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Relationship: 2833

Title

A descriptive phrase which clearly defines the two KEs being considered and the sequential relationship between them (i.e., which is upstream, and which is downstream). More help

Oxidative Stress leads to Tissue resident cell activation

Upstream event

The causing Key Event (KE) in a Key Event Relationship (KER). More help

Oxidative Stress

Downstream event

The responding Key Event (KE) in a Key Event Relationship (KER). More help

Tissue resident cell activation

Key Event Relationship Overview

The utility of AOPs for regulatory application is defined, to a large extent, by the confidence and precision with which they facilitate extrapolation of data measured at low levels of biological organisation to predicted outcomes at higher levels of organisation and the extent to which they can link biological effect measurements to their specific causes.Within the AOP framework, the predictive relationships that facilitate extrapolation are represented by the KERs. Consequently, the overall WoE for an AOP is a reflection in part, of the level of confidence in the underlying series of KERs it encompasses. Therefore, describing the KERs in an AOP involves assembling and organising the types of information and evidence that defines the scientific basis for inferring the probable change in, or state of, a downstream KE from the known or measured state of an upstream KE. More help

AOPs Referencing Relationship

AOP Name	Adjacency	Weight of Evidence	Quantitative Understanding	Point of Contact	Author Status	OECD Status
Deposition of Energy Leading to Learning and Memory Impairment	adjacent	Moderate	Low	Brendan Ferreri-Hanberry (send email)	Open for citation & comment

Taxonomic Applicability

Latin or common names of a species or broader taxonomic grouping (e.g., class, order, family) that help to define the biological applicability domain of the KER.In general, this will be dictated by the more restrictive of the two KEs being linked together by the KER. More help

Term	Scientific Term	Evidence	Link
human	Homo sapiens	Low	NCBI
mouse	Mus musculus	Low	NCBI
rat	Rattus norvegicus	Moderate	NCBI

Sex Applicability

An indication of the the relevant sex for this KER. More help

Sex	Evidence
Male	Moderate
Female	Not Specified
Unspecific	Low

Life Stage Applicability

An indication of the the relevant life stage(s) for this KER. More help

Term	Evidence
Adult	Moderate
Not Otherwise Specified	Low

Key Event Relationship Description

Provides a concise overview of the information given below as well as addressing details that aren’t inherent in the description of the KEs themselves. More help

Oxidative stress encompasses an increase in the production of free radicals (e.g., superoxide, hydrogen peroxide and hydroxyl radicals) and a loss of antioxidant mechanisms (e.g., superoxide dismutase (SOD), glutathione peroxidase (GSH-Px) and catalase (CAT)). This imbalance can lead to damaging by-products that can activate tissue resident cells. Reactive oxygen and nitrogen species (RONS) are examples of free radicals that may promote oxidative injury (Simpson & Oliver, 2020). In addition, excess free radicals can promote a reduced capacity of the cells to maintain redox balance and prevent ongoing oxidative damage (Huang, Zou & Corniola, 2012; Rojo et al., 2014). Depending on the organ/tissue, different resident cell types may become activated by oxidative stress. For example, in the brain, oxidative stress will specifically activate microglial cells and astrocytes (Lee, Cha & Lee, 2021). Microglia cells are macrophages in the brain that respond to tissue injury, provide surveillance to neurons, and maintain synaptic homeostasis (Zhu et al., 2022). Astrocytes are critical regulators of neurogenesis and synaptogenesis, blood brain barrier permeability, and responsible for maintenance of cellular homeostasis (Zhu et al., 2022). Both microglial cells and astrocytes can change from resting to reactive states, termed gliosis, in response to excess RONS (Lee, Cha & Lee, 2021). In response to RONS, Toll like receptors (TLRs) located on microglia become activated to mediate the immune response (Gill et al., 2010; Mehdipour et al., 2021). These receptors then initiate a cascade of signaling pathways that contribute to the production of pro-inflammatory cytokines and free radicals, resulting in neuroinflammation (Heidari et al., 2022).

Reactive microglia cells increase in size and number, display a reduction in the length and density of their processes, and upregulate their macrophagic processes, marked by expression of proteins related to phagocytic activity such as cluster of differentiation 68 (CD68) (Hol & Pekny, 2015). Astrocytes undergoing astrogliosis exhibit cellular hypertrophy and an upregulation of glial fibrillary acidic protein (GFAP), an intermediate filament expressed exclusively in astrocytes that plays a critical role in astroglia cell activation (Hol & Pekny, 2015). Activation of both microglial cells and astrocytes can accelerate neuroinflammatory pathways that can ultimately promote further formation of ROS creating a feedforward loop (Lee, Cha & Lee, 2021; Simpson & Oliver, 2020; Zhu et al., 2022).

