The DOI matches its Crossref record; 98 of the 98 references it cites were found in a registry or an index.
The paradox of matrix metalloproteinases in infectious disease
Open accessAbstract
Summary: Matrix metalloproteinases (MMPs) are a family of proteolytic enzymes that perform multiple roles in the normal immune response to infection. MMPs facilitate leucocyte recruitment, cytokine and chemokine processing, defensin activation and matrix remodelling. However, excess MMP activity following infection may lead to immunopathology that causes host morbidity or mortality and favours pathogen dissemination or persistence. Here, we review the normal functions of MMPs in immunity and then discuss viral and bacterial infections where excess MMP activity has been implicated in pathology, specifically examining HIV, HTLV-1, hepatitis B, endotoxin shock, Helicobacter pylori and Mycobacterium tuberculosis. Tissue destruction may be exacerbated further by bacterial-derived enzymes which activate the host pro-MMPs. Finally, the potential for therapeutic targeting of excess MMP activity in infection is considered.
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Cites
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Hammerich, L., & Tacke, F. (2023) · Nature Reviews Gastroenterology & Hepatology · doi:10.1038/s41575-023-00807-x · Cited by 803
Matrix Metalloproteinases as Modulators of Inflammation
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Saunders, B. M., & Britton, W. J. (2007) · Immunology & Cell Biology · doi:10.1038/sj.icb.7100027 · Cited by 340
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Metadata
- Authors
- Elkington, P. T. G., O'Kane, C. M., & Friedland, J. S.
- Venue
- Clinical and Experimental Immunology
- Publisher
- Oxford University Press (OUP)
- Published
- 2005-06-16
- Volume
- 142
- Issue
- 1
- Pages
- 12-20
- ISSN
- 0009-9104 (ISSN-L)
- 1365-2249
- OpenAlex
- W2010004352
- Cited by
- 340
- References
- 98
- FWCI
- 4.27
- Type
- journal article
- Language
- en
- Open access
- bronze
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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.
