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Antioxidative enzyme activities in human erythrocytes

Open access
Andersen, Helle Raun, Nielsen, Jesper B, Nielsen, Flemming, Grandjean, Philippe·1997·Clinical Chemistry

Abstract

Reliable and standardized methods are necessary to determine the expression of antioxidative enzymes and their role in maintaining health. In addition, the variability of the enzyme activities within the general population caused by age, gender, and life-style factors must be described. This study describes methodological conditions that are suitable for analyzing copper–zinc superoxide dismutase (CuZn-SOD), glutathione peroxidase (GSH-Px), catalase (CAT), and glutathione reductase (GR) in human erythrocytes with a high degree of reproducibility. Intervals for the enzyme activities have been established in a randomly selected population of 220 individuals between 20 and 89 years of age. An age-related decrease was observed in CuZn-SOD and GR activities, whereas no age-related changes were demonstrated for GSH-Px and CAT. The GSH-Px activity was positively associated with the intake of dietary supplements and negatively correlated with tobacco consumption. These factors probably account for the fact that women tended to have higher GSH-Px activity.

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Metadata

Authors
Andersen, H. R., Nielsen, J. B., Nielsen, F., & Grandjean, P.
Venue
Clinical Chemistry
Published
1997-04-01
Volume
43
Issue
4
Pages
562-568
ISSN
  • 0009-9147 (ISSN-L)
  • 1530-8561
OpenAlex
W1955393669
Cited by
301
References
0
FWCI
2.44
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Antioxidative enzyme activities in human erythrocytes. https://app.cochat.ai/papers/10.1093/clinchem/43.4.562
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Andersen, H. R., Nielsen, J. B., Nielsen, F., & Grandjean, P. (1997). Antioxidative enzyme activities in human erythrocytes. Clinical Chemistry. https://doi.org/10.1093/clinchem/43.4.562

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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.