2007) and UNSCEAR (2008)).

Anatomical location of change in the KEs may impact its response. For example, in response to ionizing radiation, changes occurred in hippocampal dendritic spines CA1 subregion of hippocampus but not in the dorsal dentate gyrus (Kiffer et al., 2019a).

Changes in KEs and the AO may be dose and stressor specific when assessed using animal models. For example, cue feared conditioning, a measure of learning and memory had different responses in mice at 0.2 Gy vs. 1 Gy of 28Si exposure (Whoolery et al., 2017). Also in mice, object memory was impaired after 0.1 or 0.25 Gy 16O exposure and social novelty learning was impaired after 0.25 Gy 16O exposure, but neither dose impaired short-term spatial memory (Kiffer et al., 2019a).
Changes in signaling pathways may provide inconsistent outcomes related to abnormal neural
remodeling. For example, the p38 pathway is involved in many, often opposing, biological processes
(Nebreda and Porras, 2000). Furthermore, the MAPK pathways can exhibit varied responses after
exposure to oxidative stress (Azimzadeh et al., 2015).

Many studies do not report direct measures of oxidative stress. As free radicals are quickly scavenged, the quantitative understanding of this relationship can be inconsistent, due to varied response of antioxidant enzymes across experimental conditions and time measurements. This has led to some inconsistencies within the KERs. For example, in contrast to other studies demonstrating an increase in oxidative stress following deposition of energy, neutron radiation decreased malondialdehyde, a product of oxidative stress (Chen et al., 2021).

The scope of several KEs in this AOP is broad and this reflects a level of uncertainty in exact endpoints that specifically link to the AO, therefore several KEs (e.g. abnormal neural remodeling and signaling pathways) are defined by multiple structural and functional measurements.

Inflammatory markers exhibit a dual role, with the capacity for both anti-inflammatory and pro-inflammatory actions. Variables such as concentration, timing, and the specific microenvironment play pivotal roles in determining whether a mediator acts in a pro-inflammatory or anti-inflammatory manner (Lawrence & Gilroy, 2007; Nathan & Ding, 2010).

The use of different assays to assess the KEs may lead to variations in the quantitative understanding of observations across studies.

Limited data is available to support an understanding of oxidative stress and pro-inflammatory
mediators at low doses < 0.1 Gy.

Finally, many of the KERs do not include studies in humans. More research could be needed to observe these relationships in human models.

There were multiple challenges present in the development of this AOP which identified numerous gaps in the data. The majority of the evidence for this AOP is extracted from preclinical animal and cellular models. Therefore, the low availability of human studies presents a challenge as translation of the animal and cellular models to humans is difficult due to differences in physiology, methods and measurements. In addition, although both age and sex are listed as modulating factors, there is more research necessary to elucidate the interaction between age and sex on the KEs, particularly how these factors may modulate the causal connectivity of the relationships and the AO. Direct comparisons between studies were also difficult due to differences in model, radiation quality, dose, dose rate and endpoint which led to some inconsistencies. Many studies reported limited dose ranges or time-points and often measured a single KE, limiting evidence for direct KERs. The current AOP has low quantitative evidence supporting the KERs, however, this AOP can be expanded with experiments that further exemplify the level of dose- and time- concordance across multiple endpoints. This will improve the quantitative understanding of the relationships which can then support the development of risk models and tools for mitigating risk.
This AOP is relevant to vertebrates, such as humans, mice, rats. The taxonomic evidence supporting the AOP comes from the use of human (Homo sapiens), human-derived cell line, beagle dog (Canis lupus familiaris), rat (Rattus orvegicus), and mouse (Mus musculus) studies. Across all species, most available data was derived from adult and adolescent models with a moderate to high level of evidence compared to less available data from preadolescent models. Many of the KEs demonstrated moderate to high evidence for males and low evidence for females. In multiple KEs, sex was unspecified.

Life Stage Applicability

<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>

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>High</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><tr><td>dog</td><td>Canis lupus familiaris</td><td>Low</td><td>NCBI</td></tr><tr><td>pigs</td><td>Sus scrofa</td><td>Low</td><td>NCBI</td></tr><tr><td>cow</td><td>Bos taurus</td><td>Low</td><td>NCBI</td></tr></tbody></table>

Sex Applicability

<table><thead><tr><td>Sex</td><td>Evidence</td></tr></thead><tbody><tr><td>Unspecific</td><td>High</td></tr><tr><td>Male</td><td>Moderate</td></tr><tr><td>Female</td><td>Low</td></tr></tbody></table>
## Essentiality of the Key Events

Overall, the KEs in this AOP demonstrate moderate essentiality. Essentiality is demonstrated when upstream KEs are blocked or inhibited eliciting a change in the downstream KE.

### Essentiality of the Deposition of Energy (MIE, KE#1686)

* Deposition of energy is difficult to test for essentiality as deposition of energy is a physical stressor and cannot be blocked/decreased using chemicals. Since deposited energy initiates events immediately, the removal of deposited energy, a physical stressor, also supports the essentiality of the key event. Studies that do not deposit energy are observed to have no downstream effects.

### Essentiality of Oxidative Stress (KE#1392)

* The effect of antioxidants on altered stress response signaling (KE#2244)

* Antioxidants including Melandrii Herba extract, N-acetyl-L-cysteine (NAC), gallocatechin gallate/epigallocatechin-3-gallate, Cornus officinalis (CC) and fermented CC (FCC), L-165041, fucoxanthin, and edaravone were shown to decrease phosphorylation of MAPKs such as ERK1/2, JNK1/2 and p38 after exposure to radiation, H2O2 or lipopolysaccharide (LPS) (Lee et al., 2017; Deng et al., 2012; Park et al., 2021; Tian et al., 2020; Schnegg et al., 2012; Zhao et al., 2017; Zhao et al., 2013; El-Missiry et al., 2018).

* The effects of antioxidants on tissue resident cell activation (KE#1492)

* Antioxidants including Kukoamine A (KuA) and curcumin were found to reduce levels of microglia and astrocyte activation (Zhang et al. 2017; Daverey & Agrawal, 2016; Wang et al., 2017).

* The effect of knocking out a ROS-producing enzyme

* A knockout model of mitochondrial superoxide dismutase 2 (SOD2) resulted in an increase in reactivity of microglial cells (Fishman et. al 2009).

### Essentiality of Increase, DNA Strand Breaks (KE#1635)

* The effects of blocking DNA strand breaks on altered stress response signaling (KE#2244)

* Treatment with mesenchymal stem cell-conditioned medium (MSC-CM) reduced γ-H2AX, decreased the levels of p53, Bax, cleaved caspase 3 and increased the levels of Bcl-2 in HT22 cells irradiated with 10 Gy of X-rays (Huang et al., 2021).

* The inhibition of microRNA (miR)-711 decreased levels of DNA damage markers, p-ATM, p-ATR and γ-H2AX, and decreased signaling molecules including p-p53, p21 and cleaved caspase 3 (Sabirzhanov et al., 2020).

* The effects of blocking DNA strand breaks on abnormal neural remodeling (KE#2098)

* Treatment of HT22 hippocampal neuronal cells with minocycline inhibited the expression of γ-H2AX and the p-ATM/ATM ratio as well as reduced apoptosis following X-ray exposure (Zhang et al., 2017). Similarly, MSC-CM reduced the expression of γ-H2AX and reduced apoptosis, reversing the changes induced by X-ray radiation (Huang et al., 2021).

* Lithium chloride was also shown to reduce γ-H2AX levels and increase proliferation in neural stem cells irradiated with 60Co gamma rays (Zanni et al., 2015).

### Essentiality of Altered Stress Response Signaling (KE#2244)

* The effects of modulating cell signaling on abnormal neural remodeling (KE#2098)
* Knockout models of key molecules in the MAPK pathways and apoptotic pathway reduced apoptotic activity and restored neuron numbers induced by simulated ischemic stroke or radiation (Tian et al., 2020; Chow, Li and Wong, 2000; Limoli et al., 2004).

* Inhibition of key signaling molecules involved in the MAPK pathways and the PI3K/Akt pathway restored neural stem cell numbers, neuronal differentiation, and neuronal structure induced by radiation (Eom et al., 2016; Kanzawa et al., 2006; Zhang et al. 2018)

### Essentiality of Tissue Resident Cell Activation (KE#1492)

* The effects of modulating cell activation on pro-inflammatory mediators (KE#1493)

* Drugs including tamoxifen, retinoic acid, N-acetyl-L-cysteine (NAC), SP 600125 (SP), a specific c-jun kinase inhibitor, and NS-398, a microglial activator attenuated the activation of tissue-resident cells and consequently reduced the levels of pro-inflammatory mediators (Liu et al., 2010; van Neerven et al., 2010; Komatsu et al., 2017; Ramanan, 2008; Kyrkanides et al., 2002).

### Essentiality of Pro-Inflammatory Mediators (KE#1493)

* The effects of modulating pro-inflammatory mediators on abnormal neural remodeling (KE#2098)

* Treatments including MW-151, a selective inhibitor of pro-inflammatory cytokine production, KuA, and histamine restored neurogenic signaling, hippocampal apoptosis, and neuronal complexity (Jenrow et al., 2013; Zhang et al., 2017; Saraiva et al., 2019).

* Multiple studies use cytokine receptor antagonists or knock-out key receptors to block the effects of IL-1β, TNF-α, and CCL2, which preserves neuron survival (Green et al., 2012; Ryan et al., 2013; Wu et al., 2012; Chen and Palmer, 2013).

* Complement component 3 (C3) knockout models also caused increased synaptic number, reduced neuron loss and ameliorated synaptic morphology impairment (Shi et al., 2017).

* The effects of modulating pro-inflammatory mediators on learning and memory impairment (AO, KE#341)

* Anti-inflammatory drugs or hormones including MW-151, a selective inhibitor of pro-inflammatory cytokine production, lidocaine, an anesthetic with anti-inflammatory properties, ethyl-eicosapentaenoate (E-EPA) and 1-[(4-nitrophenyl)sulfonyl]-4-phenylpiperazine (NSPP), both of which are anti-inflammatory drugs and α-Melanocyte stimulating hormone (α-MSH), which antagonizes the effects of pro-inflammatory cytokines, have rescued the impairments seen in learning and memory (Bhat et al., 2020; Gonzalez et al., 2009; Jenrow et al., 2013; Taepavarapruk & Song, 2010; Tan et al., 2014).

### Essentiality of Abnormal Neural Remodeling (KE#2098)

No identified studies describe essentiality of abnormal neural remodeling as it cannot be blocked / decreased using chemicals

<table><thead><tr><th></th><th>Defining Question</th><th>High (Strong)</th><th>Moderate</th><th>Low (Weak)</th></tr></thead><tbody><tr><td>Support for Essentiality of KEs</td><td>Are downstream KEs and/or the AO prevented if an upstream KE is blocked?</td><td>Direct evidence from specifically designed experimental studies illustrating essentiality for at least one of the important KEs</td><td>Indirect evidence that sufficient modification of an expected modulating factor attenuates or augments a KE</td><td>No or contradictory experimental evidence of the essentiality of any of the KEs</td></tr><tr><td>MIE, KE#1686: Deposition of energy</td><td colspan="4">Evidence for Essentiality of KE: Moderate<br>Deposition of energy is difficult to test for essentiality as deposition of energy is a physical stressor and cannot be blocked/decreased using chemicals. In the absence of energy deposition or presence of shielding as demonstrated there should be no alterations to the relevant downstream KE.</td></tr><tr><td>KE#1392: Oxidative stress</td><td colspan="4">Evidence for Essentiality of KE: Moderate</td></tr></tbody></table>
<table><tr><td>KE#1635: Increase, DNA Strand Breaks</td><td>Treatments with antioxidants, which reduce oxidative stress, attenuate downstream microglial activation and DNA strand breaks.<br>Evidence for Essentiality of KE: Moderate<br>Prevention of DNA strand breaks, for example treatment with mesenchymal stem cell-conditioned medium or minocycline, has restored altered signaling and prevented abnormal neural remodeling.</td></tr><tr><td>KE#2244: Altered Stress Response Signaling</td><td>Evidence for Essentiality of KE: Moderate<br>Knockout models or inhibition of key signaling molecules, have all been shown to influence the effects of altered stress response signaling on abnormal neural remodeling through the attenuation of stressor-induced changes in neuronal morphology and growth. The KE has also been shown to be modulated by sex and exercise.</td></tr><tr><td>KE#1492: Tissue Resident Cell Activation</td><td>Evidence for Essentiality of KE: Moderate<br>For example, the attenuation of the activation of tissue-resident cells and consequent reduction in pro-inflammatory mediators has been reported using multiple drugs</td></tr><tr><td>KE#2097: Increase, Pro-inflammatory Mediators</td><td>Evidence for Essentiality of KE: Moderate<br>Treatments with anti-inflammatory drugs, antioxidants or hormones have influenced the effects of pro-inflammatory mediators and improved neuronal structure and function. Anti-inflammatory drugs have also influenced the effects of pro-inflammatory mediators and rescued the impairments seen in learning and memory.</td></tr><tr><td>KE#2098: Increase, Abnormal Neural Remodeling</td><td>Evidence for Essentiality of KE: Moderate<br>No identified studies describe essentiality of neural remodeling as it cannot be blocked / decreased using chemicals.</td></tr></table>
Biological Plausibility

<table><thead><tr><th>Support for Biological Plausibility of KERs</th><th>Defining Question</th><th>High (Strong)</th><th>Moderate</th><th>Low (Weak)</th></tr></thead><tbody><tr><td></td><td>Is there a mechanistic relationship between KEup and KEdown consistent with established biological knowledge?</td><td>Extensive understanding of the KER based on extensive previous documentation and broad acceptance; Established mechanistic basis</td><td>KER is plausible based on analogy to accepted biological relationships, but scientific understanding is not completely established</td><td>There is empirical support for statistical association between KEs, but the structural or functional relationship between them is not understood</td></tr><tr><td>Deposition of Energy (MIE, KE#1686) → Oxidative Stress (KE#1392)</td><td></td><td></td><td>Evidence for Biological Plausibility of KER: High</td><td>There is high evidence surrounding the biological plausibility of deposition of energy leading to increased oxidative stress. When energy reaches a cell, it reacts with water and organic materials to produce ROS. Oxidative stress occurs when antioxidant systems cannot eliminate ROS.</td></tr><tr><td>Deposition of Energy (MIE, KE#1686) → Tissue Resident Cell Activation (KE#1492)</td><td></td><td></td><td>Evidence for Biological Plausibility of KER: High</td><td>There is high evidence surrounding biological plausibility of deposition of energy leading to tissue resident cell activation. It is well understood that deposition of radiation energy leads to a recruitment of immune cells within the local tissue which can induce an immune and inflammatory response, characterized by the recruitment and activation of local macrophages in the brain.</td></tr><tr><td>Oxidative Stress (KE#1392) → Increase, DNA Strand Breaks (KE#1635)</td><td></td><td></td><td>Evidence for Biological Plausibility of KER: High</td><td>There is high evidence surrounding biological plausibility of oxidative stress leading to DNA strand breaks. Oxidative stress can induce DNA damage by oxidizing or deleting DNA bases leading to strand breaks.</td></tr><tr><td>Increase, DNA Strand Breaks (KE#1635) → Altered Stress Response Signaling (KE#2244)</td><td></td><td></td><td>Evidence for Biological Plausibility of KER: High</td><td>There is high evidence surrounding biological plausibility of increased DNA strand breaks to altered stress response signaling. DNA strand breaks induce DNA damage responses which result in the induction of various stress response signaling.</td></tr><tr><td>Oxidative Stress (KE#1392) → Tissue Resident Cell Activation (KE#1492)</td><td></td><td></td><td>Evidence for Biological Plausibility of KER: Moderate</td><td>There is moderate evidence surrounding biological plausibility of increased oxidative stress leading to tissue resident cell activation. Increases in oxidative stress elicits activation of microglial cells and astrocytes in the brain. Activated microglia and astrocytes release pro-inflammatory mediators and promote antioxidant defenses. Feedforward and feedback loops of RONS and inflammatory pathways make the direct link between oxidative stress and microglial cell or astrocyte activation difficult to discern.</td></tr><tr><td>Oxidative Stress (KE#1392) → Altered Stress Response Signaling (KE#2244)</td><td></td><td></td><td>Evidence for Biological Plausibility of KER: High</td><td>There is high evidence surrounding the biological plausibility of increased oxidative stress to altered stress response signaling. Oxidative stress can lead to altered stress response signaling both directly and indirectly. Directly, oxidative stress conditions can lead to oxidation of amino acid residues. This causes conformational changes, protein expansion, and protein degradation, leading to changes in the activity and level of signaling proteins that result in downstream alterations in signaling pathways. Indirectly, oxidative stress can damage DNA causing changes in the expression of signaling proteins as well as the activation of DNA damage response signaling.</td></tr><tr><td>Altered Stress Response Signaling (KE#2244) → Increase, Abnormal Neural Remodeling (KE#2098)</td><td></td><td></td><td>Evidence for Biological Plausibility of KER: Moderate</td><td>There is moderate evidence surrounding biological plausibility of altered stress response signaling to abnormal neural remodeling. Abnormal neural remodeling is controlled by signaling pathways in the brain, including PI3K/Akt pathway, MAPK pathways, senescence pathways, and apoptosis pathways. The PI3K/Akt and MAPK pathways are involved in many processes in neurons, including cell survival, morphology, proliferation, differentiation, and synaptic activity. The apoptosis pathway influences cell numbers, while the senescence pathway can influence neurogenesis. Disruptions to components of these pathways will lead to abnormal neural remodeling in a relationship that is structurally well-understood. However, the biological changes that follow perturbation of these pathways is not understood in every context and cell type.</td></tr><tr><td>Tissue Resident Cell Activation (KE#1492) → Increase, Pro-inflammatory Mediators (KE#2097)</td><td></td><td></td><td>Evidence for Biological Plausibility of KER: High</td><td>There is high evidence surrounding biological plausibility of tissue resident activation to increase in pro-inflammatory mediators. In the brain, activated astrocytes and microglia undergo gliosis and proliferate, releasing pro-inflammatory mediators and production of cytokines. This response is normal after exposure to pathogens, but prolonged activation can prolong the inflammatory response. Cytokines and</td></tr></tbody></table>
<table><tr><td>Increase, Pro-inflammatory<br>Mediators (KE#2097) →<br>Increase, Abnormal Neural<br>Remodeling (KE#2098)</td><td>Chemokines can also increase the permeability of the blood-brain barrier, further increasing pro-inflammatory mediator levels.<br><b>Evidence for Biological Plausibility of KER: Moderate</b><br>There is moderate evidence surrounding the biological plausibility of increased pro-inflammatory mediators to abnormal neural remodeling. There are various pro-inflammatory cytokines that can affect neuronal integrity an inflammatory response and these cytokines act on different receptors to initiate several signaling pathways to induce neuronal degeneration, apoptosis or to propagate pro-inflammatory responses. However, the exact mechanistic relationship remains to be elucidated due to the complexity of cytokine cascading events.</td></tr><tr><td>Increase, Abnormal Neural<br>Remodeling (KE#2098) →<br>Impairment, Learning and<br>Memory (AO, KE#341)</td><td>There is moderate evidence surrounding biological plausibility of abnormal neural remodeling leading to impaired learning and memory. Evidence of abnormal neural remodeling, such as reductions in spine density, reduced adult neurogenesis and impaired neuronal networks are associated with cognitive impairments, as evident from studies in multiple different species</td></tr><tr><td>Deposition of Energy (MIE, KE#<br>1686) → Increase, Abnormal<br>Neural Remodeling (KE#2098)</td><td>Chemokines can also increase the permeability of the blood-brain barrier, further increasing pro-inflammatory mediator levels.<br><b>Evidence for Biological Plausibility of KER: Moderate</b><br>There is moderate evidence surrounding biological plausibility of deposition of energy to abnormal neural remodeling. Irradiation induces oxidative stress and neuroinflammation, which alter neuronal integrity. Many reviews examine the radiation-induced neural damage and identify correlation with oxidative stress and neuroinflammatory mechanisms.</td></tr><tr><td>Deposition of Energy (MIE,<br>KE#1686) → Impairment,<br>Learning and Memory (AO,<br>KE#341)</td><td>Chemokines can also increase the permeability of the blood-brain barrier, further increasing pro-inflammatory mediator levels.<br><b>Evidence for Biological Plausibility of KER: High</b><br>There is high evidence surrounding biological plausibility of deposition of energy to impaired learning and memory. Energy deposition in the form of ionizing radiation can result in behavioral changes and impairments in learning and memory. Under normal conditions, diminished cognitive functions is influenced by aging or can occur if there is a predisposition to neurodegenerative diseases such as Alzheimer's, however, exposure to ionizing radiation may accelerate risk for age-related cognitive decline.</td></tr><tr><td>Deposition of Energy (MIE,<br>KE#1686) → Increase, DNA<br>Strand Breaks (KE#1635)</td><td>Chemokines can also increase the permeability of the blood-brain barrier, further increasing pro-inflammatory mediator levels.<br><b>Evidence for Biological Plausibility of KER: High</b><br>There is high evidence surrounding biological plausibility of deposition of energy to DNA strand breaks. Direct DNA damage can occur after deposition of energy by direct oxidation of the DNA. Indirect DNA damage from deposition of energy can also occur via generation of ROS that can subsequently oxidize and damage DNA.</td></tr><tr><td>Increase, DNA Strand Breaks<br>(KE#1635) → Increase,<br>Abnormal Neural Remodeling<br>(KE#2098)</td><td>Chemokines can also increase the permeability of the blood-brain barrier, further increasing pro-inflammatory mediator levels.<br><b>Evidence for Biological Plausibility of KER: Moderate</b><br>There is moderate evidence surrounding biological plausibility of increased DNA strand breaks to increase, abnormal neural remodeling. DNA strand breaks may initiate apoptotic signaling and impact synaptic activity, neural plasticity, differentiation, and proliferation.</td></tr><tr><td>Pro-inflammatory Mediators<br>(KE#2097) → Impairment,<br>Learning and Memory (AO,<br>KE#341)</td><td>Chemokines can also increase the permeability of the blood-brain barrier, further increasing pro-inflammatory mediator levels.<br><b>Evidence for Biological Plausibility of KER: Moderate</b><br>There is moderate evidence surrounding biological plausibility of the key event relationship between pro-inflammatory mediators to impaired learning and memory. In a neuroinflammatory response, pro-inflammatory mediators including cytokines induce physiological and/or structural changes within the brain that can ultimately lead to impaired learning and memory. The exact mechanistic relationship is still unclear due to the complexity of cytokine cascading events.</td></tr></table>

