AOP ID and Title:

Short Title: Deposition of Energy Leading to Learning and Memory Impairment

Authors

Ahmad Sleiman¹, Kathleen Miller², Danicia Flores³, Jaqueline Kuan³, Kaitlyn Altwasser³, Benjamin Smith³, Tatiana Kozbenko³, Robyn Hocking³, Carole Yauk⁴, Ruth Wilkins³, Vinita Chauhan³  

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

(2) National Institute of Aerospace, Hampton, Virginia, USA 

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

(4) 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), Tokyo, Japan

 

Status

Abstract

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 signaling pathways, neuroinflammation, and their interactions, leading to eventual 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 signaling pathways (KE#2066) 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 signaling pathways have adjacent connections with 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 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. 

Background

Understanding the impact of ionizing radiation on non cancer outcomes of the central nervous system (CNS) is essential as there are many possibilities for exposure including from medical procedures and occupational settings (e.g. astronuats). Various studies have reported cognitive deficits after high-doses of radiation from radiotherapy treatments, 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, and neuronal 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). Thus far, direct pathways linking  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 starting pathway for expansion to other cognitive disorders and CNS diseases from an MIE of deposition of energy. 

Summary of the AOP

Events

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

Key Event Relationships

Stressors

Overall Assessment of the AOP

Summary of evidence (KE & KER relationships and evidence) 

This AOP was derived from data that investigates the CNS of humans, animals and cellular models following exposure to ionizing radiation. Stressors in the present pathway include a range of doses (low (<0.1 Gy) to high (>1 Gy) doses), dose rates and radiation qualities (low-LET and high-LET) with an emphasis on low-to-moderate (0.1-1 Gy) dose heavy-ion studies relevant to space travel. The goal of this AOP is to model the connectivity of the MIE of deposition of energy through the cellular and biological KEs that lead to the AO of impaired learning and memory. The KEs chosen for this AOP had strong biological plaucibility with available empirical evidence, however, other KEs may be added later to incorporate new mechanisms and AOs into its broader network. The pathway is applicable to  multiple stressors of deposition of energy including 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 mechanistic 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 signaling pathways. 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 signaling pathways can lead to neural remodeling. Various pro-inflammatory cytokines can affect neural remodeling, 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 influences 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 neuronal 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 signaling pathways (Suman et al., 2013). 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 of 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 increases 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 key events 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 in 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).  

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

There were multiple challenges present in the development of this AOP which identified 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. 

Domain of Applicability

Life Stage Applicability Taxonomic Applicability Sex Applicability

 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. 

 

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 signaling pathways (KE#2066) 

• 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 signaling (KE#2066) 

• 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 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 Signaling Pathways (KE#2066)  

• The effects of modulating cell signaling on 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 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 Neural Remodeling (KE#2098) 

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

Weight of Evidence Summary

 

1. Support for Biological Plausibility of KERs	Defining Question	High (Strong)	Moderate	Low (Weak)
	Is there a mechanistic relationship between KEup and KEdown consistent with established biological knowledge?	Extensive understanding of the KER based on extensive previous documentation and broad acceptance; Established mechanistic basis	KER is plausible based on analogy to accepted biological relationships, but scientific understanding is not completely established	There is empirical support for statistical association between KEs, but the structural or functional relationship between them is not understood
Deposition of Energy (MIE, KE#1686) → Oxidative Stress (KE#1392)	High  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.
Deposition of Energy (MIE, KE#1686) → Tissue Resident Cell Activation (KE#1492)	High  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.
Oxidative Stress (KE#1392) → Increase, DNA Strand Breaks (KE#1635)	High  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.
Increase, DNA Strand Breaks (KE#1635) → Altered Signaling Pathways (KE#2066)	High  There is high evidence surrounding biological plausibility of increased DNA strand breaks to altered signaling pathways.  DNA strand breaks induce DNA damage responses which result in the induction of various signaling pathways.
Oxidative Stress (KE#1392) → Tissue Resident Cell Activation (KE#1492)	Moderate  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.
Oxidative Stress (KE#1392) → Altered Signaling Pathways (KE#2066)	High  There is high evidence surrounding the biological plausibility of increased oxidative stress to altered signaling pathways. Oxidative stress can lead to altered signaling pathways 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.
Altered Signaling Pathways  (KE#2066) → Increase, Neural Remodeling (KE#2098)	Moderate  There is moderate evidence surrounding biological plausibility of altered signaling pathways to neural remodeling. 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 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.
Tissue Resident Cell Activation (KE#1492) → Increase, Pro-inflammatory Mediators (KE#2097)	High  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 chemokines can also increase the permeability of the blood-brain barrier, further increasing pro-inflammatory mediator levels.
Increase, Pro-inflammatory Mediators (KE#2097) → Increase, Neural Remodeling (KE#2098)	Moderate  There is moderate evidence surrounding the biological plausibility of increased pro-inflammatory mediators to 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.
Increase, Neural Remodeling (KE#2098) → Impairment, Learning and Memory (AO, KE#341)	Moderate  There is moderate evidence surrounding biological plausibility of neural remodeling leading to impaired learning and memory. Evidence of 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.
Deposition of Energy (MIE, KE# 1686) →  Increase, Neural Remodeling (KE#2098)	Moderate  There is moderate evidence surrounding biological plausibility of deposition of energy to neural remodeling. Irradiation induces oxidative stress and neuroinflammation, which alter neuronal integrity. Many reviews examine the radiation-induced neuronal damage and identify correlation with oxidative stress and neuroinflammatory mechanisms.
Deposition of Energy (MIE, KE#1686) → Impairment, Learning and Memory (AO, KE#341)	High  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 behavioural 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.
Deposition of Energy (MIE, KE#1686) → Increase, DNA Strand Breaks (KE#1635)	High  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.
Increase, DNA Strand Breaks (KE#1635) → Increase, Neural Remodeling (KE#2098)	Moderate  There is moderate evidence surrounding biological plausibility of increased DNA strand breaks to increase, neural remodeling. DNA strand breaks may initiate apoptotic signaling and impact synaptic activity, neural plasticity, differentiation, and proliferation.
Pro-inflammatory Mediators (KE#2097) → Impairment, Learning and Memory (AO, KE#341)	Moderate  There is moderate support for the 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.

Review of the Empirical support for each KER	Defining Question	High (Strong)	Moderate	Low (Weak)
	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?	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.	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	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
Deposition of Energy (MIE, KE#1686) → Oxidative Stress (KE#1392)	High   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.
Deposition of Energy (MIE, KE#1686) → Tissue Resident Cell Activation (KE#1492)	Moderate   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 low dose studies, as well as time ranges from hours to months, though additional studies at low-doses would improve empirical support.
Oxidative Stress (KE#1392) → Increase, DNA Strand Breaks (KE#1635)	Moderate  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.
Increase, DNA Strand Breaks (KE#1635) → Altered Signaling Pathways (KE#2066)	Moderate  A few studies demonstrate dose-concordance, and multiple studies demonstrate time-concordance for this relationship. DNA strand breaks were observed prior to altered signaling pathways.
Oxidative Stress (KE#1392) → Tissue Resident Cell Activation (KE#1492)	Moderate   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.
Oxidative Stress (KE#1392) → Altered Signaling Pathways (KE#2066)	Moderate   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.
Altered Signaling Pathways (KE#2066)  Increase, Neural Remodeling (KE#2098)	Moderate   Many studies demonstrate dose-concordance in multiple signaling pathways. Studies have also shown that signaling pathways are altered before 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.
Tissue Resident Cell Activation (KE#1492) → Increase, Pro-inflammatory Mediators (KE#2097)	Moderate   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.
Increase, Pro-inflammatory Mediators (KE#2097) → Increase, Neural Remodeling (KE#2098)	Moderate   There are multiple studies that show time-concordance, though studies on dose-concordance are lacking. Studies suggest that pro-inflammatory mediators are increased before 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.
Increase, Neural Remodeling (KE#2098) → Impairment, Learning and Memory (AO, KE#341)	Moderate   Multiple studies suggest dose- and time-response effects of deposited energy leading to 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.
Deposition of Energy (MIE, KE#1686) →  Increase, Neural Remodeling (KE#2098)	Moderate   Multiple studies suggest dose- and time-response effects of deposition of energy to neuronal 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.
Deposition of Energy (MIE, KE#1686) → Impairment, Learning and Memory (AO, KE#341)	Moderate   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.
Deposition of Energy (MIE, KE#1686) → Increase, DNA Strand Breaks (KE#1635)	High  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.
Increase, DNA Strand Breaks (KE#1635) → Increase, Neural Remodeling (KE#2098)	Moderate  Multiple studies demonstrate that increased DNA strand breaks lead to increased neural remodeling. However, additional studies describing both dose-concordance and time-concordance would improve empirical support.
Increase, Pro-inflammatory Mediators (KE#2097) → Impairment, Learning and Memory (AO, KE#341)	Moderate   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.

