Difference between revisions of "Relationship:1134"
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|[[Aop:177|Cyclooxygenase 1 (COX1) inhibition leading to renal failure and mortality]]||Directly Leads to||[[Relationship:1134#Weight of Evidence|Strong]]|| | |[[Aop:177|Cyclooxygenase 1 (COX1) inhibition leading to renal failure and mortality]]||Directly Leads to||[[Relationship:1134#Weight of Evidence|Strong]]|| | ||
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+ | |[[Aop:186|unknown MIE leading to renal failure and mortality]]||Directly Leads to|||| | ||
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Latest revision as of 00:48, 28 November 2016
Contents
Key Event Relationship Overview
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Description of Relationship
Upstream Event | Downstream Event/Outcome |
---|---|
renal proximal tubular necrosis, Occurrence | blood potassium concentration, Increased |
AOPs Referencing Relationship
AOP Name | Type of Relationship | Weight of Evidence | Quantitative Understanding |
---|---|---|---|
Organic anion transporter (OAT1) inhibition leading to renal failure and mortality | Directly Leads to | Moderate | |
Cyclooxygenase 1 (COX1) inhibition leading to renal failure and mortality | Directly Leads to | Strong | |
unknown MIE leading to renal failure and mortality | Directly Leads to |
Taxonomic Applicability
Name | Scientific Name | Evidence | Links |
---|
How Does This Key Event Relationship Work
Weight of Evidence
Biological Plausibility
Empirical Support for Linkage
Include consideration of temporal concordance here
Uncertainties or Inconsistencies
Quantitative Understanding of the Linkage
Is it known how much change in the first event is needed to impact the second? Are there known modulators of the response-response relationships? Are there models or extrapolation approaches that help describe those relationships?