## Empirical Support

<table><thead><tr><th>Review of the Empirical support for each KER</th><th>Defining Question</th><th>High (Strong)</th><th>Moderate</th><th>Low (Weak)</th></tr></thead><tbody><tr><td></td><td>Does KEupstream occur at lower doses and earlier time points than KEdownstream; is the incidence or frequency of KEupstream greater than that for KEdownstream for the same dose of tested stressor?</td><td>There is a dependent change in both events following exposure to a wide range of specific stressors (extensive evidence for temporal, dose-response and incidence concordance) and no or few data gaps or conflicting data.</td><td>There is demonstrated dependent change in both events following exposure to a small number of specific stressors and some evidence inconsistent with the expected pattern that can be explained by factors such as experimental design, technical considerations, differences among laboratories, etc</td><td>There are limited or no studies reporting dependent change in both events following exposure to a specific stressor (i.e., endpoints never measured in the same study or not at all), and/or lacking evidence of temporal or dose-response concordance, or identification of significant inconsistencies in empirical support across taxa and species that don't align with the expected pattern for the hypothesised AOP</td></tr><tr><td>Deposition of Energy (MIE, KE#1686) → Oxidative Stress (KE#1392)</td><td></td><td></td><td><b>Evidence for Empirical Support of KER: High</b><br>Ample evidence from in vitro and in vivo rat, mice, rabbit, squirrel, bovine and human models support time and dose response effects related to deposition of energy from various ionizing radiation sources leading to an increase in oxidative stress.</td><td></td></tr><tr><td>Deposition of Energy (MIE, KE#1686) → Tissue Resident Cell Activation (KE#1492)</td><td></td><td></td><td><b>Evidence for Empirical Support of KER: Moderate</b><br>With increasing dose of ionizing radiation, there are increasing amounts of resident tissue activation in both astrocytes and microglial cells. Multiple studies show dose-response and time-response effects with both high and</td><td></td></tr></tbody></table>
<table>
  <tr>
    <td>Oxidative Stress (KE#1392) → Increase, DNA Strand Breaks (KE#1635)</td>
    <td>low dose studies, as well as time ranges from hours to months, though additional studies at low-doses would improve empirical support.<br><b>Evidence for Empirical Support of KER: Moderate</b><br>Empirical evidence from in vivo and in vitro studies demonstrates increased DNA strand breaks from oxidative stress. Multiple studies show dose-response effects, though time response effects are difficult to monitor for both KEs.</td>
  </tr>
  <tr>
    <td>Increase, DNA Strand Breaks (KE#1635) → Altered Stress Response Signaling (KE#2244)</td>
    <td>A few studies demonstrate dose-concordance, and multiple studies demonstrate time-concordance for this relationship. DNA strand breaks were observed prior to altered stress response signaling.<br><b>Evidence for Empirical Support of KER: Moderate</b></td>
  </tr>
  <tr>
    <td>Oxidative Stress (KE#1392) → Tissue Resident Cell Activation (KE#1492)</td>
    <td>The literature demonstrates that an increase in the level of stressor related to oxidative stress results in an increase in cellular activation of microglial cells or astrocytes and this relationship is consistent between studies. However, dose and time concordance are unclear as there is limited data that describes oxidative stress occurring at lower doses or before tissue resident cell activation.<br><b>Evidence for Empirical Support of KER: Moderate</b></td>
  </tr>
  <tr>
    <td>Oxidative Stress (KE#1392) → Altered Stress Response Signaling (KE#2244)</td>
    <td>Many studies demonstrate dose-concordance, and few demonstrate time-concordance for this relationship. Oxidative stress was often observed at lower, or the same doses as altered signaling and sometimes also at earlier times as altered signaling. However, only a few specific stressors are used in this KER and inconsistencies are present, likely due to different experimental designs.<br><b>Evidence for Empirical Support of KER: Moderate</b></td>
  </tr>
  <tr>
    <td>Altered Stress Response Signaling (KE#2244) → Increase, Abnormal Neural Remodeling (KE#2098)</td>
    <td>Many studies demonstrate dose-concordance in multiple signaling pathways. Studies have also shown that signaling pathways are altered before abnormal neural remodeling is observed. However, inconsistent changes in signaling pathways may be due to the context-dependence of signaling pathways as they can have different biological processes.<br><b>Evidence for Empirical Support of KER: Moderate</b></td>
  </tr>
  <tr>
    <td>Tissue Resident Cell Activation (KE#1492) → Increase, Pro-inflammatory Mediators (KE#2097)</td>
    <td>Studies consistently observed changes in astrocyte and microglial activation at lower or the same dose as increased pro-inflammatory mediators and many studies also found changes in astrocyte and microglial activation earlier or at the same time as increased pro-inflammatory mediators. However, inconsistencies could be due to differences in experimental conditions.<br><b>Evidence for Empirical Support of KER: Moderate</b></td>
  </tr>
  <tr>
    <td>Increase, Pro-inflammatory Mediators (KE#2097) → Increase, Abnormal Neural Remodeling (KE#2098)</td>
    <td>There are multiple studies that show time-concordance, though studies on dose-concordance are lacking. Studies suggest that pro-inflammatory mediators are increased before abnormal neural remodeling occurs, reporting changes as early as 3 hours and persisting as long as 3 months. However, additional studies describing dose-concordance would improve empirical support.<br><b>Evidence for Empirical Support of KER: Moderate</b></td>
  </tr>
  <tr>
    <td>Increase, Abnormal Neural Remodeling (KE#2098) → Impairment, Learning and Memory (AO, KE#341)</td>
    <td>Multiple studies suggest dose- and time-response effects of deposited energy leading to abnormal neural remodeling and impaired learning and memory. However, additional studies at low doses would improve empirical support. Also, discrepancies in the data may be due to experimental set up and type of exposure from the stressor.<br><b>Evidence for Empirical Support of KER: Moderate</b></td>
  </tr>
  <tr>
    <td>Deposition of Energy (MIE, KE#1686) → Increase, Abnormal Neural Remodeling (KE#2098)</td>
    <td>Multiple studies suggest dose- and time-response effects of deposition of energy to abnormal neural remodeling. Studies report changes at very low doses. However, responses may be dependent on exposure type. Also, additional studies describing time-concordance would improve empirical support.<br><b>Evidence for Empirical Support of KER: Moderate</b></td>
  </tr>
  <tr>
    <td>Deposition of Energy (MIE, KE#1686) → Impairment, Learning and Memory (AO, KE#341)</td>
    <td>Various studies show that ionizing radiation can lead to impairments in learning and memory in a dose and time dependent manner. Although the impairment to learning and memory is well-studied across various doses and over multiple time points, studies often do not show impaired learning and memory with every cognitive test used, contributing to inconsistency in the relationship.<br><b>Evidence for Empirical Support of KER: Moderate</b></td>
  </tr>
  <tr>
    <td>Deposition of Energy (MIE, KE#1686) → Increase, DNA Strand Breaks (KE#1635)</td>
    <td>There is ample empirical evidence demonstrating the relationship between deposition of energy and increase, DNA strand breaks. Multiple studies in various models show both dose-concordance and time-concordance.<br><b>Evidence for Empirical Support of KER: High</b></td>
  </tr>
  <tr>
    <td>Increase, DNA Strand Breaks (KE#1635) → Increase, Abnormal Neural Remodeling (KE#2098)</td>
    <td>Multiple studies demonstrate that increased DNA strand breaks lead to increased abnormal neural remodeling. However, additional studies describing both dose-concordance and time-concordance would improve empirical support.<br><b>Evidence for Empirical Support of KER: Moderate</b></td>
  </tr>
  <tr>
    <td>Increase, Pro-inflammatory Mediators (KE#2097) → Impairment, Learning and Memory (AO, KE#341)</td>
    <td>Evidence shows that pro-inflammatory mediators increase at lower or the same stressor doses than impaired learning. Also, pro-inflammatory mediators increase before impaired learning and memory is observed. Significant inconsistencies in empirical support across taxa and species that do not align with the expected pattern have not been identified.<br><b>Evidence for Empirical Support of KER: Moderate</b></td>
  </tr>
</table>
## Known Modulating Factors

Multiple factors can modulate this AOP, most of which are listed in the table below. Other modulating factors that influence the AOP are knockout models or receptor antagonists (Tian et al., 2020; Chow, Li and Wong, 2000; Limoli et al., 2004; Eom et al., 2016; Kanzawa et al., 2006; Zhang et al. 2018; Green et al., 2012; Ryan et al., 2013; Wu et al., 2012; Chen and Palmer, 2013; Shi et al., 2017).

<table><thead><tr><td>Modulating Factor</td><td>MF details</td><td>Effects on the KER</td><td>References</td></tr></thead><tbody><tr><td>Antioxidants</td><td>Catalase, glutathione peroxidase, superoxide dismutase, peroxiredoxins, vitamins E, C, carotene, lutein, zeaxanthin, selenium, zinc, alpha-lipoic acid, melatonin, gingko biloba leaf, fermented gingo biloba leaf, Nigella sativa oil, thymoquinone, ferulic acid, Kukoamine A, curcumin, high antioxidant diet, α-tocopherol, α-lipoic 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; El-Mesallamy et al., 2018; Hua et al., 2019; Kang et al., 2020; Yang et al., 2020; Manda et al., 2008; Limoli et al., 2007; Manda et al., 2007a; Ismail et al., 2016; Demir et al., 2019; Chen et al., 2021, Zhang et al., 2017, Wang et al., 2017; Daverey & Agrawal, 2016, Ávila-Escalante et al., 2020, Hladik & Tapio, 2016, Manda et al., 2007b</td></tr><tr><td>Drugs</td><td>Modulators of tissue resident cell activation (e.g. tamoxifen, retinoic acid, NAC, SP 600125, NS-398), pro-inflammatory mediators (e.g. MW-151, lidocaine, E-EPA, NSPP, α-MSH), and drugs that inhibit DNA damage (lithium chloride, minocycline).</td><td>Several drugs have attenuated the activation of tissue-resident cells and reduced the levels of pro-inflammatory mediators to consequently ameliorate the downstream KE. Drugs that inhibit DNA damage reduced the expression of γ-H2AX and reduced cellular apoptosis.</td><td>Liu et al., 2010; van Neerven et al., 2010; Komatsu et al., 2017; Ramanan, 2008; Kyrkanides et al., 2002; Bhat et al., 2020; Gonzalez et al., 2009; Jenrow et al., 2013; Taepavarapruk & Song, 2010; Tan et al., 2014; Zhang et al., 2017; Zanni et al., 2015</td></tr><tr><td>Age</td><td>Age of organism</td><td>Aging can impact multiple KEs. For example, older organisms have lower levels of antioxidants and an increased likelihood of oxidative stress. Older age is also associated with greater tissue resident cell activation and aging tissue becomes more sensitive to immune signals and increases inflammation. Age is associated with reduced hippocampal neurogenesis and greater radiation-related decrements in learning and memory.</td><td>Liguori et al., 2018; Hanslik, Marino & Ulland, 2021; Casciati et al., 2016; Patterson, 2015; Barrientos et al., 2009; Barrientos et al., 2012.</td></tr><tr><td>Sex</td><td>Sex of organism</td><td>The sex of the organism studied can impact several KEs. For example, male mice typically showed an increase in microglia activation, while female mice showed no significant changes. Female mice were also protected from radiation-induced impairments in learning and memory. However, not all studies found this trend.</td><td>Krukowski et al., 2018a; Parihar et al., 2020; Raber et al., 2019</td></tr><tr><td>Prior Disease</td><td>Neurodegenerative diseases like Alzheimer's and Parkinson's</td><td>Generates an environment of increased oxidative stress and promotes the activation of glial cells.</td><td>Hanslik, Marino & Ulland, 2021</td></tr><tr><td>Genetics</td><td>Polymorphism that increases the expression of the APOE4 gene increases the risk of developing Alzheimer's diseases, which generally consists of a decline in</td><td>In homozygous human APOE4 knock-in mice, a dramatic increase in pro-inflammatory cytokines TNF-alpha, IL-1β and IL-6 was seen after LPS injection compared to the</td><td>Hunsberger et al., 2019; Zhu et al., 2012; Sabirzhanov et al., 2020</td></tr></tbody></table>
<table><tr><td></td><td>memory, thinking and language. MicroRNA expression such as miR-711.</td><td>APOE2 and APOE3 alleles, suggesting that APOE4 is implicated in a greater inflammatory response. Inhibition of miR-711 reduced DNA damage responses and signaling molecules.</td><td></td></tr><tr><td>Exercise</td><td>Forced running in 30-min intervals twice per day, 5 times per week for 3 weeks.</td><td>Forced running after irradiation completely restored the levels of the signaling molecules in the BDNF-pCREB pathway and slightly restored neurogenesis.</td><td>Ji et al., 2014</td></tr></table>
# Quantitative Understanding

Overall quantitative understanding for the KERs in the AOP is low. Despite evidence supporting the KERs, there is limited understanding of the trends of the relationships between KEs. In the KERs of this AOP, there are positive relationships between the KEs (i.e., an increase in the upstream KE elicits a change in the downstream KE); however, the trends and shapes of the relationships are not well established due to differences in experimental parameters, such as model, radiation type, doses, dose rate, and time of measurements. The measures of the KEs cannot be precisely predicted based on relevant measures of the other KEs in the KER and the quantitative descriptions does not account for all known modulating factors and feedback or feedforward mechanisms.

<table><thead><tr><th></th><th>Defining Question</th><th>High (Strong)</th><th>Moderate</th><th>Low (Weak)</th></tr></thead><tbody><tr><td>Review of the Quantitative Understanding for each KER</td><td>To what extent can a change in a KEdownstream can be predicted for a KEupstream? With what precision the uncertainty in the prediction of the KEdownstream can be quantified? To what extent are the known modulating factors of feedback mechanisms accounted for? To what extent to which the relationships described can be reliably generalized across the applicability domain of the KER?</td><td>Change in KEdownstream can be precisely predicted based on a relevant measure of KEupstream; Uncertainty in the quantitative prediction can be precisely estimated from the variability in the relevant KEupstream measure; Known modulating factors and feedback/ feedforward mechanisms are accounted for in the quantitative description; Evidence that the quantitative relationship between the KEs generalizes across the relevant applicability domain of the KER</td><td>Change in KEdownstream can be precisely predicted based on relevant measure of KEupstream; Uncertainty in the quantitative prediction is influenced by factors other than the variability in the relevant KEupstream measure; Quantitative description does not account for all known modulating factors and/or known feedback/ feedforward mechanisms; Quantitative relationship has only been demonstrated for a subset of the overall applicability domain of the KER</td><td>Only a qualitative or semi-quantitative prediction of the change in KEdownstream can be determined from a measure of KEupstream; Known modulating factors and feedback/ feedforward mechanisms are not accounted for; Quantitative relationship has only been demonstrated for a narrow subset of the overall applicability domain of the KER</td></tr><tr><td>Deposition of Energy (MIE, KE#1686) → Oxidative Stress (KE#1392)</td><td></td><td></td><td>Evidence for Quantitative Understanding of the KER: Moderate<br>The evidence for this KER suggests that increased deposition of energy elicits increased oxidative stress, and this is supported by measurements from a large range of doses and dose rates. Despite a large amount of available evidence, the shape of the relationship is not clear, and may depend on the endpoints used to measure oxidative stress.</td><td></td></tr><tr><td>Deposition of Energy (MIE, KE#1686) → Tissue Resident Cell Activation (KE#1492)</td><td></td><td></td><td>Evidence for Quantitative Understanding of the KER: Moderate<br>Despite a moderate amount of evidence supporting this KER such that increased deposition of energy leads to increased tissue resident cell activation, no clear trends have been established to allow for prediction of the precise amount of tissue resident cell activation based on the deposition of energy. It is likely that the abundance of tissue resident cell activation depends on the biological model, radiation type, radiation dose range and radiation dose rate.</td><td></td></tr><tr><td>Oxidative Stress (KE#1392) → Increase, DNA Strand Breaks (KE#1635)</td><td></td><td></td><td>Evidence for Quantitative Understanding of the KER: Moderate<br>There are models available that predict DNA strand breaks after deposition of energy; however the exact contribution of indirect DNA damage from oxidative stress is unknown. The quantitative understanding of the relationship depends on the biological target, the radiation quality, and the dose.</td><td></td></tr><tr><td>Increase, DNA Strand Breaks (KE#1635) → Altered Stress Response Signaling (KE#2244)</td><td></td><td></td><td>Evidence for Quantitative Understanding of the KER: Low<br>There are no trends or mathematical models that describe this relationship. Quantitative relationships between these two KEs depend on experimental model and dose.</td><td></td></tr><tr><td>Oxidative Stress (KE#1392) → Tissue Resident Cell</td><td></td><td></td><td>Evidence for Quantitative Understanding of the KER: Low<br>Overall, the evidence suggests that there is a positive relationship between increased oxidative stress and tissue resident cell activation. However, studies often report a single dose or time-point, making it difficult to quantitatively predict the amount of tissue resident cell activation after an increase in oxidative stress.</td><td></td></tr></tbody></table>
<table><tr><td>Activation (KE#1492)</td><td><strong>Evidence for Quantitative Understanding of the KER: Low</strong><br/>A precise quantitative relationship between oxidative stress and altered stress response signaling is difficult to determine because each study uses a different experimental design. The exact changes to signaling pathways due to oxidative stress will depend on the cell type and species. In addition, modulating factors are often not indicated or accounted for in studies.</td></tr><tr><td>Oxidative Stress (KE#1392) → Altered Stress Response Signaling (KE#2244)</td><td><strong>Evidence for Quantitative Understanding of the KER: Low</strong><br/>The complexity of the many synergistic and antagonistic signaling pathways influenced by a stressor will lead to a cumulative change not representative of the change to a single or a few signaling pathways. Therefore, no trend or mathematical model has been established to quantitatively determine the relationship between altered stress response signaling and endpoints related to abnormal neural remodeling.</td></tr><tr><td>Altered Stress Response Signaling (KE#2244) → Increase, Abnormal Neural Remodeling (KE#2098)</td><td><strong>Evidence for Quantitative Understanding of the KER: Low</strong><br/>Despite evidence to show that tissue-resident cell activation leads to an increase in pro-inflammatory mediators, it is difficult to compare results and identify a trend as each study uses different models, stressors, doses and time scales. No trend or mathematical model has been established to quantitatively determine the increase in pro-inflammatory mediators after glial cell activation.</td></tr><tr><td>Tissue Resident Cell Activation (KE#1492) → Increase, Pro-inflammatory Mediators (KE#2097)</td><td><strong>Evidence for Quantitative Understanding of the KER: Low</strong><br/>Despite studies showing time concordance, no trends or mathematical models have been established that can describe the relationship between increased pro-inflammatory mediators and abnormal neural remodeling.</td></tr><tr><td>Increase, Pro-inflammatory Mediators (KE#2097) → Increase, Neural Remodeling (KE#2098)</td><td><strong>Evidence for Quantitative Understanding of the KER: Low</strong><br/>Although a linear relationship was found between reductions in spine density and impairment on a test of learning and memory, no further trends have been established. There may be sex-, dose-, time- and radiation type-dependent differences in the effects of ionizing radiation on abnormal neural remodeling to impairment in learning and memory.</td></tr><tr><td>Increase, Abnormal Neural Remodeling (KE#2098) → Impairment, Learning and Memory (AO, KE#341)</td><td><strong>Evidence for Quantitative Understanding of the KER: Low</strong><br/>Evidence in support of this KER suggests that deposition of energy elicits a dose-dependent change in neural remodeling. However, the evidence base for the KER has some inconsistencies. In addition, the age of the subjects may impact the trend of the relationship. Ultimately the shape of the trend between the two KEs is unclear and may depend on the biological model used, age of the subjects, type of radiation and radiation dose/dose-rate.</td></tr><tr><td>Deposition of Energy (MIE, KE#1686) → Increase, Abnormal Neural Remodeling (KE#2098)</td><td><strong>Evidence for Quantitative Understanding of the KER: Low</strong><br/>Deposition of energy from ionizing radiation is consistently shown to impair learning and memory. However, no trend or mathematical model has been established to accurately describe this relationship. Much of the evidence for this KER comes from different experimental model species, exposures, time scales and cognitive function tests to assess the AO, making comparisons between studies and quantitative model development difficult.</td></tr><tr><td>Deposition of Energy (MIE, KE#1686) → Impairment, Learning and Memory (AO, KE#341)</td><td><strong>Evidence for Quantitative Understanding of the KER: High</strong><br/>There are models available that predict DNA strand breaks after deposition of energy due to exposure to ionizing radiation. The quantitative understanding of the relationship depends on the biological target, the radiation quality, and the dose and these have been well studied.</td></tr><tr><td>Increase, DNA Strand Breaks (KE#1635) → Increase, Abnormal Neural Remodeling (KE#2098)</td><td><strong>Evidence for Quantitative Understanding of the KER: Low</strong><br/>There are multiple studies that report abnormal neural remodeling in response to DNA strand breaks. However, no trend or mathematical model has been established to accurately describe this relationship.</td></tr><tr><td>Pro-inflammatory Mediators (KE#2097) → Impairment, Learning and Memory (AO, KE#341)</td><td><strong>Evidence for Quantitative Understanding of the KER: Low</strong><br/>Most studies report that an increase in pro-inflammatory mediators to impaired learning and memory; however, semi-quantitative measurements have been described for either upstream or downstream KE. Some, but not all, known modulating factors have been accounted for, mainly consisting of anti-inflammatory treatments. No trends or quantitative models have described this relationship.</td></tr></table>
Considerations for Potential Applications of the AOP

