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Cited by 497

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

Magnetic nanoparticle drug delivery systems for targeting tumor

Open access
Mody, Vicky V., Cox, Arthur, Shah, Samit, Singh, Ajay, Bevins, Wesley, Parihar, Harish·2014·Applied Nanoscience

Abstract

Tumor hypoxia, or low oxygen concentration, is a result of disordered vasculature that lead to distinctive hypoxic microenvironments not found in normal tissues. Many traditional anti-cancer agents are not able to penetrate into these hypoxic zones, whereas, conventional cancer therapies that work by blocking cell division are not effective to treat tumors within hypoxic zones. Under these circumstances the use of magnetic nanoparticles as a drug delivering agent system under the influence of external magnetic field has received much attention, based on their simplicity, ease of preparation, and ability to tailor their properties for specific biological applications. Hence in this review article we have reviewed current magnetic drug delivery systems, along with their application and clinical status in the field of magnetic drug delivery.

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Crossref · 10.1007/s13204-013-0216-y

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Metadata

Authors
Mody, V. V., Cox, A., Shah, S., Singh, A., Bevins, W., & Parihar, H.
Venue
Applied Nanoscience
Published
2013-04-04
Volume
4
Issue
4
Pages
385-392
ISSN
  • 2190-5509 (ISSN-L)
  • 2190-5517
OpenAlex
W2016530312
Cited by
497
References
4
FWCI
8.75
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Magnetic nanoparticle drug delivery systems for targeting tumor. https://app.cochat.ai/papers/10.1007/s13204-013-0216-y
The paper
Mody, V. V., Cox, A., Shah, S., Singh, A., Bevins, W., & Parihar, H. (2014). Magnetic nanoparticle drug delivery systems for targeting tumor. Applied Nanoscience. https://doi.org/10.1007/s13204-013-0216-y

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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.