Support for Essentiality of KEs	Defining Question		High (Strong)	Moderate	Low (Weak)
	Are downstream KEs and/or the AO prevented if an upstream KE is blocked?		Direct evidence from specifically designed experimental studies illustrating essentiality for at least one of the important KEs	Indirect evidence that sufficient modification of an expected modulating factor attenuates or augments a KE	No or contradictory experimental evidence of the essentiality of any of the KEs
MIE, KE#1686: Deposition of energy		Moderate  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.
KE#1392: Oxidative stress		Moderate  Treatments with antioxidants, which reduce oxidative stress, attenuate downstream microglial activation and DNA strand breaks.
KE#1635: Increase, DNA Strand Breaks		Moderate  Prevention of DNA strand breaks, for example treatment with mesenchymal stem cell-conditioned medium or minocycline, has restored altered signaling and neural remodeling.
KE#2066: Altered Signaling Pathways		Moderate  Knockout models or inhibition of key signaling molecules, have all been shown to influence the effects of signaling pathways on 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.
KE#1492: Tissue Resident Cell Activation		Moderate  For example, the attenuation of the activation of tissue-resident cells and consequent reduction in pro-inflammatory mediators has been reported using multiple drugs.
KE#2097: Increase, Pro-inflammatory Mediators		Moderate  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.
KE#2098: Neural Remodeling		Moderate  No identified studies describe essentiality of neural remodeling as it cannot be blocked / decreased using chemicals.

Quantitative Consideration

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.

Considerations for Potential Applications of the AOP (optional)

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 qualitaive 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.

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Appendix 1

List of MIEs in this AOP

Event: 1686: Deposition of Energy

Short Name: Energy Deposition

AOPs Including This Key Event

Stressors

Biological Context

Evidence for Perturbation by Stressor

Overview for Molecular Initiating Event

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

Domain of Applicability

Taxonomic Applicability Life Stage Applicability Sex 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.  

Life stage applicability: This MIE is not life stage specific. 

Sex applicability: This MIE is not sex specific. 

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 energy of these subatomic particles or electromagnetic waves mostly range from 124 KeV to 5.4 MeV and is dependent on the source and type of radiation (Zyla et al., 2020). To be ionizing the incident radiation must have sufficient energy to free electrons from atomic or molecular electron orbitals. The energy deposited can induce direct and indirect ionization events and this can be via internal (injections, inhalation, or absorption of radionuclides) or external exposure from radiation fields -- this also applies to non-ionizing radiation.

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

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

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

How it is Measured or Detected

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

 

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. 

 

 

List of Key Events in the AOP

Event: 1392: Oxidative Stress

Short Name: Oxidative Stress

Key Event Component

AOPs Including This Key Event

Stressors

Biological Context

Evidence for Perturbation by Stressor

Platinum

Kruidering et al. (1997) examined the effect of platinum on pig kidneys and found that it was able to induce significant dose-dependant ROS formation within 20 minutes of treatment administration.

Aluminum

In a study of the effects of aluminum treatment on rat kidneys, Al Dera (2016) found that renal GSH, SOD, and GPx levels were significantly lower in the treated groups, while lipid peroxidation levels were significantly increased.

Cadmium

Belyaeva et al. (2012) investigated the effect of cadmium treatment on human kidney cells. They found that cadmium was the most toxic when the sample was treated with 500 μM for 3 hours (Belyaeva et al., 2012). As this study also looked at mercury, it is worth noting that mercury was more toxic than cadmium in both 30-minute and 3-hour exposures at low concentrations (10-100 μM) (Belyaeva et al., 2012).

Wang et al. (2009) conducted a study evaluating the effects of cadmium treatment on rats and found that the treated group showed a significant increase in lipid peroxidation. They also assessed the effects of lead in this study, and found that cadmium can achieve a very similar level of lipid peroxidation at a much lower concentration than lead can, implying that cadmium is a much more toxic metal to the kidney mitochondria than lead is (Wang et al., 2009). They also found that when lead and cadmium were applied together they had an additive effect in increasing lipid peroxidation content in the renal cortex of rats (Wang et al., 2009).

Jozefczak et al. (2015) treated Arabidopsis thaliana wildtype, cad2-1 mutant, and vtc1-1 mutant plants with cadmium to determine the effects of heavy metal exposure to plant mitochondria in the roots and leaves. They found that total GSH/GSG ratios were significantly increased after cadmium exposure in the leaves of all sample varieties and that GSH content was most significantly decreased for the wildtype plant roots (Jozefczak et al., 2015).

Andjelkovic et al. (2019) also found that renal lipid peroxidation was significantly increased in rats treated with 30 mg/kg of cadmium.

Mercury

Belyaeva et al. (2012) conducted a study which looked at the effects of mercury on human kidney cells, they found that mercury was the most toxic when the sample was treated with 100 μM for 30 minutes.

Buelna-Chontal et al. (2017) investigated the effects of mercury on rat kidneys and found that treated rats had higher lipid peroxidation content and reduced cytochrome c content in their kidneys.

Uranium

In Shaki et al.’s article (2012), they found rat kidney mitochondria treated with uranyl acetate caused increased formation of ROS, increased lipid peroxidation, and decreased GSH content when exposed to 100 μM or more for an hour.

Hao et al. (2014), found that human kidney proximal tubular cells (HK-2 cells) treated with uranyl nitrate for 24 hours with 500 μM showed a 3.5 times increase in ROS production compared to the control. They also found that GSH content was decreased by 50% of the control when the cells were treated with uranyl nitrate (Hao et al., 2014).

Arsenic

Bhadauria and Flora (2007) studied the effects of arsenic treatment on rat kidneys. They found that lipid peroxidation levels were increased by 1.5 times and the GSH/GSSG ratio was decreased significantly (Bhadauria and Flora, 2007).

Kharroubi et al. (2014) also investigated the effect of arsenic treatment on rat kidneys and found that lipid peroxidation was significantly increased, while GSH content was significantly decreased.

In their study of the effects of arsenic treatment on rat kidneys, Turk et al. (2019) found that lipid peroxidation was significantly increased while GSH and GPx renal content were decreased.

Silver

Miyayama et al. (2013) investigated the effects of silver treatment on human bronchial epithelial cells and found that intracellular ROS generation was increased significantly in a dose-dependant manner when treated with 0.01 to 1.0 μM of silver nitrate.

Manganese

Chtourou et al. (2012) investigated the effects of manganese treatment on rat kidneys. They found that manganese treatment caused significant increases in ROS production, lipid peroxidation, urinary H₂O₂ levels, and PCO production. They also found that intracellular GSH content was depleted in the treated group (Chtourou et al., 2012).

Nickel

Tyagi et al. (2011) conducted a study of the effects of nickel treatment on rat kidneys. They found that the treated rats showed a significant increase in kidney lipid peroxidation and a significant decrease in GSH content in the kidney tissue (Tyagi et al., 2011).

Zinc

Yeh et al. (2011) investigated the effects of zinc treatment on rat kidneys and found that treatment with 150 μM or more for 2 weeks or more caused a time- and dose-dependant increase in lipid peroxidation. They also found that renal GSH content was decreased in the rats treated with 150 μM or more for 8 weeks (Yeh et al., 2011).

It should be noted that Hao et al. (2014) found that rat kidneys exposed to lower concentrations of zinc (such as 100 μM) for short time periods (such as 1 day), showed a protective effect against toxicity induced by other heavy metals, including uranium. Soussi, Gargouri, and El Feki (2018) also found that pre-treatment with a low concentration of zinc (10 mg/kg treatment for 15 days) protected the renal cells of rats were from changes in varying oxidative stress markers, such as lipid peroxidation, protein carbonyl, and GPx levels.

nanoparticles

Huerta-García et al. (2014) conducted a study of the effects of titanium nanoparticles on human and rat brain cells. They found that both the human and rat cells showed time-dependant increases in ROS when treated with titanium nanoparticles for 2 to 6 hours (Huerta-García et al., 2014). They also found elevated lipid peroxidation that was induced by the titanium nanoparticle treatment of human and rat cell lines in a time-dependant manner (Huerta-García et al., 2014).

Liu et al. (2010) also investigated the effects of titanium nanoparticles, however they conducted their trials on rat kidney cells. They found that ROS production was significantly increased in a dose dependant manner when treated with 10 to 100 μg/mL of titanium nanoparticles (Liu et al., 2010).

Pan et al. (2009) treated human cervix carcinoma cells with gold nanoparticles (Au1.4MS) and found that intracellular ROS content in the treated cells increased in a time-dependant manner when treated with 100 μM for 6 to 48 hours. They also compared the treatment with Au1.4MS gold nanoparticles to treatment with Au15MS treatment, which are another size of gold nanoparticle (Pan et al., 2009). The Au15MS nanoparticles were much less toxic than the Au1.4MS gold nanoparticles, even when the Au15MS nanoparticles were applied at a concentration of 1000 μM (Pan et al., 2009). When investigating further markers of oxidative stress, Pan et al. (2009) found that GSH content was greatly decreased in cells treated with gold nanoparticles.

