The DOI matches its Crossref record; 114 of the 114 references it cites were found in a registry or an index.
MATRIX METALLOPROTEINASE-2 (MMP-2) AND MMP-9 IN PULMONARY PATHOLOGY
Abstract
The lung is affected by a variety of disease processes that can lead to considerable morbidity and mortality. As the lung is the only organ for respiration and gas exchange, the structural and functional integrity of the lung is of primary importance. Various pathological processes affect the extracellular matrix (ECM) of the lung in an adverse manner, causing destruction of tissue integrity followed by tissue remodeling, which together impair normal pulmonary function. Matrix metalloproteinases (MMPs) are neutral proteinases that are involved in the breakdown and remodeling of the ECM under a variety of physiological and pathological conditions. MMP-2 and MMP-9, collectively known as the gelatinases, are particularly important in the pathogenesis of inflammatory, infectious, and neoplastic diseases in many organs including the lung. This review examines the expression of MMP-2 and MMP-9 in disease of the lung and discusses the role these gelatinases may play in disease progression.
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Metadata
- Authors
- Chakrabarti, S., & Patel, K. D.
- Venue
- Experimental Lung Research
- Publisher
- Informa UK Limited
- Published
- 2005-01
- Volume
- 31
- Issue
- 6
- Pages
- 599-621
- ISSN
- 0190-2148 (ISSN-L)
- 1521-0499
- OpenAlex
- W1989900054
- Cited by
- 279
- References
- 114
- FWCI
- 2.77
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: MATRIX METALLOPROTEINASE-2 (MMP-2) AND MMP-9 IN PULMONARY PATHOLOGY. https://app.cochat.ai/papers/10.1080/019021490944232
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- Chakrabarti, S., & Patel, K. D. (2005). MATRIX METALLOPROTEINASE-2 (MMP-2) AND MMP-9 IN PULMONARY PATHOLOGY. Experimental Lung Research. https://doi.org/10.1080/019021490944232
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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.