This AOP was developed to bring together mechanistic knowledge in the area of impairments in learning and memory from exposure to radiation. It includes studies from multiple species at multiple life stages and radiation exposures that contain different doses, dose-rates, and radiation qualities. Relevant studies have been selected, consolidated, and reported using the framework.

There are multiple considerations for potential applications of the AOP. Since exposure to radiation can occur in humans from multiple events, including occupational settings, accidental exposures, nuclear events, radiotherapy treatment and space travel, understanding its impact on CNS structure and function is essential. This AOP outlines a biological framework for the connection between the MIE and AO. It can be expanded to other pathophysiologies of the CNS. The qualitative information presented within each KER can be used to inform on risk-model strategies, countermeasure development, and identification of gaps in the evidence base where more research is necessary. Importantly, this AOP is a dynamic document so it can be modified as new evidence emerges.
Acharya, M. M. et al. (2010), "Consequences of ionizing radiation-induced damage in human neural stem cells", Free Radical Biology and Medicine, Vol. 49/12, Pergamon, https://doi.org/10.1016/j.freeradbiomed.2010.08.021.

Ahmadi, M. et al. (2022), "Early responses to low-dose ionizing radiation in cellular lens epithelial models", Radiation research, Vol. 197/1, Radiation Research Society, Bozeman, https://doi.org/10.1667/RADE-20-00284.1

Antonelli, A.F. et al. (2015), "Induction and Repair of DNA DSB as Revealed by H2AX Phosphorylation Foci in Human Fibroblasts Exposed to Low- and High-LET Radiation: Relationship with Early and Delayed Reproductive Cell Death", Radiation Research, Vol 183/4, BioOne, Washington, https://doi.org/10.1667/RR13855.1

Azimzadeh, O. et al. (2015), "Integrative proteomics and targeted transcriptomics analyses in cardiac endothelial cells unravel mechanisms of long-term radiation-induced vascular dysfunction", Journal of Proteome Research, Vol. 14/2, American Chemical Society, Washington, https://doi.org/10.1021/pr501141b

Balasubramanian, D (2000), "Ultraviolet radiation and cataract", Journal of ocular pharmacology and therapeutics, Vol. 16/3, Mary Ann Liebert Inc., Larchmont, https://doi.org/10.1089/jop.2000.16.285.

Bálentová, S. and M. Adamkov. (2020), "Pathological changes in the central nervous system following exposure to ionizing radiation", Physiological Research, Czech Academy of Sciences, https://doi.org/10.33549/PHYSIOLRES.934309.

Barrientos, R. M. et al. (2009), "Time course of hippocampal IL-1 β and memory consolidation impairments in aging rats following peripheral infection", Brain, Behavior, and Immunity, Vol. 23/1, Elsevier, Amsterdam, https://doi.org/10.1016/j.bbi.2008.07.002.

Barrientos, R. M. et al. (2012), "Aging-related changes in neuroimmune-endocrine function: Implications for hippocampal-dependent cognition", Hormones and Behavior, Vol. 62/3, Elsevier, Amsterdam, https://doi.org/10.1016/j.yhbeh.2012.02.010.

Belkacémi, Y. et al. (2001), "Lens epithelial cell protection by aminothiol WR-1065 and anetholedithiolethione from ionizing radiation", International journal of cancer, Vol. 96, John Wiley & Sons, Ltd., Hoboken, https://doi.org/10.1002/ijc.10346.

Betlazar, C. et al. (2016), "The impact of high and low dose ionising radiation on the central nervous system", Redox Biology, Vol. 9, Elsevier, Amsterdam, https://doi.org/10.1016/j.redox.2016.08.002.

Bhat, K. et al. (2020), "1-[(4-Nitrophenyl)sulfonyl]-4-phenylpiperazine treatment after brain irradiation preserves cognitive function in mice", Neuro-Oncology, Vol. 22/10, Oxford University Press, Oxford, https://doi.org/10.1093/neuonc/noaa095.

Brooks, A.L., D.G. Hoel & R.J. Preston (2016), "The role of dose rate in radiation cancer risk: evaluating the effect of dose rate at the molecular, cellular and tissue levels using key events in critical pathways following exposure to low LET radiation.", International Journal of Radiation Biology, Vol. 92/8, Taylor & Francis, London, doi:10.1080/09553002.2016.1186301.

Casciati, A. et al. (2016), "Age-related effects of X-ray irradiation on mouse hippocampus", Oncotarget, Vol. 7/19, https://doi.org/10.18632/oncotarget.8575.

Cekanaviciute, E., S. Rosi and S. V. Costes. (2018), "Central nervous system responses to simulated galactic cosmic rays", International Journal of Molecular Sciences, Multidisciplinary Digital Publishing Institute (MDPI) AG, Basel, https://doi.org/10.3390/ijms19113669.

Chen, Z. and T. D. Palmer. (2013), "Differential roles of TNFR1 and TNFR2 signaling in adult hippocampal neurogenesis", Brain, Behavior, and Immunity, Vol. 30, Elsevier Inc., Amsterdam, https://doi.org/10.1016/j.bbi.2013.01.083.
Chen, Y. et al. (2021), "Effects of neutron radiation on Nrf2-regulated antioxidant defense systems in rat lens", Experimental and therapeutic medicine, Vol. 21/4, Spandidos Publishing Ltd, Athens, https://doi.org/10.3892/etm.2021.9765.

Chitchumroonchokchai, C. et al. (2004), "Xanthophylls and α-tocopherol decrease UVB-induced lipid peroxidation and stress signaling in human lens epithelial cells", The Journal of Nutrition, Vol. 134/12, American Society for Nutritional Sciences, Bethesda, https://doi.org/10.1093/jn/134.12.3225.

Chow, B. M., Y.-Q. Li and C. S. Wong. (2000), "Radiation-induced apoptosis in the adult central nervous system is p53-dependent", Cell Death & Differentiation, Vol. 7/8, Springer Nature, https://doi.org/10.1038/sj.cdd.4400704.

Cucinotta, F. A. et al. (2014), "Space radiation risks to the central nervous system", Life Sciences in Space Research, Vol. 2, Elsevier Ltd, Amsterdam, https://doi.org/10.1016/j.lssr.2014.06.003.

Daverey, A. and S. K. Agrawal. (2016), "Curcumin alleviates oxidative stress and mitochondrial dysfunction in astrocytes", Neuroscience, Vol. 333, https://doi.org/10.1016/j.neuroscience.2016.07.012.

Davis, S. and S. Laroche. (2006), "Mitogen-activated protein kinase/extracellular regulated kinase signalling and memory stabilization: a review", Genes, Brain and Behavior, Vol. 5, Wiley, https://doi.org/10.1111/j.1601-183X.2006.00230.x.

de Jager, T. L., A. E. Cockrell, S. S. Du Plessis (2017), "Ultraviolet Light Induced Generation of Reactive Oxygen Species", in: Ultraviolet Light in Human Health, Diseases and Environment, vol 996. Springer Cham, https://doi.org/10.1007/978-3-319-56017-5_2.

Demir, E. et al. (2020), "Nigella sativa oil and thymoquinone reduce oxidative stress in the brain tissue of rats exposed to total head irradiation", International journal of radiation biology, Vol. 96/2, Informa, London, https://doi.org/10.1080/09553002.2020.1683636.

Deng, Z. et al. (2012), "Radiation-Induced c-Jun Activation Depends on MEK1-ERK1/2 Signaling Pathway in Microglial Cells", (I. Ulasov, Ed.) PLoS ONE, Vol. 7/5, https://doi.org/10.1371/journal.pone.0036739.

Desai, R. I. et al. (2022), "Impact of spaceflight stressors on behavior and cognition: A molecular, neurochemical, and neurobiological perspective", Neuroscience & Biobehavioral Reviews, Vol. 138, Elsevier, Amsterdam, https://doi.org/10.1016/j.neubiorev.2022.104676.

Dong, X. et al. (2015), "Relationship between irradiation-induced neuro-inflammatory environments and impaired cognitive function in the developing brain of mice", International Journal of Radiation Biology, Vol. 91/3, Informa Healthcare, London, https://doi.org/10.3109/09553002.2014.988895.

El-Missiry, M. A. et al. (2018), "Neuroprotective effect of epigallocatechin-3-gallate (EGCG) on radiation-induced damage and apoptosis in the rat hippocampus", International Journal of Radiation Biology, Vol. 94/9, https://doi.org/10.1080/09553002.2018.1492755.

Eom, H. S. et al. (2015), "Ionizing radiation induces neuronal differentiation of Neuro-2a cells via PI3-kinase and p53-dependent pathways", International Journal of Radiation Biology, Vol. 91/7, Informa, London, https://doi.org/10.3109/09553002.2015.1029595.

Falcicchia, C. et al. (2020), "Involvement of p38 MAPK in Synaptic Function and Dysfunction", International Journal of Molecular Sciences, Vol. 21/16, MDPI, Basel, https://doi.org/10.3390/ijms21165624.

Fatma, N. et al. (2005), "Impaired homeostasis and phenotypic abnormalities in Prdx6-/- mice lens epithelial cells by reactive oxygen species: Increased expression and activation of TGFβ", Cell death and differentiation, Vol. 12, Nature Portfolio, London, https://doi.org/10.1038/sj.cdd.4401597.
Fishman, K. et al. (2009), "Radiation-induced reductions in neurogenesis are ameliorated in mice deficient in CuZnSOD or MnSOD", Free Radical Biology and Medicine, Vol. 47/10, https://doi.org/10.1016/j.freeradbiomed.2009.08.016.

Fletcher, A. E (2010), "Free radicals, antioxidants and eye diseases: evidence from epidemiological studies on cataract and age-related macular degeneration", Ophthalmic Research, Vol. 44, Karger International, Basel, https://doi.org/10.1159/000316476.

Ganea, E. and J. J. Harding (2006), "Glutathione-related enzymes and the eye", Current eye research, Vol. 31/1, Informa, London, https://doi.org/10.1080/02713680500477347.

Giedzinski, E. et al. (2005), "Efficient production of reactive oxygen species in neural precursor cells after exposure to 250 MeV protons", Radiation research, Vol. 164/4, Radiation Research Society, Bozeman, https://doi.org/10.1667/rr3369.1.

Gonzalez, P. V. et al. (2009), "Memory impairment induced by IL-1β is reversed by α-MSH through central melanocortin-4 receptors", Brain, Behavior, and Immunity, Vol. 23/6, Elsevier, Amsterdam, https://doi.org/10.1016/j.bbi.2009.03.001.

Green, H. F. et al. (2012), "A role for interleukin-1β in determining the lineage fate of embryonic rat hippocampal neural precursor cells", Molecular and Cellular Neuroscience, Vol. 49/3, Elsevier Inc., Amsterdam, https://doi.org/10.1016/j.mcn.2012.01.001.

Greene-Schloesser, D. et al. (2012), "Radiation-induced brain injury: A review", Frontiers in Oncology, Vol. 2, Frontiers, Lausanne, https://doi.org/10.3389/fonc.2012.00073.

Hanslik, K. L., K. M. Marino and T. K. Ulland. (2021), "Modulation of Glial Function in Health, Aging, and Neurodegenerative Disease", Frontiers in Cellular Neuroscience, Vol. 15, https://doi.org/10.3389/fncel.2021.718324.

Hamada, N. et al. (2006), "Histone H2AX phosphorylation in normal human cells irradiated with focused ultrasoft X rays: evidence for chromatin movement during repair", Radiation Research, Vol. 166/1, Radiation Research Society, United States, https://doi.org/10.1667/RR3577.1

Hladik, D. and S. Tapio. (2016), "Effects of ionizing radiation on the mammalian brain", Mutation Research - Reviews in Mutation Research, Vol. 770, Elsevier B.V., Amsterdam, https://doi.org/10.1016/j.mrrev.2016.08.003.

Huang, Y. et al. (2021), "Mesenchymal Stem Cell-Conditioned Medium Protects Hippocampal Neurons From Radiation Damage by Suppressing Oxidative Stress and Apoptosis", Dose-Response, Vol. 19/1, SAGE publications, https://doi.org/10.1177/1559325820984944.

Hua, H. et al. (2019), "Protective effects of lanosterol synthase up-regulation in UV-B-induced oxidative stress", Frontiers in pharmacology, Vol. 10, Frontiers Media SA, Lausanne, https://doi.org/10.3389/fphar.2019.00947.

Hunsberger, H. C. et al. (2019), "The role of APOE4 in Alzheimer's disease: strategies for future therapeutic interventions", Neuronal Signaling, Vol. 3/2, Portland Press, London, https://doi.org/10.1042/NS20180203.

Hwang, S. Y. et al. (2006), "Ionizing radiation induces astrocyte gliosis through microglia activation", Neurobiology of Disease, Vol. 21/3, Academic Press, https://doi.org/10.1016/j.nbd.2005.08.006.

International commission on Radiological Protection (ICRP). (2007), "The 2007 recommendations of the International Commission on Radiological Protection.", Ann ICRP 37, ICRP Publication 103.

Ismail, A. F. and S. M. El-Sonbaty (2016), "Fermentation enhances Ginkgo biloba protective role on γ-irradiation induced neuroinflammatory gene expression and stress hormones in rat brain", Journal of photochemistry and photobiology. B, Biology, Vol. 158, Elsevier, Amsterdam, https://doi.org/10.1016/j.jphotobiol.2016.02.039.
Jenrow, K. A. et al. (2013), "Selective Inhibition of Microglia-Mediated Neuroinflammation Mitigates Radiation-Induced Cognitive Impairment", Radiation Research, Vol. 179/5, BioOne, https://doi.org/10.1667/RR3026.1.

Ji, J. et al. (2014), "Forced running exercise attenuates hippocampal neurogenesis impairment and the neurocognitive deficits induced by whole-brain irradiation via the BDNF-mediated pathway", Biochemical and Biophysical Research Communications, Vol. 443/2, Elsevier, Amsterdam, https://doi.org/10.1016/j.bbrc.2013.12.031.

Jiang, Q. et al. (2006), "UV radiation down-regulates Dsg-2 via Rac/NADPH oxidase-mediated generation of ROS in human lens epithelial cells", International Journal of Molecular Medicine, Vol. 18/2, Spandidos Publishing Ltd, Athens, https://doi.org/10.3892/ijmm.18.2.381.

Serment-Guerrero, J. et al. (2012), "Evidence of DNA double strand breaks formation in Escherichia coli bacteria exposed to alpha particles of different LET assessed by the SOS response", Applied Radiation and Isotopes, Vol. 71, Elsevier, Amsterdam, https://doi.org/10.1016/j.apradiso.2012.05.007.

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

Kang, L. et al. (2020), "Ganoderic acid A protects lens epithelial cells from UVB irradiation and delays lens opacity", Chinese journal of natural medicines, Vol. 18/12, Elsevier, Amsterdam, https://doi.org/10.1016/S1875-5364(20)60037-1.

Kanzawa, T. et al. (2006), "Ionizing radiation induces apoptosis and inhibits neuronal differentiation in rat neural stem cells via the c-Jun NH2-terminal kinase (JNK) pathway", Oncogene, Vol. 25/26, Springer Nature, https://doi.org/10.1038/sj.onc.1209414.

Karimi, N. et al. (2017), "Radioprotective effect of hesperidin on reducing oxidative stress in the lens tissue of rats", International Journal of Pharmaceutical Investigation, Vol. 7/3, Phcog Net, Bengaluru, https://doi.org/10.4103/jphi.JPHI_60_17.

Katsura, M. et al. (2021), "Recognizing Radiation-induced Changes in the Central Nervous System: Where to Look and What to Look For", RadioGraphics, Vol. 41/1, https://doi.org/10.1148/rg.2021200064.

Kiffer, F. et al. (2019a), "Late Effects of 16O-Particle Radiation on Female Social and Cognitive Behavior and Hippocampal Physiology", Radiation Research, Vol. 191/3, BioOne, Washington, https://doi.org/10.1667/RR15092.1.

Kiffer, F., M. Boerma and A. Allen. (2019b), "Behavioral effects of space radiation: A comprehensive review of animal studies", Life Sciences in Space Research, Vol. 21, Elsevier, Amsterdam, https://doi.org/10.1016/j.lssr.2019.02.004.

