The DOI matches its Crossref record; 306 of the 306 references it cites were found in a registry or an index.
Nanoparticle-Based Delivery Systems for Vaccines
Open accessAbstract
Vaccination is still the most cost-effective way to combat infectious illnesses. Conventional vaccinations may have low immunogenicity and, in most situations, only provide partial protection. A new class of nanoparticle-based vaccinations has shown considerable promise in addressing the majority of the shortcomings of traditional and subunit vaccines. This is due to recent breakthroughs in chemical and biological engineering, which allow for the exact regulation of nanoparticle size, shape, functionality, and surface characteristics, resulting in improved antigen presentation and robust immunogenicity. A blend of physicochemical, immunological, and toxicological experiments can be used to accurately characterize nanovaccines. This narrative review will provide an overview of the current scenario of the nanovaccine.
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Cites
1 retracted
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RetractedToxic potential of materials at the nanolevel
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Nanoparticle therapeutics: an emerging treatment modality for cancer
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Lipid nanoparticles for mRNA delivery
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Long-Circulating and Target-Specific Nanoparticles: Theory to Practice
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Metadata
- Authors
- Bezbaruah, R., Chavda, V. P., Nongrang, L., Alom, S., Deka, K., Kalita, T., Ali, F., Bhattacharjee, B., & Vora, L.
- Venue
- Vaccines
- Publisher
- MDPI AG
- Published
- 2022-11-17
- Volume
- 10
- Issue
- 11
- Pages
- 1946
- ISSN
- 2076-393X (ISSN-L)
- OpenAlex
- W4309284761
- Cited by
- 253
- References
- 306
- FWCI
- 15.83
- Type
- journal article
- Language
- en
- Open access
- gold
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- Bezbaruah, R., Chavda, V. P., Nongrang, L., Alom, S., Deka, K., Kalita, T., Ali, F., Bhattacharjee, B., & Vora, L. (2022). Nanoparticle-Based Delivery Systems for Vaccines. Vaccines. https://doi.org/10.3390/vaccines10111946
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.