The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Coating Optimization of Superparamagnetic Iron Oxide Nanoparticles for High T2 Relaxivity
Open accessAbstract
We describe a new method for coating superparamagnetic iron oxide nanoparticles (SPIOs) and demonstrate that, by fine-tuning the core size and PEG coating of SPIOs, the T2 relaxivity per particle can be increased by >200-fold. With 14 nm core and PEG1000 coating, SPIOs can have T2 relaxivity of 385 s-1 mM-1, which is among the highest per-Fe atom relaxivities. In vivo tumor imaging results demonstrated the potential of the SPIOs for clinical applications.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Recent advances with liposomes as pharmaceutical carriers
Torchilin, V. P. (2005) · Nature Reviews Drug Discovery · doi:10.1038/nrd1632 · Cited by 5,282
Wang, Y.-X. J., Hussain, S. M., & Krestin, G. P. (2001) · European Radiology · doi:10.1007/s003300100908 · Cited by 1,381
Winter, P. M., Morawski, A. M., Caruthers, S. D., Fuhrhop, R. W., Zhang, H., Williams, T. A., Allen, J. S., Lacy, E. K., Robertson, J. D., Lanza, G. M., et al. (2003) · Circulation · doi:10.1161/01.cir.0000093185.16083.95 · Cited by 696
Cited by
The Effect of Nanoparticle Size on In Vivo Pharmacokinetics and Cellular Interaction
Hoshyar, N., Gray, S., Han, H., & Bao, G. (2016) · Nanomedicine · doi:10.2217/nnm.16.5 · Cited by 1,990
Self-citationPhysical Principles of Nanoparticle Cellular Endocytosis
Zhang, S., Gao, H., & Bao, G. (2015) · ACS Nano · doi:10.1021/acsnano.5b03184 · Cited by 1,103
Self-citationLee, N., & Hyeon, T. (2012) · Chem. Soc. Rev. · doi:10.1039/c1cs15248c · Cited by 995
In vivo delivery, pharmacokinetics, biodistribution and toxicity of iron oxide nanoparticles
Arami, H., Khandhar, A., Liggitt, D., & Krishnan, K. M. (2015) · Chemical Society Reviews · doi:10.1039/c5cs00541h · Cited by 830
Chemical Synthesis and Assembly of Uniformly Sized Iron Oxide Nanoparticles for Medical Applications
Ling, D., Lee, N., & Hyeon, T. (2015) · Accounts of Chemical Research · doi:10.1021/acs.accounts.5b00038 · Cited by 513
Metadata
- Authors
- Tong, S., Hou, S., Zheng, Z., Zhou, J., & Bao, G.
- Venue
- Nano Letters
- Publisher
- American Chemical Society (ACS)
- Published
- 2010-10-12
- Volume
- 10
- Issue
- 11
- Pages
- 4607-4613
- ISSN
- 1530-6984 (ISSN-L)
- 1530-6992
- OpenAlex
- W2052883298
- Cited by
- 424
- References
- 3
- FWCI
- 12.74
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
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.
