کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8554180 | 1562699 | 2018 | 33 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Generalized concentration addition accurately predicts estrogenic potentials of mixtures and environmental samples containing partial agonists
ترجمه فارسی عنوان
افزودن غلظت عمومی با دقت پتانسیل استروژن موجود در مخلوط ها و نمونه های محیطی حاوی آگونیست های جزئی را پیش بینی می کند
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کلمات کلیدی
AHRTEQEREEQSeefEE2GCAEC50CECEDCEEQFBS17α-ethinylestradiol - 17α-etinylestradiol17β-estradiol - 17β استرادیولEnvironmental quality standard - استاندارد کیفیت محیط زیستEstrone - استرونIndependent action - اقدام مستقلCompetitive antagonism - انطباق رقابتیfetal bovine serum - سرم جنین گاوConcentration addition - علاوه بر تمرکزestrogen response element - عنصر پاسخ استروژنEndocrine-disrupting chemicals - مواد شیمیایی خرابکار غدد درون ریزNonylphenol - نونیل فنولaryl hydrocarbon receptor - گیرنده آرویل هیدروکربنEstrogen receptor - گیرنده استروژن
موضوعات مرتبط
علوم زیستی و بیوفناوری
علوم محیط زیست
بهداشت، سم شناسی و جهش زایی
چکیده انگلیسی
Cell-based bioanalytical tools are considered one alternative to overcome limitations of sensitivities of instrumental, analytical chemistry for monitoring estrogenic chemicals in the environment. Because these tools also reflect non-additive interactions of chemicals in mixtures, their outcomes often deviate from outcomes of chemical analytical approaches that assume additivity, e.g. the concentration addition (CA) model. Often this is because CA is unable to adequately represent effects of partial agonists, i.e. estrogens with lesser efficacies compared to 17β-estradiol. A generalized concentration addition (GCA) model has been proposed to address this shortcoming. In the present study, we investigated effects of mixtures of isomers of nonylphenol as partial model agonists in a cell-based estrogenicity assay. Whether the GCA model was able to more accurately predict the outcomes of these and previously published mixture experiments was evaluated, as well as the potency of a set of comprehensively characterized sewage effluent samples, compared to CA. If samples contained partial agonists, the GCA model consistently predicted potencies of mixtures and extracts of environmental samples more accurately than did the CA model. These findings enable more accurate estimations of potencies of estrogenicity explained by concentrations of agonists and partial agonists, thus significantly improving the ability to identify causative chemicals.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Toxicology in Vitro - Volume 46, February 2018, Pages 294-303
Journal: Toxicology in Vitro - Volume 46, February 2018, Pages 294-303
نویسندگان
Markus Brinkmann, Markus Hecker, John P. Giesy, Paul D. Jones, Hans Toni Ratte, Henner Hollert, Thomas G. Preuss,