The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.
Prevention of vascular inflammation by nanoparticle targeting of adherent neutrophils
Open accessAbstract
Inflammatory diseases such as acute lung injury and ischaemic tissue injury are caused by the adhesion of a type of white blood cell--polymorphonuclear neutrophils--to the lining of the circulatory system or vascular endothelium and unchecked neutrophil transmigration. Nanoparticle-mediated targeting of activated neutrophils on vascular endothelial cells at the site of injury may be a useful means of directly inactivating neutrophil transmigration and hence mitigating vascular inflammation. Here, we report a method employing drug-loaded albumin nanoparticles, which efficiently deliver drugs into neutrophils adherent to the surface of the inflamed endothelium. Using intravital microscopy of tumour necrosis factor-α-challenged mouse cremaster post-capillary venules, we demonstrate that fluorescently tagged albumin nanoparticles are largely internalized by neutrophils adherent to the activated endothelium via cell surface Fcɣ receptors. Administration of albumin nanoparticles loaded with the spleen tyrosine kinase inhibitor, piceatannol, which blocks 'outside-in' β2 integrin signalling in leukocytes, detached the adherent neutrophils and elicited their release into the circulation. Thus, internalization of drug-loaded albumin nanoparticles into neutrophils inactivates the pro-inflammatory function of activated neutrophils, thereby offering a promising approach for treating inflammatory diseases resulting from inappropriate neutrophil sequestration and activation.
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Cites
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Self-citationPreparation and Application of Cell Membrane-Camouflaged Nanoparticles for Cancer Therapy
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Self-citation
Metadata
- Authors
- Wang, Z., Li, J., Cho, J., & Malik, A. B.
- Venue
- Nature Nanotechnology
- Published
- 2014-02-23
- Volume
- 9
- Issue
- 3
- Pages
- 204-210
- ISSN
- 1748-3387 (ISSN-L)
- 1748-3395
- OpenAlex
- W2067500754
- Cited by
- 300
- References
- 24
- FWCI
- 5.95
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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