Komatsu, W. et al. (2017), "Nasunin inhibits the lipopolysaccharide-induced pro-inflammatory mediator production in RAW264 mouse macrophages by suppressing ROS-mediated activation of PI3 K/Akt/NF-κB and p38 signaling pathways", Bioscience, Biotechnology, and Biochemistry, Vol. 81/10, Elsevier, https://doi.org/10.1080/09168451.2017.1362973

Kozbenko, T. et al. (2022), "Deploying elements of scoping review methods for adverse outcome pathway development: a space travel case example", International Journal of Radiation Biology, Vol. 98/12, https://doi.org/10.1080/09553002.2022.2110306.

Krukowski, K. et al. (2018a), "Female mice are protected from space radiation-induced maladaptive responses", Brain, Behavior, and Immunity, Vol. 74, Academic Press Inc., https://doi.org/10.1016/j.bbi.2018.08.008.
Kyrkanides, S. et al. (1999), "TNFα and IL-1β mediate intercellular adhesion molecule-1 induction via microglia-astrocyte interaction in CNS radiation injury", Journal of Neuroimmunology, Vol. 95/1–2, Elsevier, Amsterdam, https://doi.org/10.1016/S0165-5728(98)00270-7.

Kyrkanides, S. et al. (2002), "Cyclooxygenase-2 modulates brain inflammation-related gene expression in central nervous system radiation injury", Molecular Brain Research, Vol. 104/2, Elsevier, https://doi.org/10.1016/S0169-328X(02)00353-4.

Lawrence, T. & Gilroy D. W. (2007) "Chronic inflammation: a failure of resolution?" International journal of experimental pathology, Vol. 88/2, John Wiley & Sons, Hoboken, https://doi.org/10.1111/j.1365-2613.2006.00507.x.

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.

Lee, K., A. Lee and I. Choi. (2017), "Melandrii Herba Extract Attenuates H2O2-Induced Neurotoxicity in Human Neuroblastoma SH-SY5Y Cells and Scopolamine-Induced Memory Impairment in Mice", Molecules, Vol. 22/10, MDPI, Basel, https://doi.org/10.3390/molecules22101646.

Lee, K. H., M. Cha and B. H. Lee. (2021), "Crosstalk between Neuron and Glial Cells in Oxidative Injury and Neuroprotection", International Journal of Molecular Sciences, Vol. 22/24, https://doi.org/10.3390/ijms222413315.

Lehtinen, M. and A. Bonni. (2006), "Modeling Oxidative Stress in the Central Nervous System", Current Molecular Medicine, Vol. 6/8, https://doi.org/10.2174/156652406779010786.

Li, J. et al. (2013), "Oxidative Stress and Neurodegenerative Disorders", International Journal of Molecular Sciences, Vol. 14/12, https://doi.org/10.3390/ijms141224438.

Liguori, I. et al. (2018), "Oxidative stress, aging, and diseases", Clinical Interventions in Aging, Vol.13, https://doi.org/10.2147/CIA.S158513.

Limoli, C. L. et al. (2004), "Radiation response of neural precursor cells: linking cellular sensitivity to cell cycle checkpoints, apoptosis and oxidative stress", Radiation research, Vol. 161/1, Radiation Research Society, Bozeman, https://doi.org/10.1667/rr3112.

Limoli, C. L. et al. (2007), "Redox changes induced in hippocampal precursor cells by heavy ion irradiation", Radiation and environmental biophysics, Vol. 46/2, Springer, London, https://doi.org/10.1007/s00411-006-0077-9.

Liu, J. L. et al. (2010), "Tamoxifen alleviates irradiation-induced brain injury by attenuating microglial inflammatory response in vitro and in vivo", Brain Research, Vol. 1316, Elsevier B.V., https://doi.org/10.1016/j.brainres.2009.12.055.

Long, H.-Z. et al. (2021), "PI3K/AKT Signal Pathway: A Target of Natural Products in the Prevention and Treatment of Alzheimer's Disease and Parkinson's Disease", Frontiers in Pharmacology, Vol. 12, Frontiers, https://doi.org/10.3389/fphar.2021.648636.

Madsen, T. M. et al. (2003), "Arrested neuronal proliferation and impaired hippocampal function following fractionated brain irradiation in the adult rat", Neuroscience, Vol. 119/3, Elsevier Ltd, https://doi.org/10.1016/S0306-4522(03)00199-4.

Manda, K. et al. (2007a), "Melatonin attenuates radiation-induced learning deficit and brain oxidative stress in mice", Acta neurobiologiae experimentalis, Vol. 67/1, Nencki Institute of Experimental Biology, Warsaw, pp. 63–70.

Manda, K. et al. (2007b), "Radiation-induced cognitive dysfunction and cerebellar oxidative stress in mice: Protective effect of α-lipoic acid", Behavioural Brain Research, Vol. 177/1, Elsevier, Amsterdam, https://doi.org/10.1016/j.bbr.2006.11.013.
Manda, K., M. Ueno and K. Anzai (2008), "Memory impairment, oxidative damage and apoptosis induced by space radiation: ameliorative potential of alpha-lipoic acid", *Behavioural brain research*, Vol. 187/2, Elsevier, Amsterdam, https://doi.org/10.1016/j.bbr.2007.09.033.

Mazzucchelli, C. and R. Brambilla. (2000), "Ras-related and MAPK signalling in neuronal plasticity and memory formation", *Cellular and Molecular Life Sciences*, Vol. 57/4, Springer Nature, https://doi.org/10.1007/PL00000722.

McHugh, D. and J. Gil. (2018), "Senescence and aging: Causes, consequences, and therapeutic avenues", *Journal of Cell Biology*, Vol. 217/1, Rockefeller University Press, New York, https://doi.org/10.1083/jcb.201708092.

Mielke, K. and T. Herdegen. (2000), "JNK and p38 stresskinases — degenerative effectors of signal-transduction-cascades in the nervous system", *Progress in Neurobiology*, Vol. 61/1, Elsevier, Amsterdam, https://doi.org/10.1016/S0301-0082(99)00042-8.

Mosconi, M. et al. (2011), "53BP1 and MDC1 foci formation in HT-1080 cells for low- and high-LET microbeam irradiations", *Radiation and Environmental Biophysics*, Vol. 50/3, Springer Nature, Berlin, https://doi.org/10.1007/s00411-011-0366-9.

Monje, M. L. and T. Palmer. (2003), "Radiation injury and neurogenesis", *Current Opinion in Neurology*, Vol. 16/2, Ovid Technologies (Wolters Kluwer Health), https://doi.org/10.1097/01.wco.0000063772.81810.b7.

Mousa, A. and M. Bakhiet. (2013), "Role of Cytokine Signaling during Nervous System Development", *International Journal of Molecular Sciences*, Vol. 14/7, MDPI, Basel, https://doi.org/10.3390/ijms140713931.

Nagane, M. et al. (2021), "DNA damage response in vascular endothelial senescence: Implication for radiation-induced cardiovascular diseases", *Journal of Radiation Research*, Vol. 62/4, Oxford University Press, Oxford, https://doi.org/10.1093/jrr/rrab032

Nathan, C. and A. Ding. (2010) "Nonresolving inflammation." *Cell*, Vol. 140/6, Cell press, Cambridge, https://doi.org/10.1016/j.cell.2010.02.029

National Council on Radiation Protection and Measures (NCRP). (2016). *Commentary No. 25 – Potential for central nervous system effects from radiation exposure during space activities phase I: Overview*.

Nikjoo, H. et al. (2001), "Computational approach for determining the spectrum of DNA damage induced by ionizing radiation.", *Radiation Research*, Vol. 156/5 Pt 2, BioOne, Washington, https://doi.org/10.1667/0033-7587(2001)156[0577:cafdts]2.0.co;2

Nikjoo, H. et al. (2016), "Radiation track, DNA damage and response—a review", *Reports on Progress in Physics*, Vol. 79/11, IOP Publishing, Bristol, https://doi.org/10.1088/0034-4885/79/11/116601.

Nebreda, A. R. and A. Porras. (2000), "p38 MAP kinases: beyond the stress response", *Trends in Biochemical Sciences*, Vol. 25/6, Elsevier, Amsterdam, https://doi.org/10.1016/S0968-0004(00)01595-4.

Parihar, V. K. et al. (2016), "Cosmic radiation exposure and persistent cognitive dysfunction", *Scientific Reports*, Vol. 6/1, Nature Publishing Group, https://doi.org/10.1038/srep34774.

Parihar, V. K. et al. (2018), "Persistent nature of alterations in cognition and neuronal circuit excitability after exposure to simulated cosmic radiation in mice", *Experimental Neurology*, Vol. 305, Elsevier B.V., https://doi.org/10.1016/j.expneurol.2018.03.009.

Parihar, V. K. et al. (2020), "Sex-Specific Cognitive Deficits Following Space Radiation Exposure", *Frontiers in behavioral neuroscience*, Vol. 14, Frontiers, https://doi.org/10.3389/fnbeh.2020.535885.
Park, D. H. et al. (2021), "Neuroprotective Effect of Gallocatechin Gallate on Glutamate-Induced Oxidative Stress in Hippocampal HT22 Cells", Molecules, Vol. 26/5, MDPI, Basel, https://doi.org/10.3390/molecules26051387.

Patterson, S. L. (2015), "Immune dysregulation and cognitive vulnerability in the aging brain: Interactions of microglia, IL-1β, BDNF and synaptic plasticity", Neuropharmacology, Vol. 96, Elsevier B.V., https://doi.org/10.1016/j.neuropharm.2014.12.020.

Ping, Z. et al. (2020), "Oxidative Stress in Radiation-Induced Cardiotoxicity", Oxidative Medicine and Cellular Longevity, Vol. 2020, Hindawi, London, https://doi.org/10.1155/2020/3579143

Pius-Sadowska, E. et al. (2016), "Alteration of Selected Neurotrophic Factors and their Receptor Expression in Mouse Brain Response to Whole-Brain Irradiation", Radiation Research, Vol. 186/5, BioOne, https://doi.org/10.1667/RR14457.1.

Prieto, G. A. and C. W. Cotman. (2017), "Cytokines and cytokine networks target neurons to modulate long-term potentiation", Cytokine & Growth Factor Reviews, Vol. 34, Elsevier, Amsterdam, https://doi.org/10.1016/j.cytogfr.2017.03.005.

Raber, J. et al. (2004), "Radiation-induced cognitive impairments are associated with changes in indicators of hippocampal neurogenesis", Radiation Research, Vol. 162/1, Allen Press, https://doi.org/10.1667/RR3206.

Raber, J. et al. (2019), "Combined Effects of Three High-Energy Charged Particle Beams Important for Space Flight on Brain, Behavioral and Cognitive Endpoints in B6D2F1 Female and Male Mice", Frontiers in physiology, Vol. 10, Frontiers, https://doi.org/10.3389/fphys.2019.00179.

Rai, S. N. et al. (2019), "The Role of PI3K/Akt and ERK in Neurodegenerative Disorders", Neurotoxicity Research, Vol. 35/3, Elsevier, Amsterdam, https://doi.org/10.1007/s12640-019-0003-y.

Ramalingam, M. and S.-J. Kim. (2012), "Reactive oxygen/nitrogen species and their functional correlations in neurodegenerative diseases", Journal of Neural Transmission, Vol. 119/8, Springer Nature, Berlin, https://doi.org/10.1007/s00702-011-0758-7.

Ramanan, S. et al. (2008), "PPARα ligands inhibit radiation-induced microglial inflammatory responses by negatively regulating NF-κB and AP-1 pathways", Free Radical Biology and Medicine, Vol. 45/12, Elsevier B.V., https://doi.org/10.1016/j.freeradbiomed.2008.09.002.

Rodgers, E. E. and A. B. Theibert. (2002), "Functions of PI 3-kinase in development of the nervous system", International Journal of Developmental Neuroscience, Vol. 20/3-5, Wiley, https://doi.org/10.1016/S0736-5748(02)00047-3.

Rogakou, E. P. et al. (1999), "Megabase Chromatin Domains Involved in DNA Double-Strand Breaks in Vivo", Journal of Cell Biology, Vol. 146/5, Rockefeller University Press, New York, https://doi.org/10.1083/jcb.146.5.905.

Rola, R. et al. (2004), "Radiation-induced impairment of hippocampal neurogenesis is associated with cognitive deficits in young mice", Experimental Neurology, Vol. 188/2, Academic Press Inc., https://doi.org/10.1016/j.expneurol.2004.05.005.

Romanella, S. M. et al. (2020), "Noninvasive Brain Stimulation & Space Exploration: Opportunities and Challenges", Neuroscience & Biobehavioral Reviews, Vol. 119, https://doi.org/10.1016/j.neubiorev.2020.09.005.

Rothkamm, K. and M. Löbrich. (2003), "Evidence for a lack of DNA double-strand break repair in human cells exposed to very low x-ray doses", Proceedings of the National Academy of Sciences, Vol. 100/9, National Academy of Sciences, https://doi.org/10.1073/pnas.0830918100.

Rübe, C. E. et al. (2008), "DNA Double-Strand Break Repair of Blood Lymphocytes and Normal Tissues Analysed in a Preclinical Mouse Model: Implications for Radiosensitivity Testing", Clinical
Cancer Research, Vol. 14/20, American Association for Cancer Research, Washington, https://doi.org/10.1158/1078-0432.CCR-07-5147.

Ryan, S. M. et al. (2013), "Negative regulation of TLX by IL-1β correlates with an inhibition of adult hippocampal neural precursor cell proliferation", Brain, Behavior, and Immunity, Vol. 33, Elsevier, Amsterdam, https://doi.org/10.1016/j.bbi.2013.03.005.

Sabirzhanov, B. et al. (2020), "Irradiation-Induced Upregulation of miR-711 Inhibits DNA Repair and Promotes Neurodegeneration Pathways", International Journal of Molecular Sciences, Vol. 21/15, Multidisciplinary Digital Publishing Institute (MDPI) AG, Basel, https://doi.org/10.3390/ijms21155239.

Saraiva, C. et al. (2019), "Histamine modulates hippocampal inflammation and neurogenesis in adult mice", Scientific Reports, Vol. 9/1, Springer Nature, Berlin, https://doi.org/10.1038/s41598-019-44816-w.

Schmidt-Ullrich, R. K. et al. (2000), "Signal transduction and cellular radiation responses.", Radiation research, Vol. 153/3, BioOne, https://doi.org/10.1667/0033-7587(2000)153[0245:stacrr]2.0.co;2

Schnegg, C. I. et al. (2012), "PPARδ prevents radiation-induced proinflammatory responses in microglia via transrepression of NF-κB and inhibition of the PKCα/MEK1/2/ERK1/2/AP-1 pathway", Free Radical Biology and Medicine, Vol. 52/9, Pergamon, https://doi.org/10.1016/j.FREERADBIOMED.2012.02.032.

Sherrin, T., T. Blank and C. Todorovic. (2011), "c-Jun N-terminal kinases in memory and synaptic plasticity", Reviews in the Neurosciences, Vol. 22/4, De Gruyter, https://doi.org/10.1515/rns.2011.032.

Shi, Q. et al. (2017), "Complement C3 deficiency protects against neurodegeneration in aged plaque-rich APP/PS1 mice", Science Translational Medicine, Vol. 9/392, American Association for the Advancement of Science, Washington, https://doi.org/10.1126/scitranslmed.aaf6295.

Simpson, D. S. A. and P. L. Oliver. (2020), "ROS Generation in Microglia: Understanding Oxidative Stress and Inflammation in Neurodegenerative Disease", Antioxidants, Vol. 9/8, https://doi.org/10.3390/antiox9080743.

Slezak, J. et al. (2017), "Potential markers and metabolic processes involved in the mechanism of radiation-induced heart injury", Canadian journal of physiology and pharmacology, Vol. 95/10, Canadian Science Publishing, Ottawa, https://doi.org/10.1139/cjpp-2017-0121.

Sutherland, B. M. et al. (2000), "Clustered DNA damages induced in isolated DNA and in human cells by low doses of ionizing radiation", Proceedings of the National Academy of Sciences, Vol. 97/1, National Academy of Sciences, https://doi.org/10.1073/pnas.97.1.103.

Suman, S. et al. (2013), "Therapeutic and space radiation exposure of mouse brain causes impaired DNA repair response and premature senescence by chronic oxidant production", Aging, Vol. 5/8, Impact Journals, Orchard Park, https://doi.org/10.18632/aging.100587.

Taepavarapruk, P. and C. Song. (2010), "Reductions of acetylcholine release and nerve growth factor expression are correlated with memory impairment induced by interleukin-1β administrations: effects of omega-3 fatty acid EPA treatment", Journal of Neurochemistry, Vol. 112/4, Wiley https://doi.org/10.1111/j.1471-4159.2009.06524.x.

Tan, H. et al. (2014), "Critical role of inflammatory cytokines in impairing biochemical processes for learning and memory after surgery in rats", Journal of Neuroinflammation, Vol. 11/1, Springer Nature, https://doi.org/10.1186/1742-2094-11-93.

Tian, R. et al. (2020), "miR-137 prevents inflammatory response, oxidative stress, neuronal injury and cognitive impairment via blockade of Src-mediated MAPK signaling pathway in ischemic stroke", Aging, Vol. 12/11, https://doi.org/10.18632/aging.103301.
Tomé, W. A. et al. (2015), "Hippocampal-dependent neurocognitive impairment following cranial irradiation observed in pre-clinical models: current knowledge and possible future directions", The British Journal of Radiobiology, Vol. 89/1057, British Institute of Radiology, https://doi.org/10.1259/bjr.20150762.

Toricelli, M., Pereira, A. A. R., Souza Abrao, G., Malerba, H. N., Maia, J., Buck, H. S., & Viel, T. A. (2021). Mechanisms of neuroplasticity and brain degeneration: strategies for protection during the aging process. Neural regeneration research, 16(1), 58-67. https://doi.org/10.4103/1673-5374.286952.

Turnquist, C., B. T. Harris and C. C. Harris. (2020), "Radiation-induced brain injury: current concepts and therapeutic strategies targeting neuroinflammation", Neuro-Oncology Advances, Vol. 2/1, Oxford University Press, Oxford, https://doi.org/10.1093/noajnl/vdaa057.

United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR). (2008), "Sources and effects of ionizing radiation", UNSCEAR 2008 Report, Vol 1, UN Publications.

Valerie, K. et al. (2007), "Radiation-induced cell signaling: inside-out and outside-in", Molecular Cancer Therapeutics, Vol. 6/3, American Association for Cancer Research, https://doi.org/10.1158/1535-7163.MCT-06-0596

Valliéres, L. et al. (2002), "Reduced hippocampal neurogenesis in adult transgenic mice with chronic astrocytic production of interleukin-6", Journal of Neuroscience, Vol. 22/2, Society for Neuroscience, Washington, https://doi.org/10.1523/jneurosci.22-02-00486.2002.

van Neerven, S. et al. (2010), "Inflammatory cytokine release of astrocytes in vitro is reduced by all-trans retinoic acid", Journal of Neuroimmunology, Vol. 229/1-2, Elsevier B.V., https://doi.org/10.1016/j.jneuroim.2010.08.005.

Wang, Y. L. et al. (2017), "Protective Effect of Curcumin Against Oxidative Stress-Induced Injury in Rats with Parkinson's Disease Through the Wnt/ β-Catenin Signaling Pathway", Cellular Physiology and Biochemistry, Vol. 43/6, https://doi.org/10.1159/000484302.

Wang, H. et al. (2019a), "Radiation-induced heart disease: a review of classification, mechanism and prevention", International Journal of Biological Sciences, Vol. 15/10, Ivyspring International Publisher, Sydney, https://doi.org/10.7150/ijbs.35460.

Whoolery, C. W. et al. (2017), "Whole-body exposure to 28Si-radiation dose-dependently disrupts dentate gyrus neurogenesis and proliferation in the short term and new neuron survival and contextual fear conditioning in the long term", Radiation Research, Vol. 188/5, Radiation Research Society, https://doi.org/10.1667/RR14797.1.

Wilkinson, B., Hill, M.A., and Parsons, J.L. (2023), "The Cellular Response to Complex DNA Damage Induced by Ionising Radiation" International Journal of Molecular Sciences Vol. 24/4920, Multidisciplinary Digital Publishing Institute (MDPI) AG, Basel, http://doi.org/10.3390/ijms24054920.