Evidence Collection Strategy

Include a description of the approach for identification and assembly of the evidence base for the KER. For evidence identification, include, for example, a description of the sources and dates of information consulted including expert knowledge, databases searched and associated search terms/strings. Include also a description of study screening criteria and methodology, study quality assessment considerations, the data extraction strategy and links to any repositories/databases of relevant references.Tabular summaries and links to relevant supporting documentation are encouraged, wherever possible. More help

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

Evidence Map 2.0

ID	Experimental Design	Species	Upstream Observation	Downstream Observation	Citation (first author, year)	Notes

Evidence Map

Addresses the scientific evidence supporting KERs in an AOP setting the stage for overall assessment of the AOP. More help

Title	First Author	Biological Plausibility	Dose Concordance	Temporal Concordance	Incidence Concordance

Biological Plausibility

Dose Concordance Evidence

Temporal Concordance Evidence

Incidence Concordance Evidence

Uncertainties and Inconsistencies

Addresses inconsistencies or uncertainties in the relationship including the identification of experimental details that may explain apparent deviations from the expected patterns of concordance. More help

Although ROS can activate NF-KB (Gloire, Legrand-Poels et al. 2006), not all studies consistently show NF-kB activation after RONs stressor IR. It is possible that the link between ROS and NF-kB depends on the local environmental context, with different studies not adequately controlling all influential variables. One study offers a possible explanation based on temporal response: in macrophages, NF-kB was activated by shorter exposures to H2O2 (30 min), but the response disappeared with longer exposures (Nakao, Kurokawa et al. 2008).

While many models in vivo and in vitro showed a decreased inflammatory response to RONS stressors IR in combination with antioxidants, in endothelial cells in culture the increase in IL6 and IL8 after IR was not reduced by antioxidants, although a synergistic increase in those cytokines occurring with combined TNF-a and IR treatment was reduced by antioxidants (Meeren, Bertho et al. 1997). This is a reminder that multiple mechanisms can increase inflammation, that inflammatory factors participate in positive feedback loops, and that responses to stimuli vary between cells.

Many studies do not report direct measures of RONS. As RONS 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.

Known modulating factors

This table captures specific information on the MF, its properties, how it affects the KER and respective references.1.) What is the modulating factor? Name the factor for which solid evidence exists that it influences this KER. Examples: age, sex, genotype, diet 2.) Details of this modulating factor. Specify which features of this MF are relevant for this KER. Examples: a specific age range or a specific biological age (defined by...); a specific gene mutation or variant, a specific nutrient (deficit or surplus); a sex-specific homone; a certain threshold value (e.g. serum levels of a chemical above...) 3.) Description of how this modulating factor affects this KER. Describe the provable modification of the KER (also quantitatively, if known). Examples: increase or decrease of the magnitude of effect (by a factor of...); change of the time-course of the effect (onset delay by...); alteration of the probability of the effect; increase or decrease of the sensitivity of the downstream effect (by a factor of...) 4.) Provision of supporting scientific evidence for an effect of this MF on this KER. Give a list of references. More help

Modulating factor	Details	Effects on the KER	References
Drug	KuA (antioxidant)	After 30 Gy X-ray whole-brain irradiation of rats, activated microglia increased to over 320% of control. KuA at 5 mg/kg decreased this to 240%, at 10 mg/kg decreased it to 180% and at 20 mg/kg decreased it to 170%.	Zhang et al., 2017
Drug	L-16504 (PPARδ agonist, involved in anti-inflammatory responses)	Treatment prevented the increase in ROS and reduced NF-κB and AP-1 DNA binding.	Schnegg et al., 2012
Drug	Curcumin (antioxidant)	Treatment increased SOD and GSH-Px levels and decreased the number of GFAP-positive cells.	Wang et al., 2017; Daverey & Agrawal, 2016
Age	Increased age	Increased age can cause susceptibility to ROS accumulation and tissue-resident cell activation.	Liguori et al., 2018; Hanslik, Marino & Ulland, 2021
Diet	High antioxidant diet	Increased antioxidants in diet can lead to reduced oxidative stress.	Ávila-Escalante et al., 2020
Diet	Hypocaloric diet	Caloric restriction has been shown to lead to reduced markers of oxidative stress.	Ávila-Escalante et al., 2020
Smoking	Active smokers	Active smokers show reduced GSH-Px activity compared to non-smokers (measured in patients with coronary artery disease).	Kamceva et al., 2016
Prior Disease	Neurodegenerative diseases like Alzheimer’s and Parkinson’s	These diseases can generate an environment of increased oxidative stress and promotes the activation of glial cells.	Hanslik, Marino & Ulland, 2021
Genotype	SOD knockout mice	SOD2 knockout mice experienced increased microglia activation following irradiation, indicating an impact of genotype on tissue resident cell activation.	Fishman et al., 2009