Ferreira et al. (2015) also studied the effects of gold nanoparticles. They exposed rat kidneys to GNPs-10 (10 nm particles) and GNPs-30 (30 nm particles), and found that lipid peroxidation and protein carbonyl content in the rat kidneys treated with GNPs-30 and GNPs-10, respectively, were significantly elevated.

Domain of Applicability

Taxonomic Applicability Life Stage Applicability Sex Applicability

Taxonomic applicability: Occurrence of oxidative stress is not species specific.  

Life stage applicability: Occurrence of oxidative stress is not life stage specific. 

Sex applicability: Occurrence of oxidative stress is not sex specific. 

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 (2SH àSS) on neighboring amino acids (Antelmann and 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). 

Protection against oxidative stress is relevant for all tissues and organs, although some tissues may be more susceptible. For example, the brain possesses several key physiological features, such as high O2 utilization, high polyunsaturated fatty acids content, presence of autooxidable neurotransmitters, and low antioxidant defenses as compared to other organs, that make it highly susceptible to oxidative stress (Halliwell, 2006; Emerit and al., 2004; Frauenberger et al., 2016).

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 (P_i) (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 have its own set of DNA and it is a prime target of oxidative damage (Guo et al., 2013). ROS are 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

 

Assay Type & Measured Content	Description	Dose Range Studied	Assay Characteristics (Length / Ease of use/Accuracy)
ROS Formation in the Mitochondria assay (Shaki et al., 2012)	“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, 10 mM 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.”	0, 50, 100 and 200 μM of Uranyl Acetate	Long/ Easy High accuracy
Mitochondrial Antioxidant Content Assay Measuring GSH content (Shaki et al., 2012)	“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.”	0, 50, 100, or 200 μM Uranyl Acetate
H2O2 Production Assay Measuring H2O2 Production in isolated mitochondria (Heyno et al., 2008)	“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.” (	0, 10, 30  μM Cd2+ 2  μM antimycin A
Flow Cytometry ROS & Cell Viability (Kruiderig et al., 1997)	“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)”		Strong/easy medium
DCFH-DA Assay Detection of hydrogen peroxide production (Yuan et al., 2016)	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.	0-400 µM	Long/ Easy High accuracy
H2-DCF-DA Assay Detection of superoxide production (Thiebault et al., 2007)	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.	0–600 µM	Long/ Easy High accuracy
CM-H2DCFDA Assay	**Come back and explain the flow cytometry determination of oxidative stress from Pan et al. (2009)**

Direct Methods of Measurement

Method of Measurement	References	Description	OECD-Approved Assay
Chemiluminescence	(Lu, C. et al., 2006;  Griendling, K. K., et al., 2016)	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 uminol and lucigenin are commonly used to amplify the signal.	No
Spectrophotometry	(Griendling, K. K., et al., 2016)	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.	No
Direct or Spin Trapping-Based Electron Paramagnetic Resonance (EPR) Spectroscopy	(Griendling, K. K., et al., 2016)	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.	No
Nitroblue Tetrazolium Assay	(Griendling, K. K., et al., 2016)	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.	No
Fluorescence analysis of dihydroethidium (DHE) or Hydrocyans	(Griendling, K. K., et al., 2016)	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.	No
Amplex Red Assay	(Griendling, K. K., et al., 2016)	Fluorescence analysis to measure extramitochondrial or extracellular H2O2 levels. In the presence of horseradish peroxidase and H2O2, Amplex Red is oxidized to resorufin, a fluorescent molecule measurable by plate reader.	No
Dichlorodihydrofluorescein Diacetate (DCFH-DA)	(Griendling, K. K., et al., 2016)	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.	No
HyPer Probe	(Griendling, K. K., et al., 2016)	Fluorescent measurement of intracellular H2O2 levels. HyPer is a genetically encoded fluorescent sensor that can be used for in vivo and in situ imaging.	No
Cytochrome c Reduction Assay	(Griendling, K. K., et al., 2016)	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.	No
Proton-electron double-resonance imagine (PEDRI)	(Griendling, K. K., et al., 2016)	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.	No
Glutathione (GSH) depletion	(Biesemann, N. et al., 2018)	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).	No
Thiobarbituric acid reactive substances (TBARS)	(Griendling, K. K., et al., 2016)	Oxidative damage to lipids can be measured by assaying for lipid peroxidation with TBARS using a commercially available kit.	No
Protein oxidation (carbonylation)	(Azimzadeh et al., 2017; Azimzadeh etal., 2015; Ping et al., 2020)	Can be determined with enzyme-linked immunosorbent assay (ELISA) or a commercial assay kit. Protein oxidation can indicate the level of oxidative stress.	No
Seahorse XFp Analyzer	Leung et al. 2018	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).	No

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

Method of Measurement	References	Description	OECD-Approved Assay
Immunohistochemistry	(Amsen, D., de Visser, K. E., and Town, T., 2009)	Immunohistochemistry for increases in Nrf2 protein levels and translocation into the nucleus	No
Quantitative polymerase chain reaction (qPCR)	(Forlenza et al., 2012)	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)	No
Whole transcriptome profiling via microarray or via RNA-seq followed by a pathway analysis	(Jackson, A. F. et al., 2014)	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	No

References

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Event: 2066: Altered Signaling Pathways

Short Name: Altered Signaling

AOPs Including This Key Event

Biological Context

Domain of Applicability

Taxonomic Applicability Life Stage Applicability Sex Applicability

Taxonomic applicability: Altered 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).

Life stage applicability: This key event is not life stage specific.

Sex applicability: This key event is not sex specific.

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 receive, process, and transmit signals to respond to their environment via signaling pathways. Signaling pathways are groups of molecules that work together in a cell to control physiological and metabolic processes. Kinases, for example, are important signaling molecules that can phosphorylate other proteins (Svoboda & Reenstra, 2002). Initiation of signaling pathways is an important component of cellular homeostasis including normal cell development and the response to cellular damage from exposure to external stressors (Esbenshade & Duzic, 2006). Signaling pathways are themselves activated by signals and the same signal can lead to different responses depending on the tissue type (Hamada, et al. 2011; Svoboda & Reenstra, 2002). Examples of signals include the activation of receptors to activate transcriptional targets, induction of receptor-ligand interactions and the initiation of cell-cell contact, or cell-extracellular matrix contact (Hunter, 2000). Many signalling pathways are crucial to intercellular communication via membrane receptors that transduce signals into the cell, while others are activated in an intracellular manner (Svoboda & Reenstra, 2002). Altered signalling (i.e., increase/decrease) can lead to different physiological outcomes, meaning that the directionality of the signaling response, determines the end outcome. For example, increase of the PI3K/Akt/mTOR pathway, which under physiological conditions is responsible for regulating the cell cycle, can lead to increased proliferation and decreased apoptosis. However, a decrease expression of this pathway can lead to an increase in apoptosis and decreased proliferation (Porta et al., 2014; Venkatesulu et al., 2018).

How it is Measured or Detected

Method of Measurement	Reference	Description	OECD Approved Assay
Kinase assays	(Svoboda & Reenstra, 2002)	Block kinase with inhibitors to monitor the activity of a kinase of interest.	No
Cell behaviour assays	(Svoboda & Reenstra, 2002)	Signal transduction events of cells are monitored. Cells are exposed to varying levels of signaling proteins and the resulting actions of a cell are observed (changes in structure, cell shape, matrix binding etc.).	No
Ratiometric or single-wavelength dyes	(Svoboda & Reenstra, 2002)	Detects alterations in signal-transduction activities via monitoring changes in detectable wavelengths.	No
Fluorescence microscopy/spectroscopy	(Oksvold et al., 2002)	Measures cell localization, protein interactions, signal propagation, amplification, and integration in the cell in real-time, or upon stimulation.	Yes
Green Fluorescent Protein (GFP)	(Zaccolo and Pozzan, 2000)	GFP assays act as fluorescent reporters but also as a marker of intracellular signalling events i.e. second messengers Ca2+ and cAMP, or for pH in different various cell compartments	No
Fluorescence Resonance Energy Transfer (FRET)	(Bunt and Wouters, 2017)	Assay helps illuminate the interactions between biological molecules	No
Fluorescence recovery after photobleaching (FRAP)	(Svoboda & Reenstra, 2002)	Determines mobility and diffusion of small molecules.	No
Immunoprecipitation	(Svoboda & Reenstra, 2002)	Involves isolating and concentrating a particular protein from mixed samples to detect changes in signalling molecule activity.	Chromatin immunoprecipitation approved for analyzing histone modifications
Immunohistochemistry	(Kurien et al., 2011; Svoboda & Reenstra, 2002)	Northern, western and southern blotting techniques can be used to visualize signal transduction events. For example, antibodies with recognition epitopes can be used to locate active configurations or phosphorylated proteins within a cell or cell lysate.	No
Reverse transcription-quantitative polymerase chain reaction (RT-qPCR)	(Veremeyko et al., 2012; Alwine et al, 1977)	Measures mRNA expression of the gene of interest.	No
Enzyme-linked immunosorbent assay (ELISA)	(Amsen et al., 2009; Engvall & Perlmann, 1972)	Plate-based assay technique using antibodies to detect presence of a protein in a liquid sample. Can be used to identify presence of a protein of interest especially in when in low concentrations	No

