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Relationship: 1230

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

Increase, Phenotypic enzyme activity leads to Increase, cell proliferation (hepatocytes)

Upstream event

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

Increase, Phenotypic enzyme activity

Downstream event

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

Increase, cell proliferation (hepatocytes)

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
PPARα activation leading to hepatocellular adenomas and carcinomas in rodents	adjacent	High	Moderate	Cataia Ives (send email)	Under development: Not open for comment. Do not cite	Under Development

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

Sex Applicability

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

Life Stage Applicability

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

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

Growth factors and other cytokines secreted from Kupffer cells following PPARα activation include tumor necrosis factor α (TNFα), interleukin-1α (IL-1α), and interleukin-1β (IL-1β). Although TNFα levels increase following PPARα activation, proliferation was observed in wild type, TNFα-null, and TNFα receptor-null mice, suggesting that multiple cytokines stimulate cell proliferation (Maeda et al. 2005). PPARα activation reduces the level of miRNA let-7c in liver. In turn, let-7c normally down-regulates c-Myc expression and thus, PPARα activation increases c-Myc expression that increase cell proliferation (Shah et al. 2007). PPARα activation increases levels of other cell cycle proteins including Cdk-1, Cdk-4, Cyclin D1 and Pcna (Currie et al. 2005; Woods et al. 2007).

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

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

The precise mechanism for activation of growth control genes is not known.

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

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

Cell proliferation measured by BrdU labeling index was plotted against the enzyme response of the three PPARα activators. The enzyme measured was acyl CoA oxidase, a lipid-metabolizing enzyme and was considered a surrogate for the cytokines and other growth-related cytokines stimulated by PPARα activation. These data were well fit by a Michaelis-Menten equation, suggesting that receptor mechanisms are likely involved in the growth response.

The

The maximal proliferation level was 30.88% and the half-maximal enzyme response was 3.37.

Response-response Relationship

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

Levels of cytokines and other cellular proteins involved in cell cycle control are increased concomitant with increased enzyme activity and stimulate cell proliferation.

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

Both responses considered above occured 1 week after commencing PPARα activation.

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

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

The domain of applicability is the same as for AOP 37.