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Ans E. M. F. Soffers

Researcher at Wageningen University and Research Centre

Publications -  33
Citations -  1315

Ans E. M. F. Soffers is an academic researcher from Wageningen University and Research Centre. The author has contributed to research in topics: Hydroxylation & Quantitative structure–activity relationship. The author has an hindex of 18, co-authored 33 publications receiving 1207 citations. Previous affiliations of Ans E. M. F. Soffers include Laboratory of Molecular Biology.

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The influence of pH on antioxidant properties and the mechanism of antioxidant action of hydroxyflavones.

TL;DR: The effect of the pH on antioxidant properties of a series of hydroxyflavones was investigated and it was concluded that upon deprotonation the TEAC value increases (radical scavenging capacity increases) because electron-, not H*-, donation becomes easier.
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Alkaloids in the human food chain - Natural occurrence and possible adverse effects

TL;DR: The present paper summarizes the occurrence of alkaloids in the food chain, their mode of action and possible adverse effects including a safety assessment, and for many alkaloid that are known constituents of the modern food chain and of possible concern, tolerable daily intake values have so far not been defined.
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TEAC antioxidant activity of 4-hydroxybenzoates.

TL;DR: Experimental data and computer-calculated characteristics indicate that the antioxidant behavior of the monoanionic forms of the 4-hydroxybenzoates is not determined by the tendency of the molecule to donate an electron, but by its ability to donate a hydrogen atom.
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Regioselectivity of cytochrome P-450 catalyzed hydroxylation of fluorobenzenes predicted by calculated frontier orbital substrate characteristics.

TL;DR: It is concluded that the aromatic hydroxylation of fluorobenzenes proceeds through an initial electrophilic attack of ( FeO)3+ on the aromatic substrate, and not through initial electron abstraction followed by attack of the (FeO)2+ species on the substrate radical cation.
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Computer-modeling-based QSARs for analyzing experimental data on biotransformation and toxicity

TL;DR: The present paper focuses on the possibilities and restrictions of using computer-based QSAR modeling for analyzing experimental toxicological data, with emphasis on examples from the field of biotransformation and toxicity.