References

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

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

Bunt, G., and F. S. Wouters (2017), “FRET from single to multiplexed signaling events”, Biophysical reviews, Vol. 9, Springer, London, https://doi.org/10.1007/s12551-017-0252-z

Cheng, Y. P. et al. (2017), “Acid sphingomyelinase/ceramide regulates carotid intima-media thickness in simulated weightless rats”, Pflugers Archiv European Journal of Physiology, Vol. 469, Springer, New York, https://doi.org/10.1007/s00424-017-1969-z

Coleman, M. A. et al. (2015), “Low-dose radiation affects cardiac physiology: gene networks and molecular signaling in cardiomyocytes”,  American Journal of Physiology - Heart and Circulatory Physiology, Vol. 309/11, American Physiological Society, Rockville, https://doi.org/10.1152/ajpheart.00050.2015

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

Esbenshade, T. A., and E. Duzic (2006), “Overview of signal transduction”, Current Protocols in Pharmacology, Vol. 31/1, John Wiley & Sons, Ltd., Hoboken, https://doi.org/10.1002/0471141755.ph0201s31

Hamada, N. et al. (2011), “Signaling pathways underpinning the manifestations of ionizing radiation-induced bystander effects”, Current Molecular Pharmacology, Vol. 4/2, Bentham Science Publishers, Sharjah UAE, https://doi.org/10.2174/1874467211104020079

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

Kurien, B. T. et al. (2011), “An overview of Western blotting for determining antibody specificities for immunohistochemistry”, in Signal Transduction Immunohistochemistry Methods and Protocols, Springer, London, https://doi.org/10.1007/978-1-61779-024-9_3

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/ijms20133292

Oksvold, M. P. et al. (2002), “Fluorescent histochemical techniques for analysis of intracellular signaling”, The Journal of Histochemistry and Cytochemistry, Vol. 50/3, SAGE Publications, Thousand Oaks, https://doi.org/10.1177/002215540205000301

Porta, C., C. Paglino and A. Mosca (2014), “Targeting PI3K/Akt/mTOR Signaling in Cancer”, Frontiers in Oncology, Vol. 4, Frontiers Media SA, Lausanne, https://doi.org/10.3389/fonc.2014.00064

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

Svoboda, K. K. and W. R. Reenstra (2002), “Approaches to studying cellular signaling: a primer for morphologists”, The Anatomical record, Vol. 269/2, John Wiley & Sons, Ltd., Hoboken, https://doi.org/10.1002/ar.10074

Venkatesulu, B. P. et al. (2018), “Radiation-Induced Endothelial Vascular Injury: A Review of Possible Mechanisms”, JACC: Basic to Translational Science, Vol. 3/4, Elsevier, Amsterdam, https://doi.org/10.1016/j.jacbts.2018.01.014

Veremeyko, T. et al. (2012), “Detection of microRNAs in microglia by real-time PCR in normal CNS and during neuroinflammation”, Journal of Visualized Experiments: JoVE, Vol. 65, MyJove Corporation, Cambridge, https://doi.org/10.3791/4097

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

Zaccolo, M. and T. Pozzan (2000), “Imaging signal transduction in living cells with GFP-based probes”, IUBMB life, Vol. 49/5, John Wiley & Sons, Ltd., Hoboken, https://doi.org/10.1080/152165400410218

Event: 1492: Tissue resident cell activation

Short Name: Tissue resident cell activation

Key Event Component

AOPs Including This Key Event

Biological Context

Domain of Applicability

Taxonomic Applicability Life Stage 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

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

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

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

Key Event Description

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

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

Examples of well-characterized DAMPs (danger signals or alarmins) (Saïd-Sadier  and Ojcius, 2012)

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

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

Examples of Common markers are

• CD11b
• Iba1
• GFAP
• CD68
• CD86
• Mac-1
• NF-kB
• AP-1
• Jnk
• P38/mapk

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

BRAIN

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

Regulatory examples using the KE

Measurement of glial fibrillary acidic protein (GFAP) in brain tissue, whose increase is a marker of astrocyte reactivity, is required by the US EPA in rodent toxicity studies for fuel additives (40 CFR 79.67). It has been used on rare occasions for other toxicant evaluations.

LIVER:

Kupffer cells (KCs) are a specialized population of macrophages that reside in the liver; they were first described by Carl Wilhelm von Kupffer (1829–1902) [Haubrich 2004]. KCs constitute 80%-90% of the tissue macrophages in the reticuloendothelial system and account for approximately 15% of the total liver cell population [Bouwens et al., 1986].   They play an important role in normal physiology and homeostasis as well as participating in the acute and chronic responses of the liver to toxic compounds. Activation of KCs results in the release of an array of inflammatory mediators, growth factors, and reactive oxygen species. This activation appears to modulate acute hepatocyte injury as well as chronic liver responses including hepatic cancer. Understanding the role KCs play in these diverse responses is key to understanding mechanisms of liver injury [Roberts et al.,2007].  Besides the release of inflammatory mediators including cytokines, chemokines, lysosomal and proteolytic enzymes KCs are a main source of TGF-β1 (transforming growth factor-beta 1, the most potent profibrogenic cytokine). In addition latent TGF-β1 can be activated by KC-secreted matrix metalloproteinase 9 (MMP-9)[Winwood and Arthur, 1993; Luckey and Peeterson, 2001] through the release of biologically active substances that promote the pathogenic process. Activated KCs also release ROS like superoxide generated by NOX (NADPH oxidase), thus contributing to oxidative stress. Oxidative stress also activates a variety of transcription factors like NF-κB, PPAR-γ leading to an increased gene expression for the production of growth factors, inflammatory cytokines and chemokines. KCs express TNF-α (Tumor Necrosis Factor-alpha), IL-1 (Interleukin-1) and MCP-1 (monocyte-chemoattractant protein-1), all being mitogens and chemoattractants for hepatic stellate cells (HSCs) and induce the expression of PDGF receptors on HSCs which enhances cell proliferation. Expressed TNF-α, TRAIL (TNF-related apoptosis-inducing ligand), and FasL (Fas Ligand) are not only pro-inflammatory active but also capable of inducing death receptor-mediated apoptosis in hepatocytes [Guo and Friedman, 2007; Friedman 2002; Roberts et al., 2007]. Under conditions of oxidative stress macrophages are further activated which leads to a more enhanced inflammatory response that again further activates KCs though cytokines (Interferon gamma (IFNγ), granulocyte macrophage colony-stimulating factor (GM-CSF), TNF-α), bacterial lipopolysaccharides, extracellular matrix proteins, and other chemical mediators [Kolios et al., 2006; Kershenobich Stalnikowitz and Weissbrod 2003].

Besides KCs, the resident hepatic macrophages, infiltrating bone marrow-derived macrophages, originating from circulating monocytes are recruited to the injured liver via chemokine signals. KCs appear essential for sensing tissue injury and initiating inflammatory responses, while infiltrating Ly-6C+ monocyte-derived macrophages are linked to chronic inflammation and fibrogenesis. The profibrotic functions of KCs (HSC activation via paracrine mechanisms) during chronic hepatic injury remain functionally relevant, even if the infiltration of additional inflammatory monocytes is blocked via pharmacological inhibition of the chemokine CCL2 [Baeck et al., 2012; Tacke and Zimmermann, 2014].

KC activation and macrophage recruitment are two separate events and both are necessary for fibrogenesis, but as they occur in parallel, they can be summarised as one KE.

Probably there is a threshold of KC activation and release above which liver damage is induced. Pre-treatment with gadolinium chloride (GdCl), which inhibits KC function, reduced both hepatocyte and sinusoidal epithelial cell injury, as well as decreased the numbers of macrophages appearing in hepatic lesions and inhibited TGF-β1 mRNA expression in macrophages. Experimental inhibition of KC function or depletion of KCs appeared to protect against chemical-induced liver injury [Ide et al.,2005].  

How it is Measured or Detected

In General:

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

Available methods include cytometry, immunohistochemistry, gene expression sequencing; western blotting, ELISA, and functional assays.

