The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Size-Dependent Tumor Penetration and in Vivo Efficacy of Monodisperse Drug–Silica Nanoconjugates
Open accessAbstract
The size of a nanomedicine strongly correlates with its biodistribution, tissue penetration, and cell uptake. However, there is limited understanding how the size of nanomedicine impacts the overall antitumor efficacy. We designed and synthesized camptothecin-silica nanoconjugates (Cpt-NCs) with monodisperse particle sizes of 50 and 200 nm, two representative sizes commonly used in drug delivery, and evaluated their antitumor efficacy in murine tumor models. Our studies revealed that the 50 nm Cpt-NC showed higher anticancer efficacy than the larger analogue, due presumably to its faster cellular internalization and more efficient tumor accumulation and penetration. Our findings suggest that nanomedicine with smaller sizes holds great promise for improved cancer therapy.
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 therapeutics: an emerging treatment modality for cancer
Davis, M. E., Chen, Z., & Shin, D. M. (2008) · Nature Reviews Drug Discovery · doi:10.1038/nrd2614 · Cited by 4,233
Factors affecting the clearance and biodistribution of polymeric nanoparticles
Alexis, F., Pridgen, E., Molnar, L. K., & Farokhzad, O. C. (2008) · Molecular Pharmaceutics · doi:10.1021/mp800051m · Cited by 3,699
The effect of particle design on cellular internalization pathways
Gratton, S. E. A., Ropp, P. A., Pohlhaus, P. D., Luft, J. C., Madden, V. J., Napier, M. E., & DeSimone, J. M. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0801763105 · Cited by 2,918
Drug penetration in solid tumours
Minchinton, A. I., & Tannock, I. F. (2006) · Nature reviews. Cancer · doi:10.1038/nrc1893 · Cited by 2,805
Accumulation of sub-100 nm polymeric micelles in poorly permeable tumours depends on size
Cabral, H., Matsumoto, Y., Mizuno, K., Chen, Q., Murakami, M., Kimura, M., Terada, Y., Kano, M. R., Miyazono, K., Uesaka, M., et al. (2011) · Nature Nanotechnology · doi:10.1038/nnano.2011.166 · Cited by 2,429
Drug Resistance and the Solid Tumor Microenvironment
Tredan, O., Galmarini, C. M., Patel, K., & Tannock, I. F. (2007) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/djm135 · Cited by 2,116
Nanomedicine: current status and future prospects
Moghimi, S. M., Hunter, A. C., & Murray, J. C. (2005) · The FASEB Journal · doi:10.1096/fj.04-2747rev · Cited by 2,029
Shaping cups into phagosomes and macropinosomes
Swanson, J. A. (2008) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm2447 · Cited by 941
Cited by
Mesoporous silica nanoparticles in drug delivery and biomedical applications
Wang, Y., Zhao, Q., Han, N., Bai, L., Li, J., Liu, J., Che, E., Hu, L., Zhang, Q., Jiang, T., et al. (2015) · Nanomedicine: Nanotechnology, Biology and Medicine · doi:10.1016/j.nano.2014.09.014 · Cited by 1,192
Croissant, J. G., Fatieiev, Y., & Khashab, N. M. (2017) · Advanced Materials · doi:10.1002/adma.201604634 · Cited by 782
Emerging concepts in dendrimer‐based nanomedicine: from design principles to clinical applications
Kannan, R. M., Nance, E., Kannan, S., & Tomalia, D. A. (2014) · Journal of Internal Medicine · doi:10.1111/joim.12280 · Cited by 542
Li, H.-J., Du, J.-Z., Liu, J., Du, X.-J., Shen, S., Zhu, Y.-H., Wang, X., Ye, X., Nie, S., & Wang, J. (2016) · ACS Nano · doi:10.1021/acsnano.6b02326 · Cited by 537
Engineered nanomedicines with enhanced tumor penetration
Ding, J., Chen, J., Gao, L., Jiang, Z., Zhang, Y., Li, M., Xiao, Q., Lee, S. S., & Chen, X. (2019) · Nano Today · doi:10.1016/j.nantod.2019.100800 · Cited by 420
Janjua, T. I., Cao, Y., Kleitz, F., Linden, M., Yu, C., & Popat, A. (2023) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2023.115115 · Cited by 259
Aptamer Nanomedicine for Cancer Therapeutics: Barriers and Potential for Translation
Lao, Y.-H., Phua, K. K. L., & Leong, K. W. (2015) · ACS Nano · doi:10.1021/nn507494p · Cited by 259
Chen, Q., Chen, J., Liang, C., Feng, L., Dong, Z., Song, X., Song, G., & Liu, Z. (2017) · Journal of Controlled Release · doi:10.1016/j.jconrel.2016.11.006 · Cited by 188
Harnessing and Enhancing Macrophage Phagocytosis for Cancer Therapy
Chen, S., Lai, S. W. T., Brown, C. E., & Feng, M. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.635173 · Cited by 91
“Nanoparticles are an appealing therapeutic vehicle largely due to their physical characteristics and small size (105, 106).”
Background
Metadata
- Authors
- Tang, L., Gabrielson, N. P., Uckun, F. M., Fan, T. M., & Cheng, J.
- Venue
- Molecular Pharmaceutics
- Publisher
- American Chemical Society (ACS)
- Published
- 2013-02-12
- Volume
- 10
- Issue
- 3
- Pages
- 883-892
- ISSN
- 1543-8384 (ISSN-L)
- 1543-8392
- OpenAlex
- W2107481969
- Cited by
- 174
- References
- 8
- FWCI
- 5.87
- 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.
