کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
7608008 | 1493370 | 2018 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Employing immuno-affinity for the analysis of various microbial metabolites of the mycotoxin deoxynivalenol
ترجمه فارسی عنوان
استفاده از مصنوعی ایمنی برای تجزیه و تحلیل متابولیت های مختلف میکروبی از میکوکوتوکسیک دئوسینوآیلوآنول
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
موضوعات مرتبط
مهندسی و علوم پایه
شیمی
شیمی آنالیزی یا شیمی تجزیه
چکیده انگلیسی
Deoxynivalenol (DON) is a type B trichothecene mycotoxin that is commonly detected in grains infested with Fusarium species. The maximum tolerated levels of DON in the majority of world's countries are restricted to 0.75â¯mgâ¯kgâ1 within the human food chain and to less than 1-5â¯mgâ¯kgâ1 in animal feed depending on the feed material and/or animal species due to DON's short and long-term adverse effects on human health and animal productivity. The ability to accurately analyze DON and some of its fungal/bacterial metabolites is increasingly gaining a paramount importance in food/feed analysis and research. In this study, we used the immuno-affinity approach to enrich and detect DON and three of its bacterial metabolites, namely 3-epi-DON, 3-keto-DON, and deepoxy-DON (DOM-1). The optimized enrichment step coupled with high performance liquid chromatography can accurately and reproducibly quantify the aforementioned metabolites in feed matrixes (silage extract as an example in this case). It minimizes any background interface and provides a fast and easy-to-operate protocol for the analytical determination of such metabolites. More importantly, the presented data demonstrates the ability of the utilized monoclonal antibody, generated originally to capture DON in Enzyme-Linked Immunosorbent Assays (ELISA), to cross react with three less/non-toxic DON metabolites. This raises the concerns about the genuine need to account for such cross-reactivity when DON contamination is assessed through an immuno-affinity based analyses using the investigated antibody.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Chromatography A - Volume 1556, 29 June 2018, Pages 81-87
Journal: Journal of Chromatography A - Volume 1556, 29 June 2018, Pages 81-87
نویسندگان
Yan Zhu, Yousef I. Hassan, Suqin Shao, Ting Zhou,