Winocur, G. et al. (2006), "Inhibition of neurogenesis interferes with hippocampus-dependent memory function", Hippocampus, Vol. 16/3, https://doi.org/10.1002/HIPO.20163.

Wong, G., Y. Goldshmit and A. M. Turnley. (2004), "Interferon-γ but not TNFα promotes neuronal differentiation and neurite outgrowth of murine adult neural stem cells", Experimental Neurology, Vol. 187/1, Elsevier, Amsterdam, https://doi.org/10.1016/j.expneurol.2004.01.009.

Wu, M. D. et al. (2012), "Adult murine hippocampal neurogenesis is inhibited by sustained IL-1β and not rescued by voluntary running", Brain, Behavior, and Immunity, Vol. 26/2, Elsevier Inc., Amsterdam, https://doi.org/10.1016/j.bbi.2011.09.012.

Xu, B. et al. (2019), "Oxidation Stress-Mediated MAPK Signaling Pathway Activation Induces Neuronal Loss in the CA1 and CA3 Regions of the Hippocampus of Mice Following Chronic Cold Exposure", Brain Sciences, Vol. 9/10, MDPI, Basel, https://doi.org/10.3390/brainsci9100273.
Yang, H. et al. (2020), "Cytoprotective role of humanin in lens epithelial cell oxidative stress-induced injury", Molecular medicine reports, Vol. 22/2, Spandidos Publishing Ltd, Athens, https://doi.org/10.3892/mmr.2020.11202.

Zanni, G. et al. (2015), "Lithium increases proliferation of hippocampal neural stem/progenitor cells and rescues irradiation-induced cell cycle arrest in vitro", Oncotarget, Vol. 6/35, https://doi.org/10.18632/oncotarget.5191.

Zhang, L. et al. (2017), "The inhibitory effect of minocycline on radiation-induced neuronal apoptosis via AMPKα1 signaling-mediated autophagy", Scientific Reports, Vol. 7/1, Springer Nature, Berlin, https://doi.org/10.1038/s41598-017-16693-8.

Zhang, Y. et al. (2017), "Kukoamine A Prevents Radiation-Induced Neuroinflammation and Preserves Hippocampal Neurogenesis in Rats by Inhibiting Activation of NF-κB and AP-1", Neurotoxicity Research, Vol. 31/2, https://doi.org/10.1007/s12640-016-9679-4.

Zhang, Q. et al. (2018), "The effect of brain-derived neurotrophic factor on radiation-induced neuron architecture impairment is associated with the NFATc4/3 pathway", Brain Research, Vol. 1681, Elsevier, Amsterdam, https://doi.org/10.1016/j.brainres.2017.12.032.

Zhao, Z.-Y. et al. (2013), "Edaravone Protects HT22 Neurons from H 2 O 2 -induced Apoptosis by Inhibiting the MAPK Signaling Pathway", CNS Neuroscience & Therapeutics, Vol. 19/3, John Wiley & Sons, Hoboken, https://doi.org/10.1111/cns.12044.

Zhao, D. et al. (2017), "Anti-Neuroinflammatory Effects of Fucoxanthin via Inhibition of Akt/NF-κB and MAPKs/AP-1 Pathways and Activation of PKA/CREB Pathway in Lipopolysaccharide-Activated BV-2 Microglial Cells", Neurochemical Research, Vol. 42/2, Springer Nature, Berlin, https://doi.org/10.1007/s11064-016-2123-6.

Zhou, K. et al. (2017), "Radiation induces progenitor cell death, microglia activation, and blood-brain barrier damage in the juvenile rat cerebellum", Scientific Reports, Vol. 7, Springer Nature, London, https://doi.org/10.1038/srep46181.

Zhu, Y. et al. (2012), "APOE genotype alters glial activation and loss of synaptic markers in mice", Glia, Vol. 60/4, John Wiley & Sons, Inc., Hoboken, https://doi.org/10.1002/glia.22289.

Zigman, S. et al. (1995), "Damage to cultured lens epithelial cells of squirrels and rabbits by UV-A (99.9%) plus UV-B (0.1%) radiation and alpha tocopherol protection", Molecular and cellular biochemistry, Vol. 143, Springer, London, https://doi.org/10.1007/BF00925924.

Zonis, S. et al. (2015), "Chronic intestinal inflammation alters hippocampal neurogenesis", Journal of Neuroinflammation, Vol. 12/1, Springer Nature, Berlin, https://doi.org/10.1186/s12974-015-0281-0.
## List of MIEs in this AOP

**Event:** 1686: Deposition of Energy

**Short Name:** Energy Deposition

**Key Event Component**

<table><thead><tr><td>Process</td><td>Object</td><td>Action</td></tr></thead><tbody><tr><td>energy deposition event</td><td></td><td>increased</td></tr></tbody></table>

## AOPs Including This Key Event

<table><thead><tr><td>AOP ID and Name</td><td>Event Type</td></tr></thead><tbody><tr><td>AOP:272 - Deposition of energy leading to lung cancer</td><td>Molecular Initiating Event</td></tr><tr><td>AOP:432 - Deposition of Energy by Ionizing Radiation leading to Acute Myeloid Leukemia</td><td>Molecular Initiating Event</td></tr><tr><td>AOP:386 - Deposition of ionizing energy leading to population decline via inhibition of photosynthesis</td><td>Molecular Initiating Event</td></tr><tr><td>AOP:387 - Deposition of ionizing energy leading to population decline via mitochondrial dysfunction</td><td>Molecular Initiating Event</td></tr><tr><td>AOP:388 - Deposition of ionising energy leading to population decline via programmed cell death</td><td>Molecular Initiating Event</td></tr><tr><td>AOP:435 - Deposition of ionizing energy leads to population decline via pollen abnormal</td><td>Molecular Initiating Event</td></tr><tr><td>AOP:216 - Deposition of energy leading to population decline via DNA strand breaks and follicular atresia</td><td>Molecular Initiating Event</td></tr><tr><td>AOP:238 - Deposition of energy leading to population decline via DNA strand breaks and oocyte apoptosis</td><td>Molecular Initiating Event</td></tr><tr><td>AOP:311 - Deposition of energy leading to population decline via DNA oxidation and oocyte apoptosis</td><td>Molecular Initiating Event</td></tr><tr><td>AOP:299 - Deposition of energy leading to population decline via DNA oxidation and follicular atresia</td><td>Molecular Initiating Event</td></tr><tr><td>AOP:441 - Ionizing radiation-induced DNA damage leads to microcephaly via apoptosis and premature cell differentiation</td><td>Molecular Initiating Event</td></tr><tr><td>AOP:444 - Ionizing radiation leads to reduced reproduction in Eisenia fetida via reduced spermatogenesis and cocoon hatchability</td><td>Molecular Initiating Event</td></tr><tr><td>AOP:470 - Deposition of energy leads to abnormal vascular remodeling</td><td>Molecular Initiating Event</td></tr><tr><td>AOP:473 - Energy deposition from internalized Ra-226 decay lower oxygen binding capacity of hemocyanin</td><td>Molecular Initiating Event</td></tr><tr><td>AOP:478 - Deposition of energy leading to occurrence of cataracts</td><td>Molecular Initiating Event</td></tr><tr><td>AOP:482 - Deposition of energy leading to occurrence of bone loss</td><td>Molecular Initiating Event</td></tr><tr><td>AOP:483 - Deposition of Energy Leading to Learning and Memory Impairment</td><td>Molecular Initiating 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

Energy can be deposited into any substrate, both living and non-living; it is independent of age, taxa, sex, or life-stage.

## Taxonomic Applicability

This MIE is not taxonomically specific.
<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>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><tr><td>nematode</td><td>Caenorhabditis elegans</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>thale-cress</td><td>Arabidopsis thaliana</td><td>High</td><td>NCBI</td></tr><tr><td>Scotch pine</td><td>Pinus sylvestris</td><td>Moderate</td><td>NCBI</td></tr><tr><td>Daphnia magna</td><td>Daphnia magna</td><td>High</td><td>NCBI</td></tr><tr><td>Chlamydomonas reinhardtii</td><td>Chlamydomonas reinhardtii</td><td>Moderate</td><td>NCBI</td></tr><tr><td>common brandling worm</td><td>eisenia fetida</td><td>Moderate</td><td>NCBI</td></tr><tr><td>Lemna minor</td><td>Lemna minor</td><td>High</td><td>NCBI</td></tr><tr><td>Salmo salar</td><td>Salmo salar</td><td>Low</td><td>NCBI</td></tr></tbody></table>

## Life Stage Applicability

This MIE is not life stage specific.

<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 MIE is not sex specific.

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

## Key Event Description

Deposition of energy refers to events where energetic subatomic particles, nuclei, or electromagnetic radiation deposit energy in the media through which they transverse. The energy may either be sufficient (e.g. ionizing radiation) or insufficient (e.g. non-ionizing radiation) to ionize atoms or molecules (Beir et al., 1999).

Ionizing radiation can cause the ejection of electrons from atoms and molecules, thereby resulting in their ionization and the breakage of chemical bonds. The excitation of molecules can also occur without ionization. These events are stochastic and unpredictable. The energy of these subatomic particles or electromagnetic waves ranges from 124 keV to 5.4 MeV and is dependent on the source and type of radiation (Zyla et al., 2020). Not all electromagnetic radiation is ionizing; as the incident radiation must have sufficient energy to free electrons from the electron orbitals of the atom or molecule. The energy deposited can induce direct and indirect ionization events and can result from internal (injections, inhalation, ingestion) or external exposure.

Direct ionization is the principal path where charged particles interact with biological structures such as DNA, proteins or membranes to cause biological damage. Photons, which are electromagnetic waves can also deposit energy to cause direct which themselves can indirectly damage critical targets such as DNA (Beir et al., 1999; Balagamwala et al., 2013) or alter cellular processes. Given the fundamental nature of energy deposition by radioactive/unstable nuclei, nucleons or elementary particles in material, this process is universal to all biological contexts.

The spatial structure of ionizing energy deposition along the resulting particle track is represented as linear energy transfer (LET) (Hall and Giaccia, 2018 UNSCEAR, 2020). High LET refers to energy mostly above 10 keV µm-1 which produces more complex, dense structural damage than low LET radiation (below 10 keV µm-1). Low-LET particles produce sparse ionization events such as photons (X- and gamma rays), as well as high-energy protons. Low LET radiation travels farther into tissue but deposits smaller amounts of energy, whereas high LET radiation, which includes heavy ions, alpha particles and high-energy neutrons, does not travel as far but deposits larger amounts of energy into tissue at the same absorbed dose. The biological effect of the deposition of energy can be modulated by
varying dose and dose rate of exposure, such as acute, chronic, or fractionated exposures (Hall and Giaccia, 2018).

Non-ionizing radiation is electromagnetic waves that does not have enough energy to break bonds and induce ion formation but it can cause molecules to excite and vibrate faster resulting in biological effects. Examples of non-ionizing radiation include radio waves (wavelength: 100 km-1m), microwaves (wavelength: 1m-1mm), infrared radiation (wavelength: 1mm-1um), visible light (wavelengths: 400-700 nm), and ultraviolet radiation of longer wavelengths such as UVB (wavelengths: 315-400nm) and UVA (wavelengths: 280-315 nm)

## How it is Measured or Detected

<table><thead><tr><td>Radiation type</td><td>Assay Name</td><td>References</td><td>Description</td><td>OECD Approved Assay</td></tr></thead><tbody><tr><td>Ionizing radiation</td><td>Monte Carlo Simulations (eg. Geant4)</td><td>Douglass et al., 2013; Douglass et al., 2012; Zyla et al., 2020</td><td>Monte Carlo simulations are based on a computational algorithm that mathematically models the deposition of energy into materials.</td><td>No</td></tr><tr><td>Ionizing radiation</td><td>Fluorescent Nuclear Track Detector (FNTD)</td><td>Sawakuchi, 2016; Niklas, 2013; Kodaira & Konishi, 2015</td><td>FNTDs are biocompatible chips with crystals of aluminum oxide doped with carbon and magnesium; used in conjunction with fluorescent microscopy, these FNTDs allow for the visualization and the linear energy transfer (LET) quantification of tracks produced by the deposition of energy into a material.</td><td>No</td></tr><tr><td>Ionizing radiation</td><td>Tissue equivalent proportional counter (TEPC)</td><td>Straume et al, 2015</td><td>Measure the LET spectrum and calculate the equivalent dose</td><td>No</td></tr><tr><td>Ionizing radiation</td><td>alanine dosimeters/NanoDots</td><td>Lind et al. 2019<br>Xie et al., 2022</td><td>Alanine dosimeters use the amino acid alanine to detect radiation-induced changes, and nanodots leverage nano-scale technology to provide high precision and sensitivity in radiation dose measurements</td><td>No</td></tr><tr><td>Non-ionizing radiation</td><td>UV meters or radiometers</td><td>Xie et al., 2020</td><td>UVA/UVB (irradiance intensity), UV dosimeters (accumulated irradiance over time), Spectrophotometer (absorption of UV by a substance or material)</td><td>No</td></tr></tbody></table>
References

Balagamwala, E. H. et al. (2013), "Introduction to radiotherapy and standard teletherapy techniques", Dev Ophthalmol, Vol. 52, Karger, Basel, https://doi.org/10.1159/000351045

Beir, V. et al. (1999), "The Mechanistic Basis of Radon-Induced Lung Cancer", in Health Risks of Exposure to Radon: BEIR VI, National Academy Press, Washington, D.C., https://doi.org/10.17226/5499

Douglass, M. et al. (2013), "Monte Carlo investigation of the increased radiation deposition due to gold nanoparticles using kilovoltage and megavoltage photons in a 3D randomized cell model", Medical Physics, Vol. 40/7, American Institute of Physics, College Park, https://doi.org/10.1118/1.4808150

Douglass, M. et al. (2012), "Development of a randomized 3D cell model for Monte Carlo microdosimetry simulations.", Medical Physics, Vol. 39/6, American Institute of Physics, College Park, https://doi.org/10.1118/1.4719963

Hall, E. J. and Giaccia, A.J. (2018), Radiobiology for the Radiologist, 8th edition, Wolters Kluwer, Philadelphia.

Kodaira, S. and Konishi, T. (2015), "Co-visualization of DNA damage and ion traversals in live mammalian cells using a fluorescent nuclear track detector.", Journal of Radiation Research, Vol. 56/2, Oxford University Press, Oxford, https://doi.org/10.1093/jrr/rru091

Lind, O.C., D.H. Oughton and Salbu B. (2019), "The NMBU FIGARO low dose irradiation facility", International Journal of Radiation Biology, Vol. 95/1, Taylor & Francis, London, https://doi.org/10.1080/09553002.2018.1516906.

Sawakuchi, G.O. and Akselrod, M.S. (2016), "Nanoscale measurements of proton tracks using fluorescent nuclear track detectors.", Medical Physics, Vol. 43/5, American Institute of Physics, College Park, https://doi.org/10.1118/1.4947128

Straume, T. et al. (2015), "Compact Tissue-equivalent Proportional Counter for Deep Space Human Missions.", Health physics, Vol. 109/4, Lippincott Williams & Wilkins, Philadelphia, https://doi.org/10.1097/HP.0000000000000334

Niklas, M. et al. (2013), "Engineering cell-fluorescent ion track hybrid detectors.", Radiation Oncology, Vol. 8/104, BioMed Central, London, https://doi.org/10.1186/1748-717X-8-141

UNSCEAR (2020), Sources, effects and risks of ionizing radiation, United Nations.

Xie, Li. et al. (2022), "Ultraviolet B Modulates Gamma Radiation-Induced Stress Responses in Lemna Minor at Multiple Levels of Biological Organisation", SSRN, Elsevier, Amsterdam, http://dx.doi.org/10.2139/ssrn.4081705.

Zyla, P.A. et al. (2020), Review of particle physics: Progress of Theoretical and Experimental Physics, 2020 Edition, Oxford University Press, Oxford.
Event: 1392: Oxidative Stress

Short Name: Oxidative Stress

Key Event Component

<table><thead><tr><td>Process</td><td>Object</td><td>Action</td></tr></thead><tbody><tr><td>oxidative stress</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: 220 - Cyp21 Activation Leading to Liver Cancer</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>Key Event</td></tr><tr><td>AOP: 284 - Binding of electrophilic chemicals to SH(thiol)-group of proteins and /or to seleno-proteins involved in protection against oxidative stress leads to chronic kidney disease</td><td>Key Event</td></tr><tr><td>AOP: 377 - Dysregulated prolonged Toll Like Receptor 9 (TLR9) activation leading to Multi Organ Failure involving Acute Respiratory Distress Syndrome (ARDS)</td><td>Key Event</td></tr><tr><td>AOP: 411 - Oxidative stress Leading to Decreased Lung Function</td><td>Molecular Initiating Event</td></tr><tr><td>AOP: 424 - Oxidative stress Leading to Decreased Lung Function via CFTR dysfunction</td><td>Molecular Initiating Event</td></tr><tr><td>AOP: 425 - Oxidative Stress Leading to Decreased Lung Function via Decreased FOXJ1</td><td>Molecular Initiating Event</td></tr><tr><td>AOP: 429 - A cholesterol/glucose dysmetabolism initiated Tau-driven AOP toward memory loss (AO) in sporadic Alzheimer's Disease with plausible MIE's plug-ins for environmental neurotoxicants</td><td>Key Event</td></tr><tr><td>AOP: 452 - Adverse outcome pathway of PM-induced respiratory toxicity</td><td>Key Event</td></tr><tr><td>AOP: 464 - Calcium overload in dopaminergic neurons of the substantia nigra leading to parkinsonian motor deficits</td><td>Key Event</td></tr><tr><td>AOP: 470 - Deposition of energy leads to abnormal vascular remodeling</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: 479 - Mitochondrial complexes inhibition leading to left ventricular function decrease via increased myocardial oxidative stress</td><td>Key Event</td></tr><tr><td>AOP: 481 - AOPs of amorphous silica nanoparticles: ROS-mediated oxidative stress increased respiratory dysfunction and diseases.</td><td>Key Event</td></tr><tr><td>AOP: 482 - Deposition of energy leading to occurrence of bone loss</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: 505 - Reactive Oxygen Species (ROS) formation leads to cancer via inflammation pathway</td><td>Key Event</td></tr><tr><td>AOP: 521 - Essential element imbalance leads to reproductive failure via oxidative stress</td><td>Key Event</td></tr><tr><td>AOP: 26 - Calcium-mediated neuronal ROS production and energy imbalance</td><td>Adverse Outcome</td></tr><tr><td>AOP: 488 - Increased reactive oxygen species production leading to decreased cognitive function</td><td>Key Event</td></tr><tr><td>AOP: 396 - Deposition of ionizing energy leads to population decline via impaired meiosis</td><td>Key Event</td></tr><tr><td>AOP: 437 - Inhibition of mitochondrial electron transport chain (ETC) complexes leading to kidney toxicity</td><td>Key Event</td></tr><tr><td>AOP: 535 - Binding and activation of GPER leading to learning and memory impairments</td><td>Key Event</td></tr><tr><td>AOP: 171 - Chronic cytotoxicity of the serous membrane leading to pleural/peritoneal mesotheliomas in the rat.</td><td>Key Event</td></tr><tr><td>AOP: 138 - Organic anion transporter (OAT1) inhibition leading to renal failure and mortality</td><td>Key Event</td></tr><tr><td>AOP: 177 - Cyclooxygenase 1 (COX1) inhibition leading to renal failure and mortality</td><td>Key Event</td></tr><tr><td>AOP: 186 - unknown MIE leading to renal failure and mortality</td><td>Key Event</td></tr><tr><td>AOP: 200 - Estrogen receptor activation leading to breast cancer</td><td>Key Event</td></tr><tr><td>AOP: 444 - Ionizing radiation leads to reduced reproduction in Eisenia fetida via reduced spermatogenesis and cocoon hatchability</td><td>Key Event</td></tr><tr><td>AOP: 447 - Kidney failure induced by inhibition of mitochondrial electron transfer chain through apoptosis, inflammation and oxidative stress pathways</td><td>Key Event</td></tr><tr><td>AOP: 476 - Adverse Outcome Pathways diagram related to PBDEs associated male reproductive toxicity</td><td>Key Event</td></tr><tr><td>AOP: 497 - ERa inactivation alters mitochondrial functions and insulin signalling in skeletal muscle and leads to insulin resistance and metabolic syndrome</td><td>Key Event</td></tr></tbody></table>
<table><tr><td>AOP: 457 - Succinate dehydrogenase inhibition leading to increased insulin resistance through reduction in circulating thyroxine</td><td>Key Event</td></tr><tr><td>AOP: 459 - AhR activation in the thyroid leading to Subsequent Adverse Neurodevelopmental Outcomes in Mammals</td><td>Key Event</td></tr><tr><td>AOP: 507 - Nrf2 inhibition leading to vascular disrupting effects via inflammation pathway</td><td>Key Event</td></tr><tr><td>AOP: 459 - Nrf2 inhibition leading to vascular disrupting effects through activating apoptosis signal pathway and mitochondrial dysfunction</td><td>Key Event</td></tr><tr><td>AOP: 510 - Demethylation of PPAR promotor leading to vascular disrupting effects</td><td>Key Event</td></tr><tr><td>AOP: 511 - The AOP framework on ROS-mediated oxidative stress induced vascular disrupting effects</td><td>Key Event</td></tr><tr><td>AOP: 538 - Adverse outcome pathway of PFAS-induced vascular disrupting effects via activating oxidative stress related pathways</td><td>Key Event</td></tr><tr><td>AOP: 260 - CYP2E1 activation and formation of protein adducts leading to neurodegeneration</td><td>Key Event</td></tr><tr><td>AOP: 450 - Inhibition of AChE and activation of CYP2E1 leading to sensory axonal peripheral neuropathy and mortality</td><td>Key Event</td></tr><tr><td>AOP: 501 - Excessive iron accumulation leading to neurological disorders</td><td>Key Event</td></tr><tr><td>AOP: 540 - Oxidative Stress in the Fish Ovary Leads to Reproductive Impairment via Reduced Vitellogenin Production</td><td>Key Event</td></tr><tr><td>AOP: 471 - Various neuronal effects induced by elavl3, sox10, and mbp</td><td>Key Event</td></tr><tr><td>AOP: 31 - Oxidation of iron in hemoglobin leading to hematotoxicity</td><td>Key Event</td></tr><tr><td>AOP: 534 - Succinate dehydrogenase (SDH) inhibition leads to cancer through oxidative stress</td><td>Key Event</td></tr></table>

## Biological context

Level of Biological Organization

Molecular

## Domain of Applicability

### Taxonomic Applicability

Occurrence of oxidative stress is not species specific.

