The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index.
Innovative Nanosensor for Disease Diagnosis
Abstract
As a futuristic diagnosis platform, breath analysis is gaining much attention because it is a noninvasive, simple, and low cost diagnostic method. Very promising clinical applications have been demonstrated for diagnostic purposes by correlation analysis between exhaled breath components and specific diseases. In addition, diverse breath molecules, which serve as biomarkers for specific diseases, are precisely identified by statistical pattern recognition studies. To further improve the accuracy of breath analysis as a diagnostic tool, breath sampling, biomarker sensing, and data analysis should be optimized. In particular, development of high performance breath sensors, which can detect biomarkers at the ppb-level in exhaled breath, is one of the most critical challenges. Due to the presence of numerous interfering gas species in exhaled breath, selective detection of specific biomarkers is also important. This Account focuses on chemiresistive type breath sensors with exceptionally high sensitivity and selectivity that were developed by combining hollow protein templated nanocatalysts with electrospun metal oxide nanostructures. Nanostructures with high surface areas are advantageous in achieving high sensitivity because the sensing signal is dominated by the surface reaction between the sensing layers and the target biomarkers. Furthermore, macroscale pores between one-dimensional (1D) nanostructures can facilitate fast gas diffusion into the sensing layers. To further enhance the selectivity, catalytic functionalization of the 1D metal oxide nanostructure is essential. However, the majority of conventional techniques for catalytic functionalization have failed to achieve a high degree of dispersion of nanoscale catalysts due to aggregation on the surface of the metal oxide, which severely deteriorates the sensing properties by lowering catalytic activity. This issue has led to extensive studies on monolithically dispersed nanoscale particles on metal oxides to maximize the catalytic performances. As a pioneering technique, a bioinspired templating route using apoferritin, that is, a hollow protein cage, has been proposed to obtain nanoscale (∼2 nm) catalyst particles with high dispersity. Nanocatalysts encapsulated by a protein shell were first used in chemiresistive type breath sensors for catalyst functionalization on 1D metal oxide structures. We discuss the robustness and versatility of the apoferrtin templating route for creating highly dispersive catalytic NPs including single components (Au, Pt, Pd, Rh, Ag, Ru, Cu, and La) and bimetallic catalysts (PtY and PtCo), as well as the core-shell structure of Au-Pd (Au-core@Pd-shell). The use of these catalysts is essential to establish high performance sensors arrays for the pattern recognition of biomarkers. In addition, novel multicomponent catalysts provide unprecedented sensitivity and selectivity. With this in mind, we discuss diverse synthetic routes for nanocatalysts using apoferritin and the formation of various catalyst-1D metal oxide composite nanostructures. Furthermore, we discuss detection capability of a simulated biomarker gas using the breath sensor arrays and principal component analysis. Finally, future prospects with the portable breath analysis platform are presented by demonstrating the potential feasibility of real-time and on-site breath analysis using chemiresistive sensors.
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Prospects and Challenges of Volatile Organic Compound Sensors in Human Healthcare
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Smart Gas Sensors: Recent Developments and Future Prospective
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Metadata
- Authors
- Kim, S.-J., Choi, S.-J., Jang, J.