BRAIN 

Neuroinflammation, i.e. the activation of glial cells can be measured by quantification of cellular markers (most commonly), or of released mediators (less common). As multiple activation states exist for the two main cell types involved, it is necessary to measure several markers of neuroinflammation:

1. Microglial activation can be detected based on the increased numbers of labeled microglia per volume element of brain tissue (due to increase of binding sites, proliferation, and immigration of cells) or on morphological changes. A specific microglial marker, used across different species, is CD11b. Alternatively various specific carbohydrate structures can be stained by lectins (e.g. IB4). Beyond that, various well-established antibodies are available to detect microglia in mouse tissue (F4/80), phagocytic microglia in rat tissue (ED1) or more generally microglia across species (Iba1). Transgenic mice are available with fluorescent proteins under the control of the CD11b promoter to easily quantify microglia without the need for specific stains.
2. The most frequently used astrocyte marker is glial fibrillary acidic protein, GFAP (99% of all studies) (Eng et al., 2000). This protein is highly specific for astrocytes in the brain, and antibodies are available for immunocytochemical detection. In neuroinflamatory brain regions, the stain becomes more prominent, due to an upregulation of the protein, a shape change/proliferation of the cells, and/or better accessibility of the antibody. Various histological quantification approaches can be used. Occasionally, alternative astrocytic markers, such as vimentin of the S100beta protein, have been used for astrocyte staining (Struzynska et al., 2007). Antibodies for complement component 3 (C3), the most characteristic and highly upregulated marker of A1 neurotoxic reactive astrocytes are commercially available.
3. All immunocytochemical methods can also be applied to cell culture models.
4. In patients, microglial accumulation can be monitored by PET imaging, using [11C]-PK 11195 as a microglial marker (Banati et al., 2002).
5. Activation of glial cells can be assessed in tissue or cell culture models also by quantification of sets of M1/M2 phenotype markers. This can for instance be done by PCR quantification, immunocytochemistry, immunoblotting.

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

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

LIVER:

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

References

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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. 

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Krukowski, K. et al. (2018), "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. 

Paladini, M. S. et al. (2021), "Microglia depletion and cognitive functions after brain injury: From trauma to galactic cosmic ray", Neuroscience Letters, Vol. 741, Elsevier, Amsterdam, https://doi.org/10.1016/j.neulet.2020.135462. 

Parihar, V. K. et al. (2016), "Cosmic radiation exposure and persistent cognitive dysfunction", Scientific Reports, Vol. 6/June, 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, Academic Press Inc., 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. 

Poulose, S. M. et al. (2011), "Exposure to 16O-particle radiation causes aging-like decrements in rats through increased oxidative stress, inflammation and loss of autophagy", Radiation Research, Vol. 176/6, BioOne, https://doi.org/10.1667/RR2605.1. 

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. 

Saïd-Sadier N, Ojcius DM., Alarmins, inflammasomes and immunity. Biomed J. 2012 Nov-Dec;35(6):437-49.

Schaefer L, Complexity of danger: the diverse nature of damage-associated molecular patterns, J Biol Chem. 2014 Dec 19;289(51):35237-45.

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, https://doi.org/10.18632/aging.100587. 

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Charleston JS, Body RL, Bolender RP, Mottet NK, Vahter ME, Burbacher TM. 1996. Changes in the number of astrocytes and microglia in the thalamus of the monkey Macaca fascicularis following long-term subclinical methylmercury exposure. NeuroToxicology 17: 127-138.

Charleston JS, Bolender RP, Mottet NK, Body RL, Vahter ME, Burbacher TM. 1994. Increases in the number of reactive glia in the visual cortex of Macaca fascicularis following subclinical long-term methyl mercury exposure. ToxicolApplPharmacol 129: 196-206.

Dong Y, Benveniste EN (2001) Immune Function of Astrocytes. Glia 36: 180-190

Eng LF, Ghirnikar RS, Lee YL (2000) Glial Fibrillary Acidic Protein: GFAP-Thirty-One Years (1969-2000). NeurochemRes 25: 1439-1451

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Lund S, Christensen KV, Hedtjärn M, Mortensen AL, Hagberg H, Falsig J, Hasseldam H, Schrattenholz A, Pörzgen P, Leist M. The dynamics of the LPS triggered inflammatory response of murine microglia under different culture and in vivo conditions. J Neuroimmunol. 2006 Nov;180(1-2):71-87.

Maresz K, Ponomarev ED, Barteneva N, Tan Y, Mann MK, Dittel BN (2008) IL-13 induces the expression of the alternative activation marker Ym1 in a subset of testicular macrophages. J Reprod Immunol 78: 140-148

Monnet-Tschudi F, Zurich MG, Honegger P (2007) Neurotoxicant-induced inflammatory response in three-dimensional brain cell cultures. Hum Exp Toxicol 26: 339-346

Monnet-Tschudi, F., A. Defaux, et al. (2011). "Methods to assess neuroinflammation." Curr Protoc Toxicol Chapter 12: Unit12 19.            

Mosser DM, Edwards JP (2008) Exploring the full spectrum of macrophage activation. Nat Rev Immunol 8: 958-969

Nakajima K, Kohsaka S. 2004. Microglia: Neuroprotective and neurotrophic cells in the central nervous system. Current Drug Targets-Cardiovasc & Haematol Disorders 4: 65-84.

Perego C, Fumagalli S, De Simoni MG (2011) Temporal pattern of expression and colocalization of microglia/macrophage phenotype markers following brain ischemic injury in mice. J Neuroinflammation 8: 174

Ponomarev ED, Maresz K, Tan Y, Dittel BN (2007) CNS-derived interleukin-4 is essential for the regulation of autoimmune inflammation and induces a state of alternative activation in microglial cells. J Neurosci 27: 10714-10721

Ponomarev ED, Shriver LP, Maresz K, Dittel BN (2005) Microglial cell activation and proliferation precedes the onset of CNS autoimmunity. J Neurosci Res 81: 374-389

Ransohoff RM. 2016. A polarizing question: do M1 and M2 microglia exist? Nat Neurosci 19(8): 987-991.

Sandstrom von Tobel, J., D. Zoia, et al. (2014). "Immediate and delayed effects of subchronic Paraquat exposure during an early differentiation stage in 3D-rat brain cell cultures." Toxicol Lett. DOI : 10.1016/j.toxlet.2014.02.001

Struzynska L, Dabrowska-Bouta B, Koza K, Sulkowski G (2007) Inflammation-Like Glial Response in Lead-Exposed Immature Rat Brain. Toxicol Sc 95:156-162

von Tobel, J. S., P. Antinori, et al. (2014). "Repeated exposure to Ochratoxin A generates a neuroinflammatory response, characterized by neurodegenerative M1 microglial phenotype." Neurotoxicology 44C: 61-70.

Venneti S, Lopresti BJ, Wiley CA. 2006. The peripheral benzodiazepine receptor (Translocator protein 18kDa) in microglia: from pathology to imaging. Prog Neurobiol 80(6): 308-322.

Xu DP, Zhang K, Zhang ZJ, Sun YW, Guo BJ, Wang YQ, et al. 2014. A novel tetramethylpyrazine bis-nitrone (TN-2) protects against 6-hydroxyldopamine-induced neurotoxicity via modulation of the NF-kappaB and the PKCalpha/PI3-K/Akt pathways. Neurochem Int 78: 76-85.

Zurich M-G, Eskes C, Honegger P, Bérode M, Monnet-Tschudi F. 2002. Maturation-dependent neurotoxicity of lead aceate in vitro: Implication of glial reactions. J Neurosc Res 70: 108-116.

LIVER:

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Dalton, S.R. et al. (2009), Carbon tetrachloride-induced liver damage in asialoglycoprotein receptor-deficient mice, Biochem Pharmacol, vol. 77, no. 7, pp. 1283-1290.

Friedman, S.L. (2002), Hepatic Fibrosis-Role of Hepatic Stellate Cell Activation, MedGenMed, vol. 4, no. 3, pp. 27.

Grønbaek, H. et al. (2012), Soluble CD163, a marker of Kupffer cell activation, is related to portal hypertension in patients with liver cirrhosis, Aliment Pharmacol Ther, vol 36, no. 2, pp. 173-180.

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Haubrich, W.S. (2004), Kupffer of Kupffer cells, Gastroenterology, vol. 127, no. 1, p. 16

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Kershenobich Stalnikowitz, D. and A.B. Weissbrod (2003), Liver Fibrosis and Inflammation. A Review, Annals of Hepatology, vol. 2, no. 4, pp.159-163.