<table><thead><tr><td>Term</td><td>Scientific Term</td><td>Evidence</td><td>Link</td></tr></thead><tbody><tr><td>rodents</td><td>rodents</td><td>High</td><td>NCBI</td></tr><tr><td>Homo sapiens</td><td>Homo sapiens</td><td>High</td><td>NCBI</td></tr></tbody></table>

### Life Stage Applicability

Occurrence of oxidative stress is not life stage specific

<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

Occurrence of oxidative stress is not sex specific

<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

Evidence for perturbation by prototypic stressor: There is evidence of the increase of oxidative stress following perturbation from a variety of stressors including exposure to ionizing radiation and altered gravity (Bai et al., 2020; Ungvari et al., 2013; Zhang et al., 2009).

## Key Event Description

Oxidative stress is defined as an imbalance in the production of reactive oxygen species (ROS) and antioxidant defenses. High levels of oxidizing free radicals can be very damaging to cells and molecules within the cell. As a result, the cell has important defense mechanisms to protect itself from ROS. For example, Nrf2 is a transcription factor and master regulator of the oxidative stress response. During periods of oxidative stress, Nrf2-dependent changes in gene expression are important in regaining
cellular homeostasis (Nguyen, et al., 2009) and can be used as indicators of the presence of oxidative stress in the cell.

In addition to the directly damaging actions of ROS, cellular oxidative stress also changes cellular activities on a molecular level. Redox sensitive proteins have altered physiology in the presence and absence of ROS, which is caused by the oxidation of sulfhydryls to disulfides on neighboring amino acids (Antelmann & Helmann 2011). Importantly Keap1, the negative regulator of Nrf2, is regulated in this manner (Itoh, et al. 2010).

ROS also undermine the mitochondrial defense system from oxidative damage. The antioxidant systems consist of superoxide dismutase, catalase, glutathione peroxidase and glutathione reductase, as well as antioxidants such as α-tocopherol and ubiquinol, or antioxidant vitamins and minerals including vitamin E, C, carotene, lutein, zeaxanthin, selenium, and zinc (Fletcher, 2010). The enzymes, vitamins and minerals catalyze the conversion of ROS to non-toxic molecules such as water and O2. However, these antioxidant systems are not perfect and endogenous metabolic processes and/or exogenous oxidative influences can trigger cumulative oxidative injuries to the mitochondria, causing a decline in their functionality and efficiency, which further promotes cellular oxidative stress (Balasubramanian, 2000; Ganea & Harding, 2006; Guo et al., 2013; Karimi et al., 2017).

However, an emerging viewpoint suggests that ROS-induced modifications may not be as detrimental as previously thought, but rather contribute to signaling processes (Foyer et al., 2017).

## Sources of ROS Production

**Direct Sources:** Direct sources involve the deposition of energy onto water molecules, breaking them into active radical species. When ionizing radiation hits water, it breaks it into hydrogen (H*) and hydroxyl (OH*) radicals by destroying its bonds. The hydrogen will create hydroxyperoxyl free radicals (HO2*) if oxygen is available, which can then react with another of itself to form hydrogen peroxide (H2O2) and more O2 (Elgazzar and Kazem, 2015). Antioxidant mechanisms are also affected by radiation, with catalase (CAT) and peroxidase (POD) levels rising as a result of exposure (Seen et al. 2018; Ahmad et al. 2021).

**Indirect Sources:** An indirect source of ROS is the mitochondria, which is one of the primary producers in eukaryotic cells (Powers et al., 2008). As much as 2% of the electrons that should be going through the electron transport chain in the mitochondria escape, allowing them an opportunity to interact with surrounding structures. Electron-oxygen reactions result in free radical production, including the formation of hydrogen peroxide (H2O2) (Zhao et al., 2019). The electron transport chain, which also creates ROS, is activated by free adenosine diphosphate (ADP), O2, and inorganic phosphate (Pi) (Hargreaves et al. 2020; Raimondi et al. 2020; Vargas-Mendoza et al. 2021). The first and third complexes of the transport chain are the most relevant to mammalian ROS production (Raimondi et al., 2020). The mitochondria has its own set of DNA and it is a prime target of oxidative damage (Guo et al., 2013). ROS is also produced through nicotinamide adenine dinucleotide phosphate oxidase (Nox) stimulation, an event commenced by angiotensin II, a product/effector of the renin-angiotensin system (Nguyen Dinh Cat et al. 2013; Forrester et al. 2018). Other ROS producers include xanthine oxidase, immune cells (macrophage, neutrophils, monocytes, and eosinophils), phospholipase A2 (PLA2), monoamine oxidase (MAO), and carbon-based nanomaterials (Powers et al. 2008; Jacobsen et al. 2008; Vargas-Mendoza et al. 2021).

## How it is Measured or Detected

**Oxidative Stress:** Direct measurement of ROS is difficult because ROS are unstable. The presence of ROS can be assayed indirectly by measurement of cellular antioxidants, or by ROS-dependent cellular damage. Listed below are common methods for detecting the KE, however there may be other comparable methods that are not listed
* Detection of ROS by chemiluminescence (https://www.sciencedirect.com/science/article/abs/pii/S0165993606001683)

* Detection of ROS by chemiluminescence is also described in OECD TG 495 to assess phototoxic potential.

* Glutathione (GSH) depletion. GSH can be measured by assaying the ratio of reduced to oxidized glutathione (GSH:GSSG) using a commercially available kit (e.g., http://www.abcam.com/gshgssg-ratio-detection-assay-kit-fluorometric-green-ab138881.html).

* TBARS. Oxidative damage to lipids can be measured by assaying for lipid peroxidation using TBARS (thiobarbituric acid reactive substances) using a commercially available kit.

* 8-oxo-dG. Oxidative damage to nucleic acids can be assayed by measuring 8-oxo-dG adducts (for which there are a number of ELISA based commercially available kits), or HPLC, described in Chepelev et al. (Chepelev, et al. 2015).

**Molecular Biology:** Nrf2. Nrf2's transcriptional activity is controlled post-translationally by oxidation of Keap1. Assay for Nrf2 activity include:

* Immunohistochemistry for increases in Nrf2 protein levels and translocation into the nucleus Western blot for increased Nrf2 protein levels

* Western blot of cytoplasmic and nuclear fractions to observe translocation of Nrf2 protein from the cytoplasm to the nucleus qPCR of Nrf2 target genes (e.g., Nqo1, Hmox-1, Gcl, Gst, Prx, TrxR, Srxn), or by commercially available pathway-based qPCR array (e.g., oxidative stress array from SABiosciences)

* Whole transcriptome profiling by microarray or RNA-seq followed by pathway analysis (in IPA, DAVID, metacore, etc.) for enrichment of the Nrf2 oxidative stress response pathway (e.g., Jackson et al. 2014)

* OECD TG422D describes an ARE-Nrf2 Luciferase test method

In general, there are a variety of commercially available colorimetric or fluorescent kits for detecting Nrf2 activation.

<table><thead><tr><td>Assay Type & Measured Content</td><td>Description</td><td>Dose Range Studied</td><td>Assay Characteristics (Length/Ease of use/Accuracy)</td></tr></thead><tbody><tr><td>ROS Formation in the Mitochondria assay (Shaki et al., 2012)</td><td>"The mitochondrial ROS measurement was performed flow cytometry using DCFH-DA. Briefly, isolated kidney mitochondria were incubated with UA (0, 50, 100 and 200 µM) in respiration buffer containing (0.32 mM sucrose, 10mM Tris, 20 mM Mops, 50 µM EGTA, 0.5 mM MgCl2, 0.1 mM KH2PO4 and 5 mM sodium succinate) [32]. In the interval times of 5, 30 and 60 min following the UA addition, a sample was taken and DCFH-DA was added (final concentration, 10 µM) to mitochondria and was then incubated for 10 min. Uranyl acetate-induced ROS generation in isolated kidney mitochondria were determined through the flow cytometry (Partec, Deutschland) equipped with a 488-nm argon ion laser and supplied with the Flomax software and the signals were obtained using a 530-nm bandpass filter (FL-1 channel). Each determination is based on the mean fluorescence intensity of 15,000 counts."</td><td>0, 50, 100 and 200 µM of Uranyl Acetate</td><td>Long/ Easy High accuracy</td></tr><tr><td>Mitochondrial Antioxidant Content Assay Measuring GSH content (Shaki et al., 2012)</td><td>"GSH content was determined using DTNB as the indicator and spectrophotometer method for the isolated mitochondria. The mitochondrial fractions (0.5 mg protein/ml) were incubated with various concentrations of uranyl acetate for 1 h at 30 °C and then 0.1 ml of mitochondrial fractions was added into 0.1 mol/l of phosphate buffers and 0.04% DTNB in a total volume of 3.0 ml (pH 7.4). The developed yellow color was read at 412 nm on a spectrophotometer (UV-1601 PC, Shimadzu, Japan). GSH content was expressed as µg/mg protein."</td><td>0, 50, 100, or 200 µM Uranyl Acetate</td><td></td></tr></tbody></table>
<table><tr><td>H2O2 Production Assay Measuring H2O2 Production in isolated mitochondria (Heyno et al., 2008)</td><td>"Effect of CdCl2 and antimycin A (AA) on H2O2 production in isolated mitochondria from potato. H2O2 production was measured as scopoletin oxidation. Mitochondria were incubated for 30 min in the measuring buffer (see the Materials and Methods) containing 0.5 mM succinate as an electron donor and 0.2 µM mesoxalonitrile 3-chlorophenylhydrazone (CCCP) as an uncoupler, 10 U horseradish peroxidase and 5 µM scopoletin."</td><td>0, 10, 30 µM Cd2+<br>2 µM antimycin A</td><td></td></tr><tr><td>Flow Cytometry ROS & Cell Viability (Kruiderig et al., 1997)</td><td>"For determination of ROS, samples taken at the indicated time points were directly transferred to FACScan tubes. Dih123 (10 mM, final concentration) was added and cells were incubated at 37°C in a humidified atmosphere (95% air/5% CO2) for 10 min. At t 5 9, propidium iodide (10 mM, final concentration) was added, and cells were analyzed by flow cytometry at 60 ml/min. Nonfluorescent Dih123 is cleaved by ROS to fluorescent R123 and detected by the FL1 detector as described above for Dc (Van de Water 1995)"<br>"For determination of ROS, samples taken at the indicated time points were directly transferred to FACScan tubes. Dih123 (10 mM, final concentration) was added and cells were incubated at 37°C in a humidified atmosphere (95% air/5% CO2) for 10 min. At t 5 9, propidium iodide (10 mM, final concentration) was added, and cells were analyzed by flow cytometry at 60 ml/min. Nonfluorescent Dih123 is cleaved by ROS to fluorescent R123 and detected by the FL1 detector as described above for Dc (Van de Water 1995)"</td><td></td><td>Strong/easy medium</td></tr><tr><td>DCFH-DA Assay Detection of hydrogen peroxide production (Yuan et al., 2016)</td><td>Intracellular ROS production was measured using DCFH-DA as a probe. Hydrogen peroxide oxidizes DCFH to DCF. The probe is hydrolyzed intracellularly to DCFH carboxylate anion. No direct reaction with H2O2 to form fluorescent production.</td><td>0-400 µM</td><td>Long/ Easy High accuracy</td></tr><tr><td>H2-DCF-DAAssay Detection of superoxide production (Thiebault et al., 2007)</td><td>This dye is a stable nonpolar compound which diffuses readily into the cells and yields H2-DCF. Intracellular OH or ONOO- react with H2-DCF when cells contain peroxides, to form the highly fluorescent compound DCF, which effluxes the cell. Fluorescence intensity of DCF is measured using a fluorescence spectrophotometer.</td><td>0-600 µM</td><td>Long/ Easy High accuracy</td></tr><tr><td>CM-H2DCFDA Assay (Eruslanov & Kusmartsev, 2009)</td><td>The dye (CM-H2DCFDA) diffuses into the cell and is cleaved by esterases, the thiol reactive chlormethyl group reacts with intracellular glutathione which can be detected using flow cytometry.</td><td></td><td>Long/Easy/ High Accuracy</td></tr></table>

<table><thead><tr><td>Method of Measurement</td><td>References</td><td>Description</td><td>OECD-Approved Assay</td></tr></thead><tbody><tr><td>Chemiluminescence</td><td>(Lu, C. et al., 2006; Griendling, K. K., et al., 2016)</td><td>ROS can induce electron transitions in molecules, leading to electronically excited products. When the electrons transition back to ground state, chemiluminescence is emitted and can be measured. Reagents such as luminol and lucigenin are commonly used to amplify the signal.</td><td>No</td></tr><tr><td>Spectrophotometry</td><td>(Griendling, K. K., et al., 2016)</td><td>NO has a short half-life. However, if it has been reduced to nitrite (NO2-), stable azocompounds can be formed via the Griess Reaction, and further measured by spectrophotometry.</td><td>No</td></tr><tr><td>Direct or Spin Trapping-Based electron paramagnetic resonance (EPR) Spectroscopy</td><td>(Griendling, K. K., et al., 2016)</td><td>The unpaired electrons (free radicals) found in ROS can be detected with EPR and is known as electron paramagnetic resonance. A variety of spin traps can be used.</td><td>No</td></tr><tr><td>Nitroblue Tetrazolium Assay</td><td>(Griendling, K. K., et al., 2016)</td><td>The Nitroblue Tetrazolium assay is used to measure O2.- levels. O2.- reduces nitroblue tetrazolium (a yellow dye) to formazan (a blue dye), and can be measured at 620 nm.</td><td>No</td></tr><tr><td>Fluorescence analysis of dihydroethidium (DHE) or Hydrocyans</td><td>(Griendling, K. K., et al., 2016)</td><td>Fluorescence analysis of DHE is used to measure O2.- levels. O2.- is reduced to O2 as DHE is oxidized to 2-hydroxyethidium, and this reaction can be measured by fluorescence. Similarly, hydrocyans can be oxidized by any ROS, and measured via fluorescence.</td><td>No</td></tr><tr><td>Amplex Red Assay</td><td>(Griendling, K. K., et al., 2016)</td><td>Fluorescence analysis to measure extramitochondrial or extracellular H2O2 levels. In the presence of horseradish</td><td>No</td></tr></tbody></table>
<table><tr><td>Dichlorodihydrofluorescein Diacetate (DCFH-DA)</td><td>(Griendling, K. K., et al., 2016)</td><td>An indirect fluorescence analysis to measure intracellular H2O2 levels. H2O2 interacts with peroxidase or heme proteins, which further react with DCFH, oxidizing it to dichlorofluorescein (DCF), a fluorescent product.</td><td>No</td></tr><tr><td>HyPer Probe</td><td>(Griendling, K. K., et al., 2016)</td><td>Fluorescent measurement of intracellular H2O2 levels. HyPer is a genetically encoded fluorescent sensor that can be used for in vivo and in situ imaging.</td><td>No</td></tr><tr><td>Cytochrome c Reduction Assay</td><td>(Griendling, K. K., et al., 2016)</td><td>The cytochrome c reduction assay is used to measure O2.- levels. O2.- is reduced to O2 as ferricytochrome c is oxidized to ferrocytochrome c, and this reaction can be measured by an absorbance increase at 550 nm.</td><td>No</td></tr><tr><td>Proton-electron double-resonance imaging (PEDRI)</td><td>(Griendling, K. K., et al., 2016)</td><td>The redox state of tissue is detected through nuclear magnetic resonance/magnetic resonance imaging, with the use of a nitroxide spin probe or biradical molecule.</td><td>No</td></tr><tr><td>Glutathione (GSH) depletion</td><td>(Biesemann, N. et al., 2018)</td><td>A downstream target of the Nrf2 pathway is involved in GSH synthesis. As an indication of oxidation status, GSH can be measured by assaying the ratio of reduced to oxidized glutathione (GSH:GSSG) using a commercially available kit (e.g., http://www.abcam.com/gshgssg-ratio-detection-assay-kit-fluorometric-green-ab138881.html).</td><td>No</td></tr><tr><td>Thiobarbituric acid reactive substances (TBARS)</td><td>(Griendling, K. K., et al., 2016)</td><td>Oxidative damage to lipids can be measured by assaying for lipid peroxidation with TBARS using a commercially available kit.</td><td>No</td></tr><tr><td>Protein oxidation (carbonylation)</td><td>(Azimzadeh et al., 2017; Azimzadeh et al., 2015; Ping et al., 2020)</td><td>Can be determined with ELISA or a commercial assay kit. Protein oxidation can indicate the level of oxidative stress.</td><td>No</td></tr><tr><td>Seahorse XFp Analyzer</td><td>Leung et al. 2018</td><td>The Seahorse XFp Analyzer provides information on mitochondrial function, oxidative stress, and metabolic dysfunction of viable cells by measuring respiration (oxygen consumption rate; OCR) and extracellular pH (extracellular acidification rate; ECAR).</td><td>No</td></tr></table>

Molecular Biology: Nrf2.

