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Cited by 440

The DOI matches its Crossref record; 34 of the 34 references it cites were found in a registry or an index.

Oxidative stress and human diseases: Origin, link, measurement, mechanisms, and biomarkers

Giustarini, Daniela, Dalle-Donne, Isabella, Tsikas, Dimitrios, Rossi, Ranieri·2009·Critical Reviews in Clinical Laboratory Sciences

Abstract

Oxidative stress has been related increasingly to the onset and/or progression of a growing number of human diseases. However, large studies on supplementation with anti-oxidants for prevention or treatment of different pathologies have yielded contradictory and mostly negative results, as documented by numerous meta-analyses and clinical trials. Here we analyze in detail the findings of these studies and discuss major aspects that, in our opinion, are likely to be responsible for these confounding data. With the belief that a clear correlation between disease and oxidative stress is far from being proven for most pathological conditions, our argument focuses on the following points: i) choice of biomarker(s) and/or the biological system(s) for the analyses; ii) pitfalls in pre-analytical and analytical methods for assessing oxidative stress; and iii) scientific misconduct. Eventually, suggestions aiming to obtain more convergent results on this topic are provided.

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Metadata

Authors
Giustarini, D., Dalle-Donne, I., Tsikas, D., & Rossi, R.
Venue
Critical Reviews in Clinical Laboratory Sciences
Published
2009-10-06
Volume
46
Issue
5-6
Pages
241-281
ISSN
  • 1040-8363 (ISSN-L)
  • 1549-781X
OpenAlex
W2119541485
Cited by
440
References
34
FWCI
3.33
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Oxidative stress and human diseases: Origin, link, measurement, mechanisms, and biomarkers. https://app.cochat.ai/papers/10.3109/10408360903142326
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Giustarini, D., Dalle-Donne, I., Tsikas, D., & Rossi, R. (2009). Oxidative stress and human diseases: Origin, link, measurement, mechanisms, and biomarkers. Critical Reviews in Clinical Laboratory Sciences. https://doi.org/10.3109/10408360903142326

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