The DOI matches its Crossref record; 126 of the 126 references it cites were found in a registry or an index.
Quantum Dots for Live Cell and In Vivo Imaging
Open accessAbstract
In the past few decades, technology has made immeasurable strides to enable visualization, identification, and quantitation in biological systems. Many of these technological advancements are occurring on the nanometer scale, where multiple scientific disciplines are combining to create new materials with enhanced properties. The integration of inorganic synthetic methods with a size reduction to the nano-scale has lead to the creation of a new class of optical reporters, called quantum dots. These semiconductor quantum dot nanocrystals have emerged as an alternative to organic dyes and fluorescent proteins, and are brighter and more stable against photobleaching than standard fluorescent indicators. Quantum dots have tunable optical properties that have proved useful in a wide range of applications from multiplexed analysis such as DNA detection and cell sorting and tracking, to most recently demonstrating promise for in vivo imaging and diagnostics. This review provides an in-depth discussion of past, present, and future trends in quantum dot use with an emphasis on in vivo imaging and its related applications.
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Cited by
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Nanomaterials: Applications in Cancer Imaging and Therapy
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Biomass-Based Carbon Dots: Current Development and Future Perspectives
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Application of semiconductor quantum dots in bioimaging and biosensing
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Metadata
- Authors
- Walling, M. A., Novak, J. A., & Shepard, J. R. E.
- Venue
- International Journal of Molecular Sciences
- Publisher
- MDPI AG
- Published
- 2009-02-03
- Volume
- 10
- Issue
- 2
- Pages
- 441-491
- ISSN
- 1422-0067 (ISSN-L)
- OpenAlex
- W2090249020
- Cited by
- 511
- References
- 126
- FWCI
- 18.50
- Type
- journal article
- Language
- en
- Open access
- gold
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- Walling, M. A., Novak, J. A., & Shepard, J. R. E. (2009). Quantum Dots for Live Cell and In Vivo Imaging. International Journal of Molecular Sciences. https://doi.org/10.3390/ijms10020441
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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