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Event: 2097: Increase, Pro-Inflammatory Mediators

Short Name: Increase, Pro-Inflammatory Mediators

AOPs Including This Key Event

Biological Context

Domain of Applicability

Taxonomic Applicability Life Stage Applicability Sex Applicability

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

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

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

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

Key Event Description

(Adapted from KE 1493 - in blue)

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

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

This event occurs equally in various tissues and does not require tissue-specific descriptions. Nevertheless, there are some specificities such as the release of glutamate by brain reactive glial cells (Brown & Bal-Price, 2003; Vesce et al., 2007). The differences may rather reside in the type of insult favouring the increased expression and/or release of a specific class of inflammatory mediators, as well the time after the insult reflecting different stages of the inflammatory process. For these reasons, the analyses of the changes of a battery of inflammatory mediators rather than of a single one is a more adequate measurement of this KE.  

Table 1: a non-exhaustive list of examples for pro-inflammatory mediators 

Classes of inflammatory mediators	Examples
Pro-inflammatory cytokines	TNF- α, Interleukins (IL-1, IL-6, IL-8), Interferons (IFN-γ), chemokines (CXCL, CCL, GRO-α, MCP-1), GM-CSF
Prostaglandins	PGE2
Bioactive peptides	Bradykinin
Vasoactive amines	histamine, serotonin
Reactive oxygen species (ROS)	O2-, H2O2
Reactive nitrogen species (RNS)	NO, iNOS

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

Basically, this event occurs equally in various tissues and does not require tissue-specific descriptions. Nevertheless, there are some specificities such as the release of glutamate by brain reactive glial cells (Brown and Bal-Price, 2003; Vesce et al., 2007). The differences may rather reside in the type of insult favouring the increased expression and/or release of a specific class of inflammatory mediators, as well the time after the insult reflecting different stages of the inflammatory process. For these reasons, the analyses of the changes of a battery of inflammatory mediators rather than of a single one is a more adequate measurement of this KE. 

 

How it is Measured or Detected

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

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

 

References

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

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

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

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

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

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

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

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

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

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

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

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

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

Ismail, A. F. M., A.A.M. Salem and M.M.T. Eassawy (2016), “Modulation of gamma-irradiation and carbon tetrachloride induced oxidative stress in the brain of female rats by flaxseed oil”, Journal of Photochemistry and Photobiology B: Biology, Vol. 161, Elsevier, Amsterdam, https://doi.org/10.1016/J.JPHOTOBIOL.2016.04.031. 

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

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

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

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

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

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

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, Amsterdam, 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, https://doi.org/10.3389/fnbeh.2020.535885. 

Rollins, J. and V. Miskolci (2014), “Immunofluorescence and subsequent confocal microscopy of intracellular TNF in human neutrophils” in Cytokines Bioassays, Springer, London, https://doi.org/10.1007/978-1-4939-0928-5_24 

Taetzsch, T. et al. (2015), "Redox regulation of NF-κB p50 and M1 polarization in microglia", Glia, Vol. 63/3, John Wiley & Sons, Hoboken, https://doi.org/10.1002/glia.22762. 

Thurm, C. W. and J. F. Halsey (2005), “Measurement of Cytokine Production Using Whole Blood”, in Current Protocols in Immunology, John Wiley & Sons, Inc., Hoboken, https://doi.org/10.1002/0471142735.im0718bs66 

Veeraraghavan, J. et al. (2011), "Low-dose γ-radiation-induced oxidative stress response in mouse brain and gut: Regulation by NFκB–MnSOD cross-signaling", Mutation Research/Genetic Toxicology and Environmental Mutagenesis, Vol. 718/1–2, Elsevier, Amsterdam, https://doi.org/10.1016/j.mrgentox.2010.10.006. 

Veremeyko, T. et al. (2012), “Detection of microRNAs in microglia by real-time PCR in normal CNS and during neuroinflammation”, Journal of Visualized Experiments: JoVE, Vol. 65, MyJove Corporation, Cambridge, https://doi.org/10.3791/4097 

Vesce, S. et al. (2007), “Glutamate release from astrocytes in physiological conditions and in neurodegenerative disorders characterized by neuroinflammation”, International Review of Neurobiology, Vol. 82, Elsevier, Amsterdam, https://doi.org/10.1016/S0074-7742(07)82003-4 

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

Event: 2098: Increase, Neural Remodeling

Short Name: Increase, Neural Remodeling

AOPs Including This Key Event

Biological Context

Domain of Applicability

Taxonomic Applicability Life Stage Applicability Sex Applicability

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

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

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

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

Key Event Description

(Adapted from KE: 618)

Neural remodeling describes abnormal changes in structure and function of the central nervous system (CNS), which occur in the presence of a neuronal input (Chakraborti et al., 2012). However, these connections can also be altered by stressors and stimuli. The neuron is comprised of the cell body, dendrites, axon, and axon terminals (Lodish et al., 2000). Dendritic spines exist in many shapes and sizes, categorized as thin, mushroom, or stubby types (Harris & Stevens, 1989). The presence of immature dendritic spine morphologies and changes in dendritic spine density and structure, including decreases in dendritic branch points, length, and area, are correlated with changes in excitatory synaptic transmission strength (Jandial et al., 2018; Auffret et al., 2009). Dendritic protein synthesis is required for many types of long-term synaptic plasticity (Sutton & Schuman 2006). Changes to the levels of protein synthesis greatly affects neuronal communication. The CNS architecture is also affected by decreases in neurogenesis and increases in neurodegeneration, as dendritic complexity decreases. These events provoke changes in synaptic plasticity and action potential, ultimately leading to the disruption of neuronal signalling (Cekanaviciute et al., 2018). 

How it is Measured or Detected

 

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

References

Allen, A. R. et al. (2015), "56Fe Irradiation Alters Spine Density and Dendritic Complexity in the Mouse Hippocampus", Radiation Research, Vol. 184/6, BioOne, Washington, https://doi.org/10.1667/RR14103.1. 

Alvarez, M. L. and S. C. Doné. (2014), "SYBR® Green and TaqMan® Quantitative PCR Arrays: Expression Profile of Genes Relevant to a Pathway or a Disease State" (pp. 321–359), Springer Nature, Berlin, https://doi.org/10.1007/978-1-4939-1062-5_27. 

Auffret, A. et al. (2009), "Age-Dependent Impairment of Spine Morphology and Synaptic Plasticity in Hippocampal CA1 Neurons of a Presenilin 1 Transgenic Mouse Model of Alzheimer’s Disease", Journal of Neuroscience, Vol. 29/32, Society for Neuroscience, Washington, https://doi.org/10.1523/JNEUROSCI.1856-09.2009. 

Cekanaviciute, E., S. Rosi and S. V. Costes. (2018), "Central nervous system responses to simulated galactic cosmic rays", International Journal of Molecular Sciences, Vol. 19/11, Multi-Disciplinary Digital Publishing Institute, Basel, https://doi.org/10.3390/ijms19113669. 

Chakraborti, A. et al. (2012), "Cranial Irradiation Alters Dendritic Spine Density and Morphology in the Hippocampus", (P.J. Tofilon, Ed.) PLoS ONE, Vol. 7/7, Public Library of Science, San Francisco, https://doi.org/10.1371/journal.pone.0040844. 

Dore, K. et al. (2020), "SYNPLA, a method to identify synapses displaying plasticity after learning", Proceedings of the National Academy of Sciences, Vol. 117/6, Proceedings of the National Academy of Sciences, https://doi.org/10.1073/pnas.1919911117. 

Falsig, J., M. Latta and M. Leist. (2003), "Defined inflammatory states in astrocyte cultures: correlation with susceptibility towards CD95-driven apoptosis", Journal of Neurochemistry, Vol. 88/1, John Wiley & Sons, Inc., Hoboken, https://doi.org/10.1111/j.1471-4159.2004.02144.x. 

Fike, J. R. et al. (1984), "Computed Tomography Analysis of the Canine Brain: Effects of Hemibrain X Irradiation", Radiation Research, Vol. 99/2, Allen Press, Lawrence, https://doi.org/10.2307/3576373. 

Fike, J. R. et al. (1988), "Radiation dose response of normal brain", International Journal of Radiation Oncology, Biology, Physics, Vol. 14/1, Elsevier, Amsterdam, https://doi.org/10.1016/0360-3016(88)90052-1. 

Harris, K. and J. Stevens. (1989), "Dendritic spines of CA 1 pyramidal cells in the rat hippocampus: serial electron microscopy with reference to their biophysical characteristics", The Journal of Neuroscience, Vol. 9/8, Society for Neuroscience, Washington, https://doi.org/10.1523/JNEUROSCI.09-08-02982.1989. 

Hill, C. L. and G. J. Stephens. (2021), "An Introduction to Patch Clamp Recording" (pp. 1–19), https://doi.org/10.1007/978-1-0716-0818-0_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. b., Amsterdam, https://doi.org/10.1016/j.mrrev.2016.08.003. 

