The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Protein Corona Fingerprinting Predicts the Cellular Interaction of Gold and Silver Nanoparticles
Abstract
Using quantitative models to predict the biological interactions of nanoparticles will accelerate the translation of nanotechnology. Here, we characterized the serum protein corona 'fingerprint' formed around a library of 105 surface-modified gold nanoparticles. Applying a bioinformatics-inspired approach, we developed a multivariate model that uses the protein corona fingerprint to predict cell association 50% more accurately than a model that uses parameters describing nanoparticle size, aggregation state, and surface charge. Our model implicates a set of hyaluronan-binding proteins as mediators of nanoparticle-cell interactions. This study establishes a framework for developing a comprehensive database of protein corona fingerprints and biological responses for multiple nanoparticle types. Such a database can be used to develop quantitative relationships that predict the biological responses to nanoparticles and will aid in uncovering the fundamental mechanisms of nano-bio interactions.
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
Nanoparticle Size and Surface Chemistry Determine Serum Protein Adsorption and Macrophage Uptake
Walkey, C. D., Olsen, J. B., Guo, H., Emili, A., & Chan, W. C. W. (2012) · Journal of the American Chemical Society · doi:10.1021/ja2084338 · Cited by 1,926
Self-citationMonopoli, M. P., Walczyk, D., Campbell, A., Elia, G., Lynch, I., Baldelli Bombelli, F., & Dawson, K. A. (2011) · Journal of the American Chemical Society · doi:10.1021/ja107583h · Cited by 1,835
Walkey, C. D., & Chan, W. C. W. (2012) · Chem. Soc. Rev. · doi:10.1039/c1cs15233e · Cited by 1,758
Self-citationTime Evolution of the Nanoparticle Protein Corona
Casals, E., Pfaller, T., Duschl, A., Oostingh, G. J., & Puntes, V. (2010) · ACS Nano · doi:10.1021/nn901372t · Cited by 1,211
Cited by
Cancer nanomedicine: progress, challenges and opportunities
Shi, J., Kantoff, P. W., Wooster, R., & Farokhzad, O. C. (2017) · Nature Reviews Cancer · doi:10.1038/nrc.2016.108 · Cited by 5,873
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
Self-citationDiverse Applications of Nanomedicine
Pelaz, B., Alexiou, C., Alvarez-Puebla, R. A., Alves, F., Andrews, A. M., Ashraf, S., Balogh, L. P., Ballerini, L., Bestetti, A., Brendel, C., et al. (2017) · ACS Nano · doi:10.1021/acsnano.6b06040 · Cited by 1,350
Self-citationLee, K., Conboy, M., Park, H. M., Jiang, F., Kim, H. J., Dewitt, M. A., Mackley, V. A., Chang, K., Rao, A., Skinner, C., et al. (2017) · Nature Biomedical Engineering · doi:10.1038/s41551-017-0137-2 · Cited by 755
Complement proteins bind to nanoparticle protein corona and undergo dynamic exchange in vivo
Chen, F., Wang, G., Griffin, J. I., Brenneman, B., Banda, N. K., Holers, V. M., Backos, D. S., Wu, L., Moghimi, S. M., & Simberg, D. (2017) · Nature Nanotechnology · doi:10.1038/nnano.2016.269 · Cited by 599
Meta-analysis of cellular toxicity for cadmium-containing quantum dots
Oh, E., Liu, R., Nel, A., Gemill, K. B., Bilal, M., Cohen, Y., & Medintz, I. L. (2016) · Nature Nanotechnology · doi:10.1038/nnano.2015.338 · Cited by 502
Self-citationBiological Identity of Nanoparticles In Vivo : Clinical Implications of the Protein Corona
Caracciolo, G., Farokhzad, O. C., & Mahmoudi, M. (2017) · Trends in Biotechnology · doi:10.1016/j.tibtech.2016.08.011 · Cited by 426
In vivo degeneration and the fate of inorganic nanoparticles
Feliu, N., Docter, D., Heine, M., del Pino, P., Ashraf, S., Kolosnjaj-Tabi, J., Macchiarini, P., Nielsen, P., Alloyeau, D., Gazeau, F., et al. (2016) · Chemical Society Reviews · doi:10.1039/c5cs00699f · Cited by 423
