Antagonism interactions based

Particular attention is given to the development of new mechanistic biomarker assays and bioassays that can be used as indices of the toxicity of mixtures. These biomarker assays are typically based on toxic mechanisms such as brain acetylcholinesterase inhibition, vitamin K antagonism, thyroxin antagonism, Ah-receptor-mediated toxicity, and interaction with the estrogenic receptor. They can give integrative measures of the toxicity of mixtures of compounds where the components of the mixture share the same mode of action. They can also give evidence of potentiation as well as additive toxicity. 

In the following, several terms used to describe interactions between chemicals are mentioned as well as basic concepts used in the hazard and risk assessment of chemical mixmres. The description of these basic concepts, first outlined by Bliss (1939) and Placket and Hewlett (1952), are based on the publications by Konemann and Pieters (1996), Cassee et al. (1998), and Groten et al. (2001). The definitions of additivity, synergism, antagonism, and potentiation are those of Klaassen (1995) and Seed et al. (1995). 

Approach provides a better base for subsequent development and testing of hypotheses concerning interactions between individual components in the mixture (e.g., synergisms, antagonisms). 

The broad-spectrum peptidomimetic lAP family inhibitors were also recently developed (107). Designed based on (7, 5)-bicyclic scaffold, these SMAC-mimetics were found to antagonize the protein interactions that involve XIAP, melanoma... 

Antagonism is a relatively common phenomenon, and antidotal strategies are often based on this type of interaction. Chemical antagonism is a simple interaction between two chemicals in which the formed complex is less toxic. Functional antagonism occurs when two chemicals have opposing actions on physiology, thus their combined effects counteract each other. Kinetic or dispositional antagonism occurs when the absorption, distribution, elimination, or biotransformation of a chemical is altered by... 

WOE), which estimates the joint actions (additivity, antagonism and exaggeration) for binary mixtures of chemicals based on the information on individual components. Several factors such as mechanistic interaction, uncertainty factors, route of exposure etc. are taken into account. The better the data set on the individual chemicals is, the more precise the joint action can be predicted. The draw back is the high- to low-dose extrapolation as most of the individual toxicity information is developed at high doses. According to WOE evaluations, considering common mechanisms for simple chemical mixtures can lead to better estimates of the observed toxic responses than the default assumption of dose additivity. 

Sigmoid Emax Model Jonkers and colleagues [80] studied the pharmacodynamics of racemic metoprolol, a cardioselective beta-blocker, and the active S-isomer in extensive metabolizers (EMs) and poor metabolizers (PMs). The drug effect studied was the antagonism by metoprolol of terbutaline-induced hypokalemia (abnormally low potassium concentration in the blood). The pharmacodynamic interaction was described by a sigmoidal function for competitive antagonism based on the earlier work of Holford and Sheiner [81] ... 

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