Quantitative Understanding of the Linkage

Captures information that helps to define how much change in the upstream KE, and/or for how long, is needed to elicit a detectable and defined change in the downstream KE. More help

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

Dose Concordance

Reference	Experiment description	Result
Wang, 2017	In vivo. Adult male Sprague-Dawley rats were treated with 4 µg/µL of the neurotoxin 6-hydroxydopamine. Oxidative stress was measured by SOD and GSH-Px levels through a bicinchoninic acid protein assay kit. GFAP was used as a marker of astrocytes and was detected using immunohistochemistry.	SOD decreased 0.64-fold and GSH-Px decreased 0.34-fold. GFAP increased 1.7-fold.
Daverey & Agrawal, 2016	In vitro. Human A172 (glioblastoma astrocytes) and HA-sp (spinal cord astrocytes) cell lines were treated with H2O2. GFAP expression was detected through immunofluorescence.	After 50 µM of H2O2, both cell types showed increased GFAP expression about 1.5-fold. GFAP was also increased 1.5- to 2-fold after 100 and 200 µM of H2O2.

Time Concordance

Reference	Experiment description	Result
Schnegg et al., 2012	In vitro. BV-2 immortalized microglia were irradiated with 10 Gy of 137Cs gamma raysat 3.56 Gy/min. Measured 1h after irradiation, intracellular ROS generation was measured by the fluorescent DCFH-DA probe, and activation of NF-κB and AP-1 was determined by immunoblotting as a measure of cell activation.	Both measured 1h after irradiation, ROS increased about 7-fold while NF-κB and AP-1 DNA binding was increased 2.5- and 2-fold, respectively.
Daverey & Agrawal, 2016	In vitro. Human A172 (glioblastoma astrocytes) and HA-sp (spinal cord astrocytes) cell lines were treated with 50 µM of the ROS H2O2. GFAP expression was detected through immunofluorescence after various durations of H2O2 treatment.	Both cell types showed increased GFAP about 1.5-fold, measured after treatment with H2O2. H2O2 administered for 2, 6 and 12h showed slight increases at each timepoint, while after 24h of H2O2 treatment, GFAP was only increased in A172 cells.

Incidence Concordance

Reference	Experimental description	Result
Schnegg et al., 2012	In vitro. BV-2 immortalized microglia were irradiated with 10 Gy of 137Cs gamma rays at 3.56 Gy/min. Intracellular ROS generation was measured by the fluorescent DCFH-DA probe, and activation of NF-κB and AP-1 was determined by immunoblotting as a measure of cell activation.	ROS increased about 7-fold while NF-κB and AP-1 DNA binding was increased 2.5- and 2-fold, respectively.

Response-response Relationship

Provides sources of data that define the response-response relationships between the KEs. More help

Time-scale

Information regarding the approximate time-scale of the changes in KEdownstream relative to changes in KEupstream (i.e., do effects on KEdownstream lag those on KEupstream by seconds, minutes, hours, or days?). More help

Known Feedforward/Feedback loops influencing this KER

Define whether there are known positive or negative feedback mechanisms involved and what is understood about their time-course and homeostatic limits. More help

Since inflammatory signaling and activated immune cells can also increase the production of RONS, positive feedback and feedforward loops can occur (Zhao and Robbins 2009; Ratikan, Micewicz et al. 2015; Blaser, Dostert et al. 2016). Similarly, positive feedforward and feedback loops regarding RONS, cellular activation, and inflammation also occur in the CNS. Both RONS and microglial cell activation can accelerate neuroinflammatory pathways that can ultimately promote further formation of RONS (Lee, Cha & Lee, 2021; Simpson & Oliver, 2020; Zhu et al., 2022).

Domain of Applicability

A free-text section of the KER description that the developers can use to explain their rationale for the taxonomic, life stage, or sex applicability structured terms. More help

Evidence for this relationship comes from in vitro human- and mouse-derived models, as well as in vivo rat models. Most of the evidence are in male adult and male models, although sex and age are not always specified.