The DOI matches its Crossref record; 314 of the 314 references it cites were found in a registry or an index.
Oxidative stress in Alzheimer's disease
Open accessAbstract
Oxidative damage is a major feature in the pathophysiology of Alzheimer's disease (AD). In this review, we discuss free radical-mediated damage to the biochemical components involved in the pathology and clinical symptoms of AD. We explain how amyloid beta-protein (Abeta), microtubule-associated protein tau, presenilins, apolipoprotein E, mitochondria and proteases play a role in increasing oxidative stress in AD. Abeta not only can induce oxidative stress, but its generation is also increased as a result of oxidative stress. Finally, a hypothetical model linking oxidative stress with beta-amyloid and neurofibrillary tangle pathology in AD is proposed.
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Cites
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Cited by
Brain oxidative stress in a triple-transgenic mouse model of Alzheimer disease
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Antioxidant activities and phenolics content of eight species of seaweeds from north Borneo
Matanjun, P., Mohamed, S., Mustapha, N. M., Muhammad, K., & Ming, C. H. (2008) · Journal of Applied Phycology · doi:10.1007/s10811-007-9264-6 · Cited by 342
Neuroprotective effect of natural products against Alzheimer’s disease
Essa, M. M., Vijayan, R. K., Castellano-Gonzalez, G., Memon, M. A., Braidy, N., & Guillemin, G. J. (2012) · Neurochemical Research · doi:10.1007/s11064-012-0799-9 · Cited by 278
Neuroprotective Strategies for Neurological Disorders by Natural Products: An update
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Metadata
- Authors
- Chauhan, V., & Chauhan, A.
- Venue
- Pathophysiology
- Publisher
- Elsevier BV
- Published
- 2006-08
- Volume
- 13
- Issue
- 3
- Pages
- 195-208
- ISSN
- 0928-4680 (ISSN-L)
- OpenAlex
- W2091711919
- Cited by
- 342
- References
- 314
- FWCI
- 8.04
- Type
- journal article
- Language
- en
- Open access
- gold
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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.