Kiffer, F. et al. (2020), "Late Effects of 1H + 16O on Short-Term and Object Memory, Hippocampal Dendritic Morphology and Mutagenesis", Frontiers in Behavioral Neuroscience, Vol. 14, Frontiers Media S.A., https://doi.org/10.3389/fnbeh.2020.00096. 

Kressel, M. and P. Groscurth (1994), "Distinction of apoptotic and necrotic cell death by in situ labelling of fragmented DNA", Cell and tissue research, Vol. 278/3, Nature, https://doi.org/10.1007/BF00331373.  

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Event: 1635: Increase, DNA strand breaks

Short Name: Increase, DNA strand breaks

AOPs Including This Key Event

Stressors

Biological Context

Domain of Applicability

Taxonomic Applicability Life Stage Applicability Sex Applicability

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

Life stage applicability: This key event is not life stage specific as all life stages display strand breaks. However, there is an increase in baseline levels of DNA strand breaks seen in older individuals though it is unknown whether this change due to increased break induction or a greater retention of breaks due to poor repair (White & Vijg, 2016). 

Sex applicability: This key event is not sex specific as both sexes display evidence of strand breaks. In some cell types, such as peripheral blood mononuclear cells, males show higher levels of single strand breaks than females (Garm et al., 2012). 

Evidence for perturbation by a stressor: There are studies demonstrating that increased DNA strand breaks can result from exposure to multiple stressor types including ionizing & non-ionizing radiation, chemical agents, and oxidizing agents (EPRI, 2014; Hamada, 2014; Cencer et al., 2018; Cannan & Pederson, 2016; Yang et al., 1998).  

Key Event Description

DNA strand breaks can occur on a single strand (SSB) or both strands (double strand breaks; DSB). SSBs arise when the phosphate backbone connecting adjacent nucleotides in DNA is broken on one strand. DSBs are generated when both strands are simultaneously broken at sites that are sufficiently close to one another that base-pairing and chromatin structure are insufficient to keep the two DNA ends juxtaposed. As a consequence, the two DNA ends generated by a DSB can physically dissociate from one another, becoming difficult to repair and increasing the chance of inappropriate recombination with other sites in the genome (Jackson, 2002). SSB can turn into DSB if the replication fork stalls at the lesion leading to fork collapse.

Strand breaks are intermediates in various biological events, including DNA repair (e.g., excision repair), V(D)J recombination in developing lymphoid cells and chromatin remodeling in both somatic cells and germ cells. The spectrum of damage  can be complex, particularily if the stressor is from large amounts of deposited energy which can result in complex lesions and clustered damage defined as two or more oxidized bases, abasic sites or starnd breaks on opposing DNA strands within a few helical turns. These lesions are more difficult to repair and have been studied in many types of models  (Barbieri et al., 2019 and Asaithamby et al., 2011). DSBs and complex lesions  are of particular concern, as they are considered the most lethal and deleterious type of DNA lesion. If misrepaired or left unrepaired, DSBs may drive the cell towards genomic instability, apoptosis or tumorigenesis (Beir, 1999).

 

How it is Measured or Detected

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

 

Assay Name	References	Description	OECD Approved Assay
Comet Assay (Single Cell Gel Eletrophoresis - Alkaline)	Collins, 2004; Olive and Banath, 2006; Platel et al., 2011; Nikolova et al., 2017	To detect SSBs or DSBs, single cells are encapsulated in agarose on a slide, lysed, and subjected to gel electrophoresis at an alkaline pH (pH >13); DNA fragments are forced to move, forming a "comet"-like appearance	Yes (No. 489)
Comet Assay (Single Cell Gel Eltrophoresis - Neutral)	Collins, 2014; Olive and Banath, 2006; Anderson and Laubenthal, 2013; Nikolova et al., 2017	To detect DSBs, single cells are encapsulated in agarose on a slide, lysed, and subjected to gel electrophoresis at a neutral pH; DNA fragments, which are not denatured at the neutral pH, are forced to move, forming a "comet"-like appearance	N/A
γ-H2AX Foci Quantification - Flow Cytometry	Rothkamm and Horn, 2009; Bryce et al., 2016	Measurement of γ-H2AX immunostaining in cells by flow cytometry, normalized to total levels of H2AX	N/A
γ-H2AX Foci Quantification - Western Blot	Burma et al., 2001; Revet et al., 2011	Measurement of γ-H2AX immunostaining in cells by Western blotting, normalized to total levels of H2AX	N/A
γ-H2AX Foci Quantification - Microscopy	Redon et al., 2010; Mah et al., 2010; Garcia-Canton et al., 2013	Quantification of γ-H2AX immunostaining by counting γ- H2AX foci visualized with a microscope	N/A
γ-H2AX Foci Detection - ELISA and flow cytometry	Ji et al., 2017; Bryce et al., 2016	Detection of γ-H2AX in cells by ELISA, normalized to total levels of H2AX; γH2AX foci detection can be high-throughput and automated using flow cytometry-based immunodetection.	N/A
Pulsed Field Gel Electrophoresis (PFGE)	Ager et al., 1990; Gardiner et al., 1985; Herschleb et al., 2007; Kawashima et al., 2017	To detect DSBs, cells are embedded and lysed in agarose, and the released DNA undergoes gel electrophoresis in which the direction of the voltage is periodically alternated; Large DNA fragments are thus able to be separated by size	N/A
The TUNEL (Terminal Deoxynucleotidyl Transferase dUTP Nick End Labeling) Assay	Loo, 2011	To detect strand breaks, dUTPs added to the 3’OH end of a strand break by the DNA polymerase terminal deoxynucleotidyl transferase (TdT) are tagged with a fluorescent dye or a reporter enzyme to allow visualization (We note that this method is typically used to measure apoptosis)	N/A
In Vitro DNA Cleavage Assays using Topoisomerase	Nitiss, 2012	Cleavage of DNA can be achieved using purified topoisomerase; DNA strand breaks can then be separated and quantified using gel electrophoresis	N/A
PCR assay	Figueroa‑González & Pérez‑Plasencia, 2017	Assay of strand breaks through the observation of DNA amplification prevention. Breaks block Taq polymerase, reducing the number of DNA templates, preventing amplification	N/A
Sucrose density gradient centrifuge	Raschke et al. 2009	Division of DNA pieces by density, increased fractionation leads to lower density pieces, with the use of a sucrose cushion	N/A
Alkaline Elution Assay	Kohn, 1991	Cells lysed with detergent-solution, filtered through membrane to remove all but intact DNA	N/A
Unwinding Assay	Nacci et al. 1992	DNA is stored in alkaline solutions with DNA-specific dye and allowed to unwind following removal from tissue, increased strand damage associated with increased unwinding	N/A

References

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Anderson, D. & Laubenthal J. (2013), “Analysis of DNA Damage via Single-Cell Electrophoresis. In: Makovets S, editor. DNA Electrophoresis. Totowa.”, NJ: Humana Press. p 209-218.

Asaithamby, A., B. Hu and D.J. Chen. (2011) Unrepaired clustered DNA lesions induce chromosome breakage in human cells. Proc Natl Acad Sci U S A 108(20): 8293-8298 .

Barbieri, S., G. Babini, J. Morini et a l (2019). . Predicting DNA damage foci and their experimental readout with 2D microscopy: a unified approach applied to photon and neutron exposures. Scientific Reports 9(1): 14019

Bryce, S. et al. (2016), “Genotoxic mode of action predictions from a multiplexed flow cytometric assay and a machine learning approach.”, Environ Mol Mutagen. 57:171-189. Doi: 10.1002/em.21996.

Burma, S. et al. (2001), “ATM phosphorylates histone H2AX in response to DNA double-strand breaks.”, J Biol Chem, 276(45): 42462-42467. doi:10.1074/jbc.C100466200

Cannan, W.J. and D.S. Pederson (2016), "Mechanisms and Consequences of Double-Strand DNA Break Formation in Chromatin.", Journal of Cellular Physiology, Vol.231/1, Wiley, New York, https://doi.org/10.1002/jcp.25048.  

Cencer, C. et al. (2018), “PARP-1/PAR Activity in Cultured Human Lens Epithelial Cells Exposed to Two Levels of UVB Light”, Photochemistry and Photobiology, Vol.94/1, Wiley-Blackwell, Hoboken, https://doi.org/10.1111/php.12814.  

Charlton, E. D. et al. (1989), “Calculation of Initial Yields of Single and Double Stranded Breaks in Cell Nuclei from Electrons, Protons, and Alpha Particles.”,  Int. J. Radiat. Biol. 56(1): 1-19. doi: 10.1080/09553008914551141.

Collins, R. A. (2004), “The Comet Assay for DNA Damage and Repair. Molecular Biotechnology.”, Mol Biotechnol. 26(3): 249-61. doi:10.1385/MB:26:3:249

EPRI (2014), Epidemiology and mechanistic effects of radiation on the lens of the eye: Review and scientific appraisal of the literature, EPRI, California. 