Hadjidemetriou, M., Al-Ahmady, Z., Mazza, M., Collins, R. F., Dawson, K., & Kostarelos, K. (2015) · ACS Nano · doi:10.1021/acsnano.5b03300 · Cited by 358
Impact of protein pre-coating on the protein corona composition and nanoparticle cellular uptake
Mirshafiee, V., Kim, R., Park, S., Mahmoudi, M., & Kraft, M. L. (2016) · Biomaterials · doi:10.1016/j.biomaterials.2015.10.019 · Cited by 316
Secreted Biomolecules Alter the Biological Identity and Cellular Interactions of Nanoparticles
Albanese, A., Walkey, C. D., Olsen, J. B., Guo, H., Emili, A., & Chan, W. C. W. (2014) · ACS Nano · doi:10.1021/nn4061012 · Cited by 258
Self-citationValsami-Jones, E., & Lynch, I. (2015) · Science · doi:10.1126/science.aad0768 · Cited by 232
An evaluation of blood compatibility of silver nanoparticles
Huang, H., Lai, W., Cui, M., Liang, L., Lin, Y., Fang, Q., Liu, Y., & Xie, L. (2016) · Scientific Reports · doi:10.1038/srep25518 · Cited by 186
Dynamic protein coronas revealed as a modulator of silver nanoparticle sulphidation in vitro
Miclăuş, T., Beer, C., Chevallier, J., Scavenius, C., Bochenkov, V. E., Enghild, J. J., & Sutherland, D. S. (2016) · Nature Communications · doi:10.1038/ncomms11770 · Cited by 174
Kang, B., Okwieka, P., Schöttler, S., Winzen, S., Langhanki, J., Mohr, K., Opatz, T., Mailänder, V., Landfester, K., & Wurm, F. R. (2015) · Angewandte Chemie International Edition · doi:10.1002/anie.201502398 · Cited by 159
Bigdeli, A., Palchetti, S., Pozzi, D., Hormozi-Nezhad, M. R., Baldelli Bombelli, F., Caracciolo, G., & Mahmoudi, M. (2016) · ACS Nano · doi:10.1021/acsnano.6b00261 · Cited by 157
Enhanced immunocompatibility of ligand-targeted liposomes by attenuating natural IgM absorption
Guan, J., Shen, Q., Zhang, Z., Jiang, Z., Yang, Y., Lou, M., Qian, J., Lu, W., & Zhan, C. (2018) · Nature Communications · doi:10.1038/s41467-018-05384-1 · Cited by 152
Foroozandeh, P., & Aziz, A. A. (2015) · Nanoscale Research Letters · doi:10.1186/s11671-015-0922-3 · Cited by 143
Stealth Effect of Biomolecular Corona on Nanoparticle Uptake by Immune Cells
Caracciolo, G., Palchetti, S., Colapicchioni, V., Digiacomo, L., Pozzi, D., Capriotti, A. L., La Barbera, G., & Laganà, A. (2015) · Langmuir · doi:10.1021/acs.langmuir.5b02158 · Cited by 131
Digiacomo, L., Cardarelli, F., Pozzi, D., Palchetti, S., Digman, M. A., Gratton, E., Capriotti, A. L., Mahmoudi, M., & Caracciolo, G. (2017) · Nanoscale · doi:10.1039/c7nr06437c · Cited by 109
Cao, C., Zhao, J., Lu, M., Garvey, C. J., & Stenzel, M. H. (2019) · Biomacromolecules · doi:10.1021/acs.biomac.8b01707 · Cited by 72
Han, B., Qu, C., Park, K., Konieczny, S. F., & Korc, M. (2016) · Cancer Letters · doi:10.1016/j.canlet.2015.12.003 · Cited by 53
Nanocarrier imaging at single-cell resolution across entire mouse bodies with deep learning
Luo, J., Molbay, M., Chen, Y., Horvath, I., Kadletz, K., Kick, B., Zhao, S., Al-Maskari, R., Singh, I., Ali, M., et al. (2025) · Nature Biotechnology · doi:10.1038/s41587-024-02528-1 · Cited by 53
Milk Protein Adsorption on Metallic Iron Surfaces
(2023) · doi:10.3390/nano13121857 · Cited by 17
Multiscale modelling of biomolecular corona formation on metallic surfaces
Amini, P. M., Rouse, I., Subbotina, J., & Lobaskin, V. (2024) · Beilstein Journal of Nanotechnology · doi:10.3762/bjnano.15.21 · Cited by 10
Metadata
- Authors
- Walkey, C. D., Olsen, J. B., Song, F., Liu, R., Guo, H., Olsen, D. W. H., Cohen, Y., Emili, A., & Chan, W. C. W.
- Venue
- ACS Nano
- Publisher
- American Chemical Society (ACS)
- Published
- 2014-02-25
- Volume
- 8
- Issue
- 3
- Pages
- 2439-2455
- ISSN
- 1936-0851 (ISSN-L)
- 1936-086X
- OpenAlex
- W2323147899
- Cited by
- 815
- References
- 4
- FWCI
- 29.96
- Type
- journal article
- Language
- en
- Open access
- closed
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.
