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Cited by 301

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Flavonoids protect LDL from oxidation and attenuate atherosclerosis

Fuhrman, Bianca, Aviram, Michael·2001·Current Opinion in Lipidology

Abstract

Consumption of some plant-derived flavonoids results in their absorption and appearance in plasma and tissues. The inverse relationship between dietary flavonoids consumption and cardiovascular diseases may be associated with the ability of flavonoids to attenuate LDL oxidation, macrophage foam cell formation and atherosclerosis. The effect of flavonoids on arterial cell-mediated oxidation of LDL is determined by their accumulation in the lipoprotein and in arterial cells, such as macrophages. Flavonoids can reduce LDL lipid peroxidation by scavenging reactive oxygen/nitrogen species, chelation of transition metal ions and sparing of LDL-associated antioxidants. They can also reduce macrophage oxidative stress by inhibition of cellular oxygenases [such as nicotinamide adenine dinucleotide phosphate, reduced form (NADPH) oxidase] or by activating cellular antioxidants (such as the glutathione system). Thus, plant flavonoids, as potent natural antioxidants that protect against lipid peroxidation in arterial cells and lipoproteins, significantly attenuate the development of atherosclerosis.

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Metadata

Authors
Fuhrman, B., & Aviram, M.
Venue
Current Opinion in Lipidology
Published
2001-02
Volume
12
Issue
1
Pages
41-48
ISSN
0957-9672 (ISSN-L)
OpenAlex
W2021543924
Cited by
301
References
2
FWCI
8.71
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Flavonoids protect LDL from oxidation and attenuate atherosclerosis. https://app.cochat.ai/papers/10.1097/00041433-200102000-00008
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Fuhrman, B., & Aviram, M. (2001). Flavonoids protect LDL from oxidation and attenuate atherosclerosis. Current Opinion in Lipidology. https://doi.org/10.1097/00041433-200102000-00008

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.