The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Minimal "Self" Peptides That Inhibit Phagocytic Clearance and Enhance Delivery of Nanoparticles
Open accessAbstract
Stealth Delivery: Delivery of therapeutics and imaging agents is hampered by the ability of the innate immune system to recognize and clear foreign particles. "Self" cells are protected from phagocytic clearance by the membrane protein CD47 that interacts with signal regulatory protein-α (SIRPα) on macrophages. Taking advantage of this protective strategy, Rodriguez et al. (p. 971 ) labeled nanoparticles with computationally designed minimal human-CD47–based peptide (hCD47). When injected into a strain of mice in which macrophages expressed a SIRPα that cross-reacts with hCD47, the peptide prevented clearance of nanoparticles and enhanced drug delivery to tumors.
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Cited by
Principles of nanoparticle design for overcoming biological barriers to drug delivery
Blanco, E., Shen, H., & Ferrari, M. (2015) · Nature Biotechnology · doi:10.1038/nbt.3330 · Cited by 7,002
Cancer nanomedicine: progress, challenges and opportunities
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Analysis of nanoparticle delivery to tumours
Wilhelm, S., Tavares, A. J., Dai, Q., Ohta, S., Audet, J., Dvorak, H. F., & Chan, W. C. W. (2016) · Nature Reviews Materials · doi:10.1038/natrevmats.2016.14 · Cited by 5,218
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Progress and challenges towards targeted delivery of cancer therapeutics
Rosenblum, D., Joshi, N., Tao, W., Karp, J. M., & Peer, D. (2018) · Nature Communications · doi:10.1038/s41467-018-03705-y · Cited by 2,220
Metadata
- Authors
- Rodriguez, P. L., Harada, T., Christian, D. A., Pantano, D. A., Tsai, R. K., & Discher, D. E.
- Venue
- Science
- Published
- 2013-02-22
- Volume
- 339
- Issue
- 6122
- Pages
- 971-975
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W2169515956
- Cited by
- 985
- References
- 6
- FWCI
- 37.13
- 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).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