Figueroa‑González, G. and C. Pérez‑Plasencia. (2017), “Strategies for the evaluation of DNA damage and repair mechanisms in cancer”, Oncology Letters, Vol.13/6, Spandidos Publications, Athens, https://doi.org/10.3892/ol.2017.6002. 

Garcia-Canton, C. et al. (2013), “Assessment of the in vitro p-H2AX assay by High Content Screening asa novel genotoxicity test.”, Mutat Res. 757:158-166.  Doi:  10.1016/j.mrgentox.2013.08.002

Gardiner, K. et al. (1986), “Fractionation of Large Mammalian DNA Restriction Fragments Using Vertical Pulsed-Field Gradient Gel Electrophoresis.”,  Somatic Cell and Molecular Genetics. 12(2): 185-95.Doi: 10.1007/bf01560665.

Garm, C. et al. (2012), “Age and gender effects on DNA strand break repair in peripheral blood mononuclear cells”, Aging Cell, Vol.12/1, Blackwell Publishing Ltd, Oxford, https://doi.org/10.1111/acel.12019. 

Hamada, N. (2014), “What are the intracellular targets and intratissue target cells for radiation effects?”, Radiation research, Vol. 181/1, The Radiation Research Society, Indianapolis, https://doi.org/10.1667/RR13505.1. 

Herschleb, J. et al. (2007), “Pulsed-field gel electrophoresis.”,  Nat Protoc. 2(3): 677-684. doi:10.1038/nprot.2007.94

Iliakis, G. et al. (2015), “Alternative End-Joining Repair Pathways Are the Ultimate Backup for Abrogated Classical Non-Homologous End-Joining and Homologous Recombination Repair: Implications for the Formation of Chromosome Translocations.”,  Mutation Research/Genetic Toxicology and Environmental Mutagenesis. 2(3): 677-84. doi: 10.1038/nprot.2007.94

Jackson, S. (2002). “Sensing and repairing DNA double-strand breaks.”,  Carcinogenesis. 23:687-696. Doi:10.1093/carcin/23.5.687.

Ji, J. et al. (2017), “Phosphorylated fraction of H2AX as a measurement for DNA damage in cancer cells and potential applications of a novel assay.”,  PLoS One. 12(2): e0171582. doi:10.1371/journal.pone.0171582

Kawashima, Y.(2017), “Detection of DNA double-strand breaks by pulsed-field gel electrophoresis.”,  Genes Cells 22:84-93. Doi: 10.1111/gtc.12457.

Khoury, L. et al. (2013), “Validation of high-throughput genotoxicity assay screening using cH2AX in-cell Western assay on HepG2 cells.”, Environ Mol Mutagen, 54:737-746. Doi:  10.1002/em.21817.

Khoury, L. et al. (2016), “Evaluation of four human cell lines with distinct biotransformation properties for genotoxic screening.”, Mutagenesis, 31:83-96. Doi: 10.1093/mutage/gev058.

Kohn, K.W. (1991), “Principles and practice of DNA filter elution”, Pharmacology & Therapeutics, Vol.49/1, Elsevier, Amsterdam, https://doi.org/10.1016/0163-7258(91)90022-E. 

Loo, DT. (2011), “In Situ Detection of Apoptosis by the TUNEL Assay: An Overview of Techniques. In: Didenko V, editor. DNA Damage Detection In Situ, Ex Vivo, and In Vivo. Totowa.”, NJ: Humana Press. p 3-13.doi: 10.1007/978-1-60327-409-8_1.

Mah, L. J. et al. (2010), “Quantification of gammaH2AX foci in response to ionising radiation.”,  J Vis Exp(38). doi:10.3791/1957.

Nacci, D. et al. (1992), “Application of the DNA alkaline unwinding assay to detect DNA strand breaks in marine bivalves”, Marine Environmental Research, Vol.33/2, Elsevier BV, Amsterdam, https://doi.org/10.1016/0141-1136(92)90134-8. 

Nikolova, T., F. et al. (2017), “Genotoxicity testing: Comparison of the γH2AX focus assay with the alkaline and neutral comet assays.”,  Mutat Res 822:10-18. Doi: 10.1016/j.mrgentox.2017.07.004.

Nitiss, J. L. et al. (2012), “Topoisomerase assays. ”, Curr Protoc Pharmacol. Chapter 3: Unit 3 3.

OECD. (2014). Test No. 489: “In vivo mammalian alkaline comet assay.”  OECD Guideline for the Testing of Chemicals, Section 4 .

Olive, P. L., & Banáth, J. P. (2006), “The comet assay: a method to measure DNA damage in individual cells.”,  Nature Protocols. 1(1): 23-29. doi:10.1038/nprot.2006.5.

Platel A. et al. (2011), “Study of oxidative DNA damage in TK6 human lymphoblastoid cells by use of the thymidine kinase gene-mutation assay and the in vitro modified comet assay: Determination of No-Observed-Genotoxic-Effect-Levels.”,  Mutat Res 726:151-159. Doi: 10.1016/j.mrgentox.2011.09.003.

Raschke, S., J. Guan and G. Iliakis. (2009), “Application of alkaline sucrose gradient centrifugation in the analysis of DNA replication after DNA damage”, Methods in Molecular Biology, Vol.521, Humana Press, Totowa, https://doi.org/10.1007/978-1-60327-815-7_18. 

Redon, C. et al. (2010), “The use of gamma-H2AX as a biodosimeter for total-body radiation exposure in non-human primates.”,  PLoS One. 5(11): e15544. doi:10.1371/journal.pone.0015544

Revet, I. et al. (2011), “Functional relevance of the histone γH2Ax in the response to DNA damaging agents.” Proc Natl Acad Sci USA.108:8663-8667. Doi: 10.1073/pnas.1105866108

Rogakou, E.P. et al. (1998), “DNA Double-stranded Breaks Induce Histone H2AX Phosphorylation on Serine 139.” , J Biol Chem, 273:5858-5868. Doi: 10.1074/jbc.273.10.5858

Rothkamm, K. & Horn, S. (2009), “γ-H2AX as protein biomarker for radiation exposure.”,  Ann Ist Super Sanità, 45(3): 265-71.

White, R.R. and J. Vijg. (2016), “Do DNA Double-Strand Breaks Drive Aging?”, Molecular Cell, Vol.63, Elsevier, Amsterdam, http://doi.org/10.1016/j.molcel.2016.08.004. 

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List of Adverse Outcomes in this AOP

Event: 341: Impairment, Learning and memory

Short Name: Impairment, Learning and memory

Key Event Component

AOPs Including This Key Event

Biological Context

Domain of Applicability

Taxonomic Applicability Life Stage Applicability Sex Applicability

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

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

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

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

Key Event Description

 

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

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

Learning and memory depend upon the coordinated action of different brain regions and neurotransmitter systems constituting functionally integrated neural networks (D’Hooge and DeDeyn, 2001). Among the many brain areas engaged in the acquisition of, or retrieval of, a learned event, the hippocampal-based memory systems have received the most study. For example, the hippocampus has been shown to be critical for spatial-temporal memory, visio-spatial memory, verbal and narrative memory, and episodic and autobiographical memory (Burgess et al., 2000; Vorhees and Williams, 2014). However, there is substantial evidence that fundamental learning and memory functions are not mediated by the hippocampus alone but require a network that includes, in addition to the hippocampus, anterior thalamic nuclei, mammillary bodies cortex, cerebellum and basal ganglia (Aggleton and Brown, 1999; Doya, 2000; Mitchell et al., 2002, Toscano and Guilarte, 2005; Gilbert et al., 2006, 2016). Thus, damage to variety of brain structures can potentially lead to impairment of learning and memory. The main learning areas and pathways are similar in rodents and primates, including man (Eichenbaum, 2000; Stanton and Spear, 1990).While the prefrontal cortex and frontostriatal neuronal circuits have been identified as the primary sites of higher-order cognition in vertebrates, invertebrates utilize paired mushroom bodies, shown to contain ~300,000 neurons in honey bees (Menzel, 2012; Puig et al., 2014).

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

How it is Measured or Detected

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

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

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

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

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

5) Operant Responding. Performance on operant responding reflects the cortex’ ability to organize processes (Rabin et al., 2002). 

In humans:  A variety of standardized learning and memory tests have been developed for human neuropsychological testing, including children (Rohlman et al., 2008). These include episodic autobiographical memory, perceptual motor tests, short and  long term memory tests, working memory tasks, word pair recognition memory; object location recognition memory. Some have been incorporated in general tests of intelligence (IQ) such as the Wechsler Adult Intelligence Scale (WAIS) and the Wechsler. Modifications have been made and norms developed for incorporating of tests of learning and memory in children. Examples of some of these tests include:

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

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

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

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

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

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

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

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

Regulatory Significance of the AO

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

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

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Appendix 2

List of Key Event Relationships in the AOP