The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Engineered Hybrid Nanoparticles for On-Demand Diagnostics and Therapeutics
Open accessAbstract
Together with the simultaneous development of nanomaterials and molecular biology, the bionano interface brings about various applications of hybrid nanoparticles in nanomedicine. The hybrid nanoparticles not only present properties of the individual components but also show synergistic effects for specialized applications. Thus, the development of advanced hybrid nanoparticles for targeted and on-demand diagnostics and therapeutics of diseases has rapidly become a hot research topic in nanomedicine. The research focus is to fabricate novel classes of programmable hybrid nanoparticles that are precisely engineered to maximize drug concentrations in diseased cells, leading to enhanced efficacy and reduced side effects of chemotherapy for the disease treatment. In particular, the hybrid nanoparticle platforms can simultaneously target diseased cells, enable the location to be imaged by optical methods, and release therapeutic drugs to the diseased cells by command. This Account specially discusses the rational fabrication of integrated hybrid nanoparticles and their applications in diagnostics and therapeutics. For diagnostics applications, hybrid nanoparticles can be utilized as imaging agents that enable detailed visualization at the molecular level. By the use of suitable targeting ligands incorporated on the nanoparticles, targeted optical imaging may be feasible with improved performance. Novel imaging techniques such as multiphoton excitation and photoacoustic imaging using near-infrared light have been developed using the intrinsic properties of particular nanoparticles. The use of longer-wavelength excitation sources allows deeper penetration into the human body for disease diagnostics and at the same time reduces the adverse effects on normal tissues. Furthermore, multimodal imaging techniques have been achieved by combining several types of components in nanoparticles, offering higher accuracy and better spatial views, with the aim of detecting life-threatening diseases before symptoms appear. For therapeutics applications, various nanoparticle-based treatment methods such as photodynamic therapy, drug delivery, and gene delivery have been developed. The intrinsic ability of organic nanoparticles to generate reactive oxygen species has been utilized for photodynamic therapy, and mesoporous silica nanoparticles have been widely used for drug loading and controlled delivery. Herein, the development of controlled-release systems that can specifically deliver drug molecules to target cells and release then upon triggering is highlighted. By control of the release of loaded drug molecules at precise sites (e.g., cancer cells or malignant tumors), side effects of the drugs are minimized. This approach provides better control and higher efficacy of drugs in the human body. Future personalized medicine is also feasible through gene delivery methods. Specific DNA/RNA-carrying nanoparticles are able to deliver them to target cells to obtain desired properties. This development may create an evolution in current medicine, leading to more personalized healthcare systems that can reduce the population screening process and also the duration of drug evaluation. Furthermore, nanoparticles can be incorporated with various components that can be used for simultaneous diagnostics and therapeutics. These multifunctional theranostic nanoparticles enable real-time monitoring of treatment process for more efficient 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
Cited by
Dai, Y., Xu, C., Sun, X., & Chen, X. (2017) · Chemical Society Reviews · doi:10.1039/c6cs00592f · Cited by 931
Zhou, J., Yu, G., & Huang, F. (2017) · Chemical Society Reviews · doi:10.1039/c6cs00898d · Cited by 677
Versatile Types of Organic/Inorganic Nanohybrids: From Strategic Design to Biomedical Applications
Zhao, N., Yan, L., Zhao, X., Chen, X., Li, A., Zheng, D., Zhou, X., Dai, X., & Xu, F.-J. (2019) · Chemical Reviews · doi:10.1021/acs.chemrev.8b00401 · Cited by 429
Liu, B., Li, C., Chen, G., Liu, B., Deng, X., Wei, Y., Xia, J., Xing, B., Ma, P., & Lin, J. (2017) · Advanced Science · doi:10.1002/advs.201600540 · Cited by 316
RetractedDong, Z., Feng, L., Zhu, W., Sun, X., Gao, M., Zhao, H., Chao, Y., & Liu, Z. (2016) · Biomaterials · doi:10.1016/j.biomaterials.2016.09.025 · Cited by 284
Metadata
- Authors
- Nguyen, K. T., & Zhao, Y.
- Venue
- Accounts of Chemical Research
- Publisher
- American Chemical Society (ACS)
- Published
- 2015-11-25
- Volume
- 48
- Issue
- 12
- Pages
- 3016-3025
- ISSN
- 0001-4842 (ISSN-L)
- 1520-4898
- OpenAlex
- W2228430403
- Cited by
- 165
- References
- 1
- FWCI
- 10.69
- 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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Engineered Hybrid Nanoparticles for On-Demand Diagnostics and Therapeutics. https://app.cochat.ai/papers/10.1021/acs.accounts.5b00316
- The paper
- Nguyen, K. T., & Zhao, Y. (2015). Engineered Hybrid Nanoparticles for On-Demand Diagnostics and Therapeutics. Accounts of Chemical Research. https://doi.org/10.1021/acs.accounts.5b00316
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.