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Relationship: 916

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

Infiltration, Inflammatory cells leads to Inflammation, Liver

Upstream event
The causing Key Event (KE) in a Key Event Relationship (KER). More help
Downstream event
The responding Key Event (KE) in a Key Event Relationship (KER). More help

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

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
mouse Mus musculus High NCBI
human Homo sapiens High NCBI

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

Immune cells such as polymorphonuclear neutrophils (PMNs) or monocytes, circulate in the blood and become attracted towards a gradient of secreted pro-inflammatory cytokines. PMNs have a life span of only 7-12 hours. Therefore, around 1-2 x 1011 PMN are produced daily in the human body. They account for about 50-70 % of all blood leukocytes in the human body [1][2]. Upon an inflammatory event, neutrophil production is upregulated, and its lifetime increases as a response to platelet activating factor (PAF), granulocyte-colony stimulating factor (G-CSF) or various pro-inflammatory cytokines, such as interleukin 1ß (IL-1ß) [2]. In sterile tissue injury, for example as the result of apoptosis, there is no need for PMNs to function as antimicrobial effectors; instead, they clear debris and initiate the wound-healing process. Released damage-associated molecular patterns (see Relationship:924) stimulate Kupffer cells to produce IL-1ß which leads to intercellular adhesion molecular-1 (ICAM-1) upregulation on sinusoidal endothelial cells [3]. ICAM-1 in turn mediates neutrophil adhesion to endothelial cells, as it interacts with ß2 integrin, which is expressed on the surface of PMNs. Subsequent to adhesion, neutrophils begin to migrate across the endothelium and towards the affected tissue [4][5]. The transition of neutrophils from a resting state, as during circulation in the blood, to an activated state at the site of infection is triggered by an ordered sequence of signals from cytokines[3].

The aberrant activation of neutrophils and their extended lifespan upon an inflammatory stimulus can increase the probability of extracellular damage. PMNs are potent phagocytes, but they also lead to pathogen destruction upon oxidative bursting. The oxidative burst is marked by an increased consumption of molecular oxygen, resulting in the production of reactive oxygen species (ROS) such as H2O2 and OH•, and reactive nitrogen species (RNS)[6]. In general, the acute inflammatory response, as in the liver, is bi-phasic. The initial phase is characterised by a macrophage (Kupffer cell)-mediated phase, with the generation of reactive oxygen species aggravating the organ damage. The activated macrophages and subsequent infiltrating lymphocytes produce additional cytokines that further promote the inflammatory response, leading to a second phase, during which neutrophils become fully activated and secrete ROS, complement components, proteases, CXCL-1 and CXCL-2[3]. The role of IL-1 and IL-17A in neutrophil activation and subsequent induction of inflammation has been confirmed by the use of knock-down models, showing that the absence of these mediators prevent neutrophil infiltration and subsequent onset of inflammation, inhibition of the latter also being shown by direct depletion of neutrophils[7].

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

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

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

[8][7]: mouse [9]: human