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Selective two-dimensional effect-directed analysis with thin-layer chromatography

delete2017-11-01
delete18
PRE
AI
L
Lena Stütz *
S
Stefan Weiß
W
W. Schulz
W
Wolfgang Schwack
R
Rudi Winzenbacher
DOI:10.1016/j.chroma.2017.10.009delete
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摘要

摘要

En 中文
There are thousands of organic trace substances in the environment that are not fully characterized, and evaluation of their relevance to the ecosystem is difficult. Effect-directed analysis (EDA) is a suitable tool to assess the effects of a substance via in-vitro bioassays, which can provide information about the relevance of the substance. High-performance thin-layer chromatography (HPTLC) has been shown to be a good method for fractionation. Environmental samples, however, often have high complexity, which is why the peak capacity of HPTLC is not sufficient. Therefore, this study focused on the development of selective two-dimensional (2D) HPTLC-EDA to increase the peak capacity and facilitate the identification of effective compounds. Thus, only effective zones were selected in the first dimension in terms of heart cutting and were transferred to the second dimension through elution head-based extraction. Three 2D approaches were developed and validated. The best results in terms of peak capacity and orthogonality were achieved when the retardation factors of the first dimension were used to adjust the mobile phase (MP) for the second dimension. Applying the acetylcholinesterase (AChE) inhibition assay as an example EDA, analysis of spiked surface water by 2D HPTLC-EDA allowed zones with neurotoxic effects to responsible substances to be assigned. The 2D separation reduced the complexity of effective zones and thus facilitated the subsequent identification of effective compounds. Knowledge about a substanceis effects enabled assessment of its relevance to the environment. (C) 2017 Elsevier B.V. All rights reserved.
Keyword:
Two-dimensional separation
Acetylcholinesterase inhibition assay
Elution head-based extraction
Peak capacity
Orthogonality
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期刊

Journal of Chromatography A 封面图
Journal of Chromatography A
IF:
4
论文数:
3.2W
被引数:
5.2W

机构

U
University Hohenheim
学者数:
6.1K
论文数: 5.8K
被引数: 2.3K
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