Nrf2's transcriptional activity is controlled post-translationally by oxidation of Keap1. Assays for Nrf2 activity include:

<table><thead><tr><th>Method of Measurement</th><th>References</th><th>Description</th><th>OECD-Approved Assay</th></tr></thead><tbody><tr><td>Immunohistochemistry</td><td>(Amsen, D., de Visser, K. E., and Town, T., 2009)</td><td>Immunohistochemistry for increases in Nrf2 protein levels and translocation into the nucleus</td><td>No</td></tr><tr><td>qPCR</td><td>(Forlenza et al., 2012)</td><td>qPCR of Nrf2 target genes (e.g., Nqo1, Hmox-1, Gcl, Gst, Prx, TrxR, Srxn), or by commercially available pathway-based qPCR array (e.g., oxidative stress array from SABiosciences)</td><td>No</td></tr><tr><td>Whole transcriptome profiling via microarray or via RNA-seq followed by a pathway analysis</td><td>(Jackson, A. F. et al., 2014)</td><td>Whole transcriptome profiling by microarray or RNA-seq followed by pathway analysis (in IPA, DAVID, metacore, etc.) for enrichment of the Nrf2 oxidative stress response pathway</td><td>No</td></tr></tbody></table>
Ahmad, S. et al. (2021), "60Co-γ Radiation Alters Developmental Stages of Zeugodacus cucurbitae (Diptera: Tephritidae) Through Apoptosis Pathways Gene Expression", Journal Insect Science, Vol. 21/5, Oxford University Press, Oxford, https://doi.org/10.1093/jisesa/ieab080

Antelmann, H. and J. D. Helmann (2011), "Thiol-based redox switches and gene regulation.", Antioxidants & Redox Signaling, Vol. 14/6, Mary Ann Leibert Inc., Larchmont, https://doi.org/10.1089/ars.2010.3400

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

Azimzadeh, O. et al. (2015), "Integrative Proteomics and Targeted Transcriptomics Analyses in Cardiac Endothelial Cells Unravel Mechanisms of Long-Term Radiation-Induced Vascular Dysfunction", Journal of Proteome Research, Vol. 14/2, American Chemical Society, Washington, https://doi.org/10.1021/pr501141b

Azimzadeh, O. et al. (2017), "Proteome analysis of irradiated endothelial cells reveals persistent alteration in protein degradation and the RhoGDI and NO signalling pathways", International Journal of Radiation Biology, Vol. 93/9, Informa, London, https://doi.org/10.1080/09553002.2017.1339332

Azzam, E. I. et al. (2012), "Ionizing radiation-induced metabolic oxidative stress and prolonged cell injury", Cancer Letters, Vol. 327/1-2, Elsevier, Ireland, https://doi.org/10.1016/j.canlet.2011.12.012

Bai, J. et al. (2020), "Irradiation-induced senescence of bone marrow mesenchymal stem cells aggravates osteogenic differentiation dysfunction via paracrine signaling", American Journal of Physiology - Cell Physiology, Vol. 318/5, American Physiological Society, Rockville, https://doi.org/10.1152/ajpcell.00520.2019.

Balasubramanian, D (2000), "Ultraviolet radiation and cataract", Journal of ocular pharmacology and therapeutics, Vol. 16/3, Mary Ann Liebert Inc., Larchmont, https://doi.org/10.1089/jop.2000.16.285.

Biesemann, N. et al., (2018), "High Throughput Screening of Mitochondrial Bioenergetics in Human Differentiated Myotubes Identifies Novel Enhancers of Muscle Performance in Aged Mice", Scientific Reports, Vol. 8/1, Nature Portfolio, London, https://doi.org/10.1038/s41598-018-27614-8.

Elgazzar, A. and N. Kazem. (2015), "Chapter 23: Biological effects of ionizing radiation" in The Pathophysiologic Basis of Nuclear Medicine, Springer, New York, pp. 540-548

Eruslanov, E., & Kusmartsev, S. (2010). Identification of ROS using oxidized DCFDA and flow-cytometry. Methods in molecular biology, N.J., Vol. 594, https://doi.org/10.1007/978-1-60761-411-1_4

Fletcher, A. E (2010), "Free radicals, antioxidants and eye diseases: evidence from epidemiological studies on cataract and age-related macular degeneration", Ophthalmic Research, Vol. 44, Karger International, Basel, https://doi.org/10.1159/000316476.

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
Forrester, S.J. et al. (2018), “Angiotensin II Signal Transduction: An Update on Mechanisms of Physiology and Pathophysiology”, Physiological Reviews, Vol. 98/3, American Physiological Society, Rockville, https://doi.org/10.1152/physrev.00038.201

Foyer, C. H., A. V. Ruban, and G. Noctor (2017), “Viewing oxidative stress through the lens of oxidative signalling rather than damage”, Biochemical Journal, Vol. 474/6, Portland Press, England, https://doi.org/10.1042/BCJ20160814

Ganea, E. and J. J. Harding (2006), “Glutathione-related enzymes and the eye”, Current eye research, Vol. 31/1, Informa, London, https://doi.org/10.1080/02713680500477347.

Griendling, K. K. et al. (2016), “Measurement of reactive oxygen species, reactive nitrogen species, and redox-dependent signaling in the cardiovascular system: a scientific statement from the American Heart Association”, Circulation research, Vol. 119/5, Lippincott Williams & Wilkins, Philadelphia, https://doi.org/10.1161/RES.0000000000000110

Guo, C. et al. (2013), “Oxidative stress, mitochondrial damage and neurodegenerative diseases”, Neural regeneration research, Vol. 8/21, Publishing House of Neural Regeneration Research, China, https://doi.org/10.3969/j.issn.1673-5374.2013.21.009

Hargreaves, M., and L. L. Spriet (2020), “Skeletal muscle energy metabolism during exercise.”, Nature Metabolism, Vol. 2, Nature Portfolio, London, https://doi.org/10.1038/s42255-020-0251-4

Hladik, D. and S. Tapio (2016), “Effects of ionizing radiation on the mammalian brain”, Mutation Research/Reviews in Mutation Research, Vol. 770, Elsevier, Amsterdam, https://doi.org/10.1016/j.mrrev.2016.08.003

Itoh, K., J. Mimura and M. Yamamoto (2010), “Discovery of the negative regulator of Nrf2, Keap1: a historical overview”, Antioxidants & Redox Signaling, Vol. 13/11, Mary Ann Leibert Inc., Larchmont, https://doi.org/10.1089/ars.2010.3222

Jackson, A.F. et al. (2014), “Case study on the utility of hepatic global gene expression profiling in the risk assessment of the carcinogen furan.”, Toxicology and Applied Pharmacology, Vol. 274/11, Elsevier, Amsterdam, https://doi.org/10.1016/j.taap.2013.10.019

Jacobsen, N.R. et al. (2008), “Genotoxicity, cytotoxicity, and reactive oxygen species induced by single-walled carbon nanotubes and C60 fullerenes in the FE1-MutaTM Mouse lung epithelial cells”, Environmental and Molecular Mutagenesis, Vol. 49/6, John Wiley & Sons, Inc., Hoboken, https://doi.org/10.1002/em.20406

Karimi, N. et al. (2017), “Radioprotective effect of hesperidin on reducing oxidative stress in the lens tissue of rats”, International Journal of Pharmaceutical Investigation, Vol. 7/3, Phcog Net, Bengaluru, https://doi.org/10.4103/jphi.JPHI_60_17.

Leung, D.T.H., and Chu, S. (2018), “Measurement of Oxidative Stress: Mitochondrial Function Using the Seahorse System” In: Murthi, P., Vaillancourt, C. (eds) Preeclampsia. Methods in Molecular Biology, vol 1710. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7498-6_22

Lu, C., G. Song, and J. Lin (2006), “Reactive oxygen species and their chemiluminescence-detection methods”, TrAC Trends in Analytical Chemistry, Vol. 25/10, Elsevier, Amsterdam, https://doi.org/10.1016/j.trac.2006.07.007
Nguyen Dinh Cat, A. et al. (2013), "Angiotensin II, NADPH oxidase, and redox signaling in the vasculature", Antioxidants & redox signaling, Vol. 19/10, Mary Ann Liebert, Larchmont, https://doi.org/10.1089/ars.2012.4641

Ping, Z. et al. (2020), "Oxidative Stress in Radiation-Induced Cardiotoxicity", Oxidative Medicine and Cellular Longevity, Vol. 2020, Hindawi, https://doi.org/10.1155/2020/3579143

Powers, S.K. and M.J. Jackson. (2008), "Exercise-Induced Oxidative Stress: Cellular Mechanisms and Impact on Muscle Force Production", Physiological Reviews, Vol. 88/4, American Physiological Society, Rockville, https://doi.org/10.1152/physrev.00031.2007

Raimondi, V., F. Ciccarese and V. Ciminale. (2020), "Oncogenic pathways and the electron transport chain: a dangeROS liason", British Journal of Cancer, Vol. 122/2, Nature Portfolio, London, https://doi.org/10.1038/s41416-019-0651-y

Seen, S. and L. Tong. (2018), "Dry eye disease and oxidative stress", Acta Ophthalmologica, Vol. 96/4, John Wiley & Sons, Inc., Hoboken, https://doi.org/10.1111/aos.13526

Ungvari, Z. et al. (2013), "Ionizing Radiation Promotes the Acquisition of a Senescence-Associated Secretory Phenotype and Impairs Angiogenic Capacity in Cerebromicrovascular Endothelial Cells: Role of Increased DNA Damage and Decreased DNA Repair Capacity in Microvascular Radiosensitivity", The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, Vol. 68/12, Oxford University Press, Oxford, https://doi.org/10.1093/gerona/glt057.

Vargas-Mendoza, N. et al. (2021), "Oxidative Stress, Mitochondrial Function and Adaptation to Exercise: New Perspectives in Nutrition", Life, Vol. 11/11, Multidisciplinary Digital Publishing Institute, Basel, https://doi.org/10.3390/life1111269

Wang, H. et al. (2019), "Radiation-induced heart disease: a review of classification, mechanism and prevention", International Journal of Biological Sciences, Vol. 15/10, Ivyspring International Publisher, Sydney, https://doi.org/10.7150/ijbs.35460

Zhang, R. et al. (2009), "Blockade of AT1 receptor partially restores vasoreactivity, NOS expression, and superoxide levels in cerebral and carotid arteries of hindlimb unweighting rats", Journal of applied physiology, Vol. 106/1, American Physiological Society, Rockville, https://doi.org/10.1152/japplphysiol.01278.2007.

Zhao, R. Z. et al. (2019), "Mitochondrial electron transport chain, ROS generation and uncoupling", International journal of molecular medicine, Vol. 44/1, Spandidos Publishing Ltd., Athens, https://doi.org/10.3892/ijmm.2019.4188
# Event: 2244: Altered Stress Response Signaling

## Short Name: Altered Stress Response Signaling

### Key Event Component

<table><thead><tr><td>Process</td><td>Object</td><td>Action</td></tr></thead><tbody><tr><td>cell surface receptor signaling pathway</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: 470 – Deposition of energy leads to abnormal vascular remodeling</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></tbody></table>

### Biological context

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

## Domain of Applicability

### Taxonomic Applicability

Altered stress response signaling is applicable to all animals as cell signaling occurs among animal cells. This includes vertebrates such as humans, mice and rats (Nair et al., 2019).

<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>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 not life stage specific.

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

### Sex Applicability

This key event is not sex specific.

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

## Evidence for Perturbation by Prototypic Stressor

Evidence for perturbation by a stressor: Multiple studies show that signaling pathways can be disrupted by many types of stressors including ionizing radiation and altered gravity (Cheng et al., 2020; Coleman et al., 2021; Su et al., 2020; Yentrapalli et al., 2013).

## Key Event Description

Cells rely on a balance of signaling pathways to maintain their functionality and viability. These pathways integrate signals from both external and internal stressors to coordinate protective responses, thereby enhancing the cell's ability to cope with adverse conditions. Key components of these pathways include the activation of stress-responsive transcription factors such as NF-κB, p53, and AP-1, which regulate the expression of genes involved in cell cycle arrest, DNA repair, and apoptosis. DNA double-strand breaks, for instance, initiate a cascade of events involving the ataxia-telangiectasia mutated (ATM) kinase, the DNA-dependent protein kinase (DNA-PK), and the p53 pathway, ultimately leading to cell cycle arrest and repair mechanisms or apoptosis if the damage is irreparable (Kastan and Lim,
2000). Furthermore, the mitogen-activated protein kinase (MAPK) pathways, including ERK, JNK, and p38, are crucial for the cellular stress response and inflammatory processes (Dent et al., 2003).

These pathways are essential in regulating cellular survival and mediating apoptosis under various physiological and pathological conditions. Persistent signaling or a pre-existing inflammatory environment can significantly influence cell fate. For instance, the cAMP-PKA pathway, which is involved in neurotransmitter signaling, impacts synaptic plasticity and memory formation (Zhang et al., 2024). The MAPK pathway, encompassing ERK, JNK, and p38 MAP kinases, is vital for cell differentiation, proliferation, and response to stress stimuli (Arthur and Ley, 2013; Yue and Lopez, 2020). The PI3K-Akt pathway promotes cell survival and growth by inhibiting apoptotic processes and supporting metabolic functions (Manning and Cantley, 2007). The p53 pathway is a key regulator of the cellular stress response, often leading to apoptosis in the context of severe DNA damage or oxidative stress (Kruiswijk et al., 2015).

Exposure to stressors, such as radiation, can disrupt these stress response signaling pathways or lead to persistent activation. For example, the cAMP-PKA pathway can be hindered by reduced cAMP levels and impaired PKA activity, leading to decreased CREB phosphorylation (Zhang et al., 2024). The MAPK pathway is affected by external stressors through the inhibition of ERK activation and subsequent gene expression (Kim and Choi, 2010). The PI3K-Akt pathway, which is vital for cell survival, experiences reduced PI3K activity and Akt signaling, impairing mTOR-mediated protein synthesis (Glaviano et al., 2023; Martini et al., 2014). Activation of the p53 pathway in response to DNA damage can also potentially induce cellular senescence if the damage is irreparable (Ou et al., 2018). Persistent disruptions in these pathways can lead to a wide range of pathophysiological conditions, including neurodegenerative diseases, chronic inflammation, cardiovascular disease, and cancer.

## Key Stress Response Pathways: Description and Components for Measurement

A broad way to measure these pathways concurrently is through the use of omics technologies, Omics technologies (Dai and Shen. 2022) involve comprehensive, high-throughput analysis of DNA, RNA, proteins, and metabolites to understand cellular functions and dynamics, offering a systems-level view of biological processes. Pathway analysis can then be used to gain insights from large amounts of omics data (Palli et al. 2019). Transcriptomics RNA sequence libraries are generated, clustering analysis is done, then sequencing for gene analysis (Qin et al. 2023). Proteins have been analyzed with proteomic analysis through LC-MS/MS analysis, bioinformatic analysis, western blot, qRT-PCR analysis or molecular docking. Metabolites are mass analyzed using the Thermo Q EXACTIVE, and then the edited data matrix is imported to Metabo Analyst for analysis (Hu et al. 2022).

Additionally, Post-translational modifications (PTMs) can also be measured using techniques such as mass spectrometry, which identifies and quantifies modifications like ubiquitination, glycosylation, and phosphorylation. Western blotting and immunoassays detect specific PTMs using antibodies tailored to particular modifications, while labeling methods can highlight modifications like acetylation and methylation. These measurements help elucidate protein function, stability, and interactions within cellular processes.

### AMP-PKA Pathway:

The AMP-PKA pathway is activated by stressors which engage G protein-coupled receptors (GPCRs). GPCRs activation leads to the production of cyclic adenosine monophosphate (cAMP) by adenylyl cyclase. cAMP then goes on to activate protein kinase A (PKA), which is one of the primary kinases required for several functions in the cell such as DNA repair and initiating a response to oxidative stress (Hunter, 2000; Jessulat et al., 2021; Steinberg and Hardie, 2023). This results in PKA phosphorylating various target proteins, thereby influencing gene expression, metabolism and cell survival.

### MAPK Pathway:

MAPK pathway is triggered by a variety of stressors, including growth factors, cytokines, hormones and various cellular stressors such as oxidative stress (Kim and Choi., 2010). The pathway involves a
kinase cascade starting from receptor tyrosine kinases (RTKs) or GPCRs, leading to the activation of Ras, Raf, MEK, and ERK. Activated ERK then translocates to the nucleus and regulates gene expression, affecting cell growth, differentiation, and apoptosis (Morrison, 2012).

**PI3K-Akt Pathway:**

The PI3K-Akt pathway is activated by stressors through receptor tyrosine kinases (RTKs) or GPCRs. Activation of phosphoinositide 3-kinase (PI3K) generates phosphatidylinositol (3,4,5)-trisphosphate (PIP3), recruiting and activating Akt. Akt then phosphorylates downstream targets, resulting in promotion of cell survival, growth, and metabolism while inhibiting apoptosis (Martini et al., 2014; Jin et al., 2022).

**NF-κB Pathway:**

NF-κB is activated by pro-inflammatory cytokines, pathogens, and stress signals. This pathway involves the activation of IκB kinase (IKK), which phosphorylates IκB, leading to its degradation and the release of NF-κB. NF-κB then translocates to the nucleus and promotes the expression of genes involved in inflammation, immune response, and cell survival (Liu et al., 2017)

**JAK-STAT Pathway:**

The JAK-STAT signaling pathway is triggered by cytokines and growth factors. Janus kinases (JAKs) are then activated, which phosphorylate and activate signal transducer and activator of transcription (STAT) proteins. Activated STATs dimerize and translocate to the nucleus to regulate gene expression, impacting cell proliferation, differentiation, and immune function. This signaling pathway is involved in multiple important biological processes such as differentiation, apoptosis, cell proliferation and immune regulation (Xin et al., 2020).

**HSP (Heat Shock Protein) Pathway:**

HSP (Heat Shock Protein) pathway is induced by heat shock, oxidative stress, and other proteotoxic stresses. Stress signals lead to the activation of heat shock factor 1 (HSF1), which translocates to the nucleus and promotes the expression of heat shock proteins (HSPs). HSPs act as molecular chaperones, aiding in protein folding, preventing aggregation, and promoting protein degradation. These proteins can also work as danger signaling biomarkers, being secreted to the exterior of the cell in response to stress (Zininga et al., 2018)

**p53 Pathway:**

The p53 pathway is activated by DNA damage, oxidative stress, and other genotoxic stresses. DNA damage activates kinases like ATM and ATR, which phosphorylate and stabilize p53. p53 then regulates the expression of genes involved in cell cycle arrest, DNA repair, and apoptosis (Joerger and Fersht, 2016). p53 functions also expand to roles in development, metabolic regulation and stem cell biology.

**Unfolded Protein Response (UPR):**

Unfolded Protein Response (UPR) is triggered by the accumulation of unfolded or misfolded proteins in the endoplasmic reticulum (ER) (Hetz et al., 2020). This pathway involves sensors such as IRE1, PERK, and ATF6, which detect ER stress and activate downstream signaling pathways (Ron and Walter, 2007). UPR aims to restore ER homeostasis by enhancing protein folding capacity, degrading misfolded proteins, and reducing protein synthesis (Grootjans et al., 2016).

