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Cited by 1,022

The DOI matches its Crossref record; 52 of the 52 references it cites were found in a registry or an index.

Oxidative Stress, Mitochondrial Dysfunction, and Aging

Open access
Cui, Hang, Kong, Yahui, Zhang, Hong·2012·Journal of Signal Transduction

Abstract

Aging is an intricate phenomenon characterized by progressive decline in physiological functions and increase in mortality that is often accompanied by many pathological diseases. Although aging is almost universally conserved among all organisms, the underlying molecular mechanisms of aging remain largely elusive. Many theories of aging have been proposed, including the free-radical and mitochondrial theories of aging. Both theories speculate that cumulative damage to mitochondria and mitochondrial DNA (mtDNA) caused by reactive oxygen species (ROS) is one of the causes of aging. Oxidative damage affects replication and transcription of mtDNA and results in a decline in mitochondrial function which in turn leads to enhanced ROS production and further damage to mtDNA. In this paper, we will present the current understanding of the interplay between ROS and mitochondria and will discuss their potential impact on aging and age-related diseases.

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Metadata

Authors
Cui, H., Kong, Y., & Zhang, H.
Venue
Journal of Signal Transduction
Publisher
Wiley
Published
2012-10-02
Volume
2012
Pages
1-13
ISSN
  • 2090-1739 (ISSN-L)
  • 2090-1747
OpenAlex
W2021460489
Cited by
1,022
References
52
FWCI
10.23
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Oxidative Stress, Mitochondrial Dysfunction, and Aging. https://app.cochat.ai/papers/10.1155/2012/646354
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Cui, H., Kong, Y., & Zhang, H. (2012). Oxidative Stress, Mitochondrial Dysfunction, and Aging. Journal of Signal Transduction. https://doi.org/10.1155/2012/646354

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.