New approach to predicts toxic mixtures effects of estrogen receptor agonists with different parameters of individual curves

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11310%2F15%3A10324706" target="_blank" >RIV/00216208:11310/15:10324706 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1016/j.toxlet.2015.08.1001" target="_blank" >http://dx.doi.org/10.1016/j.toxlet.2015.08.1001</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.toxlet.2015.08.1001" target="_blank" >10.1016/j.toxlet.2015.08.1001</a>

Jazyk výsledku

angličtina

Název v původním jazyce

New approach to predicts toxic mixtures effects of estrogen receptor agonists with different parameters of individual curves

Popis výsledku v původním jazyce

Human population is exposed permanently to various endocrine active compounds. Some of them are administered willingly as contraceptives and some are administered via environmental exposures. Because these compounds occur most commonly as complex mixtures, methods to predict an expected outcome of the combination exposure are crucial for correct risk assessment. Scientific articles mainly focused on a combination of two drugs with a similar mode of action. They predict mixture effects by simple toxic equivalency factors (TEF) for each chemicals or using generalized concentration addition (GCA) model with simplified version of the Hill function. Both the models have substantial limitations restricting they applicability. Our approach uses the full logistic function with all the four parameters to calculate the mixtures effects. This model still matches the isobologram pattern and therefore it is the most complex version of concentration addition. Using all the four parameters of the logistic function as the initial values, this approach can calculate the mixture effects of compounds with different slopes, or the compounds that are only partial agonists. As the result, this model predicts dose-response curves for selected mixtures. We used recombinant yeast estrogenic assay (YES) as a simple tool to confirm our equations. The advantage of the used assay was the fact, that we monitored only activation or inactivation of the estrogen receptor without any other metabolic transformations or toxic effects on the testing organism.

Název v anglickém jazyce

New approach to predicts toxic mixtures effects of estrogen receptor agonists with different parameters of individual curves

Popis výsledku anglicky

Human population is exposed permanently to various endocrine active compounds. Some of them are administered willingly as contraceptives and some are administered via environmental exposures. Because these compounds occur most commonly as complex mixtures, methods to predict an expected outcome of the combination exposure are crucial for correct risk assessment. Scientific articles mainly focused on a combination of two drugs with a similar mode of action. They predict mixture effects by simple toxic equivalency factors (TEF) for each chemicals or using generalized concentration addition (GCA) model with simplified version of the Hill function. Both the models have substantial limitations restricting they applicability. Our approach uses the full logistic function with all the four parameters to calculate the mixtures effects. This model still matches the isobologram pattern and therefore it is the most complex version of concentration addition. Using all the four parameters of the logistic function as the initial values, this approach can calculate the mixture effects of compounds with different slopes, or the compounds that are only partial agonists. As the result, this model predicts dose-response curves for selected mixtures. We used recombinant yeast estrogenic assay (YES) as a simple tool to confirm our equations. The advantage of the used assay was the fact, that we monitored only activation or inactivation of the estrogen receptor without any other metabolic transformations or toxic effects on the testing organism.

Druh

O - Ostatní výsledky

CEP obor

CI - Průmyslová chemie a chemické inženýrství

OECD FORD obor

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Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů