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Relationship: 67

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

Cell injury/death leads to Increased, Activation and Recruitment of Hepatic macrophages (Kupffer Cells)

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
human Homo sapiens High NCBI
Rattus norvegicus Rattus norvegicus 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

Damaged hepatocytes release reactive oxygen species (ROS), cytokines such as TGF-β1 and TNF-α, and chemokines which lead to oxidative stress, inflammatory signalling and finally activation of Kupffer cells (KCs). ROS generation in hepatocytes results from oxidative metabolism by NADH oxidase (NOX) and cytochrome 2E1 activation as well as through lipid peroxidation. Damaged liver cells trigger a sterile inflammatory response with activation of innate immune cells through release of damage-associated molecular patterns (DAMPs), which activate KCs through toll-like receptors and recruit activated neutrophils and monocytes into the liver. Central to this inflammatory response is the promotion of ROS formation by these phagocytes. Upon initiation of apoptosis hepatocytes undergo genomic DNA fragmentation and formation of apoptotic bodies; these apoptotic bodies are consecutively engulfed by KCs and cause their activation. This increased phagocytic activity strongly up-regulates NOX expression in KCs, a superoxide producing enzyme of phagocytes with profibrogenic activity, as well as nitric oxide synthase (iNOS) mRNA transcriptional levels with consequent harmful reaction between ROS and nitricoxide (NO), like the generation of cytotoxic peroxinitrite (N2O3). ROS and/or diffusible aldehydes also derive from liver sinusoidal endothelial cells (LSECs) which are additional initial triggers of KC activation. [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11]

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 Supporting this KER

Addresses the scientific evidence supporting KERs in an AOP setting the stage for overall assessment of the AOP. More help
Biological Plausibility
Addresses the biological rationale for a connection between KEupstream and KEdownstream.  This field can also incorporate additional mechanistic details that help inform the relationship between KEs, this is useful when it is not practical/pragmatic to represent these details as separate KEs due to the difficulty or relative infrequency with which it is likely to be measured.   More help

There is a functional relationship between cell injury/death and KC activation, consistent with established biological knowledge.

[1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11]

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 detailed mechanisms of the KC - hepatocyte interaction and its consequences for both normal and toxicant-driven liver responses remain to be determined. KC activation followed by cytokine release is associated in some cases with evident liver damage, whereas in others this event is unrelated to liver damage or may be even protective; apparently this impact is dependent on the quantity of KC activation; excessive or prolonged release of KC mediators can switch an initially protective mechanism to a damaging inflammatory response. Evidence suggests that low levels of cytokine release from KCs constitute a survival signal that protects hepatocytes from cell death and in some cases, stimulates proliferation. [3]

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
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

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

Human: [1][3][7] Rat: [14][3]

References

List of the literature that was cited for this KER description. More help
  1. 1.0 1.1 1.2 Winwood, P.J., and M.J. Arthur (1993), Kupffer cells: their activation and role in animal models of liver injury and human liver disease, Semin Liver Dis, vol. 13, no. 1, pp. 50-59.
  2. 2.0 2.1 Luckey, S.W., and D.R. Petersen (2001), Activation of Kupffer cells during the course of carbon tetrachloride-induced liver injury and fibrosis in rats, Exp Mol Pathol, vol. 71, no. 3, pp. 226-240.
  3. 3.0 3.1 3.2 3.3 3.4 Roberts, R.A. et al. (2007), Role of the Kupffer cell in mediating hepatic toxicity and carcinogenesis, Toxicol Sci, vol. 96, no. 1, pp. 2-15.
  4. 4.0 4.1 Malhi, H. et al. (2010), Hepatocyte death: a clear and present danger, Physiol Rev, vol. 90, no. 3, pp. 1165-1194.
  5. 5.0 5.1 Canbay, A., S.L. Friedman and G.J. Gores (2004), Apoptosis: the nexus of liver injury and fibrosis, Hepatology, vol. 39, no. 2, pp. 273-278.
  6. 6.0 6.1 Orrenius, S., P. Nicotera and B. Zhivotovsky (2011), Cell death mechanisms and their implications in toxicology, Toxicol. Sci, vol. 119, no. 1, pp. 3-19.
  7. 7.0 7.1 7.2 Kolios, G., V. Valatas and E. Kouroumalis (2006), Role of Kupffer cells in the pathogenesis of liver disease, World J.Gastroenterol, vol. 12, no. 46, pp. 7413-7420.
  8. 8.0 8.1 Kisseleva T and Brenner DA, (2008), Mechanisms of Fibrogenesis, Exp Biol Med, vol. 233, no. 2, pp. 109-122.
  9. 9.0 9.1 Jaeschke, H. (2011), Reactive oxygen and mechanisms of inflammatory liver injury: Present concepts, J Gastroenterol Hepatol. vol. 26, suppl. 1, pp. 173-179.
  10. 10.0 10.1 Li, Jing-Ting et al. (2008), Molecular mechanism of hepatic stellate cell activation and antifibrotic therapeutic strategies, J Gastroenterol, vol. 43, no. 6, pp. 419–428.
  11. 11.0 11.1 Poli, G. (2000), Pathogenesis of liver fibrosis: role of oxidative stress, Mol Aspects Med, vol. 21, no. 3, pp. 49 – 98.
  12. Canbay, A. et al. (2003), Kupffer cell engulfment of apoptotic bodies stimulates death ligand and cytokine expression, Hepatology, vol. 38, no. 5, pp. 1188-1198.
  13. Soldatow, V.Y. et al. (2013), In vitro models for liver toxicity testing, Toxicol Res, vol. 2, no.1, pp. 23–39.
  14. 14.0 14.1 Tukov, F.F. et al. (2006), Modeling inflammation-drug interactions in vitro: a rat Kupffer cell-hepatocyte co-culture system, Toxicol In Vitro, vol. 20, no. 8, pp. 1488-1499.
  15. LeCluyse, E.L. et al. (2012), Organotypic liver culture models: meeting current challenges in toxicity testing, Crit Rev Toxicol, vol. 42, no. 6, 501-548.