*How it is Measured or Detected*

<table><thead><tr><td>Pathway</td><td>Method of Measurement</td><td>Description</td><td>Reference</td><td>OECD Approved Assay</td></tr></thead><tbody><tr><td rowspan="2">cAMP-PKA</td><td>ELISA</td><td>Measures intracellular cAMP concentrations to assess activation of the cAMP-PKA pathway.</td><td>Zhu et al., 2016</td><td>No</td></tr><tr><td>cAMP-Glo™ Assay</td><td>Monitors the level of intracellular cAMP in the cell with receptors that are modulated by lipid and free fatty acid agonists.</td><td>Hu et al., 2019</td><td>No</td></tr></tbody></table>
<table><tr><td></td><td>Western Blot</td><td>Detects phosphorylation of PKA substrates, indicating pathway activation.</td><td>Zhang et al., 2021</td><td>No</td></tr><tr><td></td><td>Direct cAMP Enzyme Immunoassay</td><td>Uses a cAMP polyclonal antibody to competitively bind the cAMP in the sample which has cAMP covalently bonded.</td><td>Nogueira et al., 2015</td><td>No</td></tr><tr><td></td><td>RT-PCR</td><td>Quantifies mRNA levels of PKA-RII and PKA-C.</td><td>Zhu et al., 2016</td><td>No</td></tr><tr><td>MAPK</td><td>Western Blot</td><td>Detects the phosphorylation state of MAPK family members (ERK, JNK, p38), indicating activation.</td><td>Tan et al., 2022; Xia and Tang 2023</td><td>No</td></tr><tr><td></td><td>Immunohistochemistry</td><td>Visualizes the activation of MAPKs (JNK and p38) in tissue sections using specific antibodies.</td><td>Er et al., 2022</td><td>No</td></tr><tr><td></td><td>qRT-PCR</td><td>Quantifies mRNA levels of JNK, MAPK1(ERK), and MAPK14(p38)</td><td>Xia and Tang 2023</td><td>No</td></tr><tr><td>PI3K-Akt</td><td>Western Blot</td><td>Detects phosphorylation of proteins such as PI3K and AKT.</td><td>Jin et al., 2022; Xia and Tang 2023; Bamodu et al., 2020</td><td>No</td></tr><tr><td></td><td>qRT-PCR</td><td>Quantifies mRNA levels of AKT1 and PI3K.</td><td>Xia and Tang 2023</td><td>No</td></tr><tr><td>p53</td><td>Western Blot</td><td>Measures levels of p53 and its downstream target proteins to assess activation.</td><td>Wei et al., 2024; Mendes et al. 2015</td><td>No</td></tr><tr><td></td><td>qPCR</td><td>Quantifies mRNA levels of p53-regulated genes such as p21, Bax, and H3K27me3.</td><td>Wei et al., 2024</td><td>No</td></tr><tr><td></td><td>Chromatin immunoprecipitation (ChIP)</td><td>Detects p53 binding to DNA at target gene promoters.</td><td>Vousden and Prives, 2009; Wei et al., 2024</td><td>No</td></tr><tr><td></td><td>Co-immunoprecipitation (Co-IP)</td><td>Identifies p53 protein to protein interactions.</td><td>Wei et al., 2024</td><td>No</td></tr><tr><td></td><td>Immunofluorescence</td><td>Visualizes localization and expression of p53.</td><td>Wei et al., 2024</td><td>No</td></tr><tr><td>NF-κB</td><td>Western Blot</td><td>Detects phosphorylation and degradation of IκBα, indicating activation of the NF-κB pathway.</td><td>Mao et al., 2023; Meier-Soelch et al., 2021; Xia and Tang 2023</td><td>No</td></tr><tr><td></td><td>Electrophoretic Mobility Shift Assay (EMSA)</td><td>Measures DNA-binding activity of NF-κB to specific response elements.</td><td>Meier-Soelch et al., 2021; Ramaswami and Hayden, 2015</td><td>No</td></tr><tr><td></td><td>ELISA</td><td>Quantifies NF-κB DNA-binding activity in nuclear extracts.</td><td>Meier-Soelch et al., 2021</td><td>No</td></tr><tr><td>JAK-STAT</td><td>Western Blot</td><td>Measures levels of JAK2 and STAT3</td><td>Broughton and Burfoot, 2001; Mao et al., 2023</td><td>No</td></tr><tr><td></td><td>Electrophoretic Mobility Shift Assay (EMSA)</td><td>Measures DNA-binding activity of STAT proteins to specific response elements.</td><td>Broughton and Burfoot; Jiao et al., 2003</td><td>No</td></tr><tr><td>HSP</td><td>Western Blot</td><td>Measures levels of heat shock proteins such as HSP70 and HSP83.</td><td>Kaur and Kaur, 2013; Thakur et al., 2019</td><td>No</td></tr><tr><td></td><td>ELISA</td><td>Quantifies levels of specific heat shock proteins in cell extracts.</td><td>Kaur and Kaur, 2013</td><td>No</td></tr><tr><td></td><td>Immunofluorescence</td><td>Visualizes localization and expression of heat shock proteins in cells.</td><td>Thakur et al., 2019</td><td>No</td></tr><tr><td>UPR</td><td>Western Blot</td><td>Measures levels of UPR markers such as PERK, IRE1α, ATF-6</td><td>Sita et al., 2023; Kennedy et al., 2015; Zheng et al., 2019</td><td>No</td></tr><tr><td></td><td>qPCR and RT-PCR</td><td>Quantifies mRNA levels of UPR-regulated genes such as ATF4 and CHOP.</td><td>Kennedy et al., 2015; Zheng et al., 2019</td><td>No</td></tr><tr><td></td><td>Immunofluorescence</td><td>Visualizes localization and expression of UPR markers in cells.</td><td>Zheng et al., 2019</td><td>No</td></tr></table>
References

Arthur, J. S. and S. C. Ley (2013), "Mitogen-activated protein kinases in innate immunity", Nature Reviews Immunology, Vol. 13/9, Springer, New York, https://doi.org/10.1038/nri3495

Bamodu, O. A. et al. (2020), “Elevated PDK1 Expression Drives PI3K/AKT/MTOR Signaling Promotes Radiation-Resistant and Dedifferentiated Phenotype of Hepatocellular Carcinoma”, Cells, Vol. 9/3, Multidisciplinary Digital Publishing Institute, Basel, https://doi.org/10.3390/cells9030746

Broughton, N. and M. S. Burfoot (2001), “JAK-mediated phosphorylation and activation of STAT signaling proteins. Analysis by phosphotyrosine blotting and EMSA”, Methods in molecular biology (Clifton, N.J.), Vol. 124, Springer, New York, https://doi.org/10.1385/1-59259-059-4:131

Dai, X. and L. Shen (2022), “Advances and Trends in Omics Technology Development”, Frontiers in medicine, Vol. 9, Frontiers Media, Lausanne, https://doi.org/10.3389/fmed.2022.911861

Dent, P., et al. (2003), “MAPK pathways in radiation responses”, Oncogene, Vol. 22/37, Springer, London, https://doi.org/10.1038/sj.onc.1206701

Er, H. et al. (2022), “Acute and Chronic Exposure to 900 MHz Radio Frequency Radiation Activates p38/JNK-mediated MAPK Pathway in Rat Testis”, Reproductive sciences (Thousand Oaks, Calif.), Vol. 29/5, Springer, New York, https://doi.org/10.1007/s43032-022-00844-y

Glaviano, A., et al. (2023), “PI3K/AKT/mTOR signaling transduction pathway and targeted therapies in cancer”, Molecular cancer, Vol. 22/1, Springer, London, https://doi.org/10.1186/s12943-023-01827-6Hu

Grootjans, J. et al. (2016), “The unfolded protein response in immunity and inflammation”, Nature reviews. Immunology, Vol. 16/8, Springer, London, https://doi.org/10.1038/nri.2016.62

Hetz, C., K. Zhang and R. J. Kaufman (2020), “Mechanisms, regulation and functions of the unfolded protein response”, Nature reviews. Molecular cell biology, Vol 21/8, Springer, London, https://doi.org/10.1038/s41580-020-0250-z

Hu, S. et al. (2019), “Ganoderma lucidum polysaccharide inhibits UVB-induced melanogenesis by antagonizing cAMP/PKA and ROS/MAPK signaling pathways”, Journal of cellular physiology, Vol. 234/5, John Wiley & Sons, Ltd., Hoboken, https://doi.org/10.1002/jcp.27492

Hunter, T. (2000), “Signaling – 2000 and beyond”, Cell, Vol. 100/1, Cell Press, Cambridge, https://doi.org/10.1016/s0092-8674(00)81688-8

Hu, X., et al. (2022), “Combining network pharmacology, RNA-seq, and metabolomics strategies to reveal the mechanism of Cimicifugae Rhizoma - Smilax glabra Roxb herb pair for the treatment of psoriasis”, Phytomedicine : international journal of phytotherapy and phytopharmacology, Vol. 105, Elsevier, Amsterdam, https://doi.org/10.1016/j.phymed.2022.154384

Jessulat, M. et al. (2021), “The conserved Tpk1 regulates non-homologous end joining double-strand break repair by phosphorylation of Nej1, a homolog of the human XLF”, Nucleic acids research, Vol. 49/14, Oxford University Press, Oxford, https://doi.org/10.1093/nar/gkab585

Jiao, J. et al. (2003), “Initiation and maintenance of CNTF-Jak/STAT signaling in neurons is blocked by protein tyrosine phosphatase inhibitors”, Brain research. Molecular brain research, Vol.116/1-2, Elsevier, Amsterdam, https://doi.org/10.1016/s0169-328x(03)00286-9
Jin, Y., et al. (2022). "Activation of PI3K/AKT Pathway Is a Potential Mechanism of Treatment Resistance in Small Cell Lung Cancer". Clinical cancer research : an official journal of the American Association for Cancer Research, Vol. 28/3, https://doi.org/10.1158/1078-0432.CCR-21-1943

Joerger, A. C. and A. R. Fersht (2016), "The p53 Pathway: Origins, Inactivation in Cancer, and Emerging Therapeutic Approaches", Annual review of biochemistry, Vol. 85, Annual Reviews,

Joerger AC, Fersht AR. (2016), “The p53 Pathway: Origins, Inactivation in Cancer, and Emerging Therapeutic Approaches”, Annu Rev Biochem. Jun 2;85:375-404. doi: 10.1146/annurev-biochem-060815-014710. Epub 2016 May 4.

Kastan, M. B. and D. S. Lim (2000), "The many substrates and functions of ATM. Nature reviews", Molecular cell biology, Vol. 1/3, Springer, London, https://doi.org/10.1038/35043058

Kaur, J. and S. Kaur (2013), “ELISA and western blotting for the detection of Hsp70 and Hsp83 antigens of Leishmania donovani”, Journal of parasitic diseases: official organ of the Indian Society for Parasitology, Vol. 37/1, Springer, New York, https://doi.org/10.1007/s12639-012-0133-0

Kennedy, D., A. Samali and R. Jäger (2015), “Methods for studying ER stress and UPR markers in human cells”, Methods in molecular biology (Clifton, N.J.), Vol. 1292, Springer, New York, https://doi.org/10.1007/978-1-4939-2522-3_1

Kim, E. K. and E. J. Choi (2010), “Pathological roles of MAPK signaling pathways in human diseases”, Biochimica et biophysica acta, Vol. 802/4, Elsevier, Amsterdam, https://doi.org/10.1016/j.bbadis.2009.12.009

Kim, W. et al. (2019), “Cellular Stress Responses in Radiotherapy.” Cells, Vol. 8/9, Multidisciplinary Digital Publishing Institute, Basel, https://doi.org/10.3390/cells8091105

Kruiswijk, F., C. F. Labuschagne and K. H. Vousden (2015), “p53 in survival, death and metabolic health: a lifeguard with a licence to kill”, Nature Reviews Molecular Cell Biology, Vol. 16/7, Springer, New York, https://doi.org/10.1038/nrm4007

Liu, T. et al. (2017), “NF-κB signaling in inflammation”, Signal transduction and targeted therapy, Vol. 2, Springer, New York, https://doi.org/10.1038/sigtrans.2017.23

Manning, B. D., and L. C. Cantley (2007), “AKT/PKB signaling: navigating downstream”, Cell, Vol. 129/7, Elsevier, Amsterdam, https://doi.org/10.1016/j.cell.2007.06.009

Mao, P. et al. (2023), “CXCL5 promotes tumorigenesis and angiogenesis of glioblastoma via JAK-STAT/NF-κB signaling pathways”, Molecular biology reports, Vol. 50/10, Springer, New York, https://doi.org/10.1007/s11033-023-08671-3

Martini, M. et al. (2014), “PI3K/AKT signaling pathway and cancer: an updated review”, Annals of medicine, Vol. 46/6, Taylor & Francis, Oxfordshire, https://doi.org/10.3109/07853890.2014.912836

Meier-Soelch, J. et al. (2021), “Monitoring the Levels of Cellular NF-κB Activation State”, Cancers, Vol. 13/21, Multidisciplinary Digital Publishing Institute, Basel, https://doi.org/10.3390/cancers13215351

Mendes, F., et al. (2015), “Effects of X-radiation on lung cancer cells: the interplay between oxidative stress and P53 levels”, Medical oncology (Northwood, London, England), Vol. 32/12, Springer, New York, https://doi.org/10.1007/s12032-015-0712-x
Morrison D. K. (2012), "MAP kinase pathways", Cold Spring Harbor perspectives in biology, Vol. 4/11, https://doi.org/10.1101/cshperspect.a011254

Nair, A. et al. (2019), “Conceptual Evolution of Cell Signaling”, International journal of molecular sciences, Vol. 20/13, Multidisciplinary Digital Publishing Institute, Basel, https://doi.org/10.3390/ijms20133292su

Nogueira, K. M., et al. (2015), “Evidence of cAMP involvement in cellobiohydrolase expression and secretion by Trichoderma reesei in presence of the inducer sophorose”, BMC microbiology, Vol. 15, Springer, London, https://doi.org/10.1186/s12866-015-0536-z

Ou, H. L. and B. Schumacher (2018), “DNA damage responses and p53 in the aging process”, Blood, Vol. 131/5, https://doi.org/10.1182/blood-2017-07-746396

Palli, R., M. G. Palshikar and J. Thakar (2019), “Executable pathway analysis using ensemble discrete-state modeling for large-scale data”, PLoS computational biology, Vol. 15/9, PLOS, San Francisco, https://doi.org/10.1371/journal.pcbi.1007317

Qin, Y. et al. (2023), “A pan-cancer analysis of the MAPK family gene and their association with prognosis, tumor microenvironment, and therapeutic targets”, Medicine, Vol. 102/45, Wolters Kluwer, Alphen aan den Rijn, https://doi.org/10.1097/MD.00000000000035829

Ramaswami, S. and M.S. Hayden (2015), “Electrophoretic mobility shift assay analysis of NF-κB DNA binding”, Methods in molecular biology (Clifton, N.J.), Vol. 1280, Springer, New York, https://doi.org/10.1007/978-1-4939-2422-6_1

Ron, D., and P. Walter (2007), “Signal integration in the endoplasmic reticulum unfolded protein response”, Nature reviews. Molecular cell biology, Vol. 8/7, Springer, New York, https://doi.org/10.1038/nrm2199

Sita, G. et al. (2023), “The Unfolded Protein Response in a Murine Model of Alzheimer's Disease: Looking for Predictors”, International journal of molecular sciences, Vol. 24/22, Multidisciplinary Digital Publishing Institute, Basel, https://doi.org/10.3390/ijms242216200

Steinberg, G. R. and D. G. Hardie (2023), “New insights into activation and function of the AMPK”, Nature reviews. Molecular cell biology, Vol. 24/4, Springer, London, https://doi.org/10.1038/s41580-022-00547-x

Su, Y. T. et al. (2020), “Acid sphingomyelinase/ceramide mediates structural remodeling of cerebral artery and small mesenteric artery in simulated weightless rats”, Life Sciences, Vol. 243, Elsevier, Amsterdam, https://doi.org/10.1016/j.lfs.2019.117253

Tan, B.,et al. (2022), “Changes in the histopathology and in the proteins related to the MAPK pathway in the brains of rats exposed to pre and postnatal radiofrequency radiation over four generations”, Journal of chemical neuroanatomy, Vol.126, Elsevier, Amsterdam, https://doi.org/10.1016/j.jchemneu.2022.102187

Thakur, S. S., et al. (2019), “Expression and localization of heat-shock proteins during skeletal muscle cell proliferation and differentiation and the impact of heat stress”, Cell stress & chaperones, Vol. 24/2, Elsevier, Amsterdam, https://doi.org/10.1007/s12192-019-01001-2

Vousden, K. H. and C. Prives (2009), “Blinded by the Light: The Growing Complexity of p53”, Cell, Vol. 137/3, Elsevier, Amsterdam, https://doi.org/10.1016/j.cell.2009.04.037
Wei, S. et al. (2024), “DCAF13 inhibits the p53 signaling pathway by promoting p53 ubiquitination modification in lung adenocarcinoma.” Journal of experimental & clinical cancer research: CR, Vol. 43/1, Springer, London, https://doi.org/10.1186/s13046-023-02936-2

Xia, Z., Li, Q. and Z. Tang (2023), “Network pharmacology, molecular docking, and experimental pharmacology explored Ermiao wan protected against periodontitis via the PI3K/AKT and NF-kB/MAPK signal pathways.” Journal of ethnopharmacology, Vol. 303, Elsevier, Amsterdam, https://doi.org/10.1016/j.jep.2022.115900

Xin, P., et al. (2020), “The role of JAK/STAT signaling pathway and its inhibitors in diseases.” International immunopharmacology, Vol. 80, Elsevier, Amsterdam, https://doi.org/10.1016/j.intimp.2020.106210

Yentrapalli, R. et al. (2013), “The PI3K/Akt/mTOR pathway is implicated in the premature senescence of primary human endothelial cells exposed to chronic radiation”, PloS one, Vol. 8/8, PLOS, San Francisco, https://doi.org/10.1371/journal.pone.0070024

Yue, J. and J. M. López (2020), “Understanding MAPK Signaling Pathways in Apoptosis”, International journal of molecular sciences, Vol. 21/7, Multidisciplinary Digital Publishing Institute, Basel, https://doi.org/10.3390/ijms21072346

Zhang, H., et al. (2024), “cAMP-PKA/EPAC signaling and cancer: the interplay in tumor microenvironment.” Journal of hematology & oncology, Vol. 9/1, Springer, New York, https://doi.org/10.1186/s13045-024-01524-x

Zhang, J., et al. (2021), “PKA-RIIβ autophosphorylation modulates PKA activity and seizure phenotypes in mice”, Communications biology, Vol. 4/1, Springer, London, https://doi.org/10.1038/s42003-021-01748-4

Zheng, W., et al. (2019), “ATG5 and ATG7 induced autophagy interplays with UPR via PERK signaling.” Cell communication and signaling: CCS, Vol. 17/1, Springer, London https://doi.org/10.1186/s12964-019-0353-3

Zhu, G., et al. (2016), “Radiotherapy Suppresses Bone Cancer Pain through Inhibiting Activation of cAMP Signaling in Rat Dorsal Root Ganglion and Spinal Cord.” Mediators of inflammation, Vol. 2016, John Wiley & Sons, Ltd., Hoboken, https://doi.org/10.1155/2016/5093095

Zininga, T., L. Ramatsui and A. Shonhai (2018), “Heat Shock Proteins as Immunomodulants”, Molecules (Basel, Switzerland), Vol 23/11, Multidisciplinary Digital Publishing Institute, Basel, https://doi.org/10.3390/molecules23112846
**Event: 1492: Tissue resident cell activation**

**Short Name: Tissue resident cell activation**

**Key Event Component**

<table><thead><tr><td>Process</td><td>Object</td><td>Action</td></tr></thead><tbody><tr><td>cell activation involved in immune 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: 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>Key Event</td></tr><tr><td>AOP: 38 - Protein Alkylation leading to Liver Fibrosis</td><td>Key Event</td></tr><tr><td>AOP: 293 - Increased DNA damage leading to increased risk of breast cancer</td><td>Key Event</td></tr><tr><td>AOP: 294 - Increased reactive oxygen and nitrogen species (RONS) leading to increased risk of breast cancer</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></tbody></table>

**Biological context**

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

**Domain of Applicability**

Extend to at least invertebrates. Not to plants and not to single-celled organisms.

**BRAIN:** Tissue resident activation is observed in human, monkey, rat, mouse, and zebrafish, in association with neurodegeneration or following toxicant exposure. Some references (non-exhaustive list) are given below for illustration:

Human: Vennetti et al., 2006

Monkey (Macaca fascicularis): Charleston et al., 1994, 1996

Rat: Little et al., 2012; Zurich et al., 2002; Eskes et al., 2002

Mouse: Liu et al., 2012

Zebrafish: Xu et al., 2014.

**LIVER:**

Human: Su et al., 2002; Kegel et al., 2015; Boltjes et al., 2014

Rat: Luckey and Peterson, 2001

Mouse: Dalton t al., 2009

**Taxonomic Applicability**

Tissue resident activation is observed in human, monkey, rat, mouse, and zebrafish, in association with neurodegeneration or following toxicant exposure. (Vennetti et al., 2006; Charleston et al., 1994, 1996; Little et al., 2012; Zurich et al., 2002; Eskes et al., 2002; Liu et al., 2012; Xu et al., 2014, Su et al., 2002; Kegel et al., 2015; Boltjes et al., 2014, Luckey and Peterson, 2001, Dalton t al., 2009).

<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></td><td>NCBI</td></tr><tr><td>Macaca fascicularis</td><td>Macaca fascicularis</td><td></td><td>NCBI</td></tr><tr><td>rat</td><td>Rattus norvegicus</td><td></td><td>NCBI</td></tr><tr><td>mouse</td><td>Mus musculus</td><td></td><td>NCBI</td></tr><tr><td>zebrafish</td><td>Danio rerio</td><td></td><td>NCBI</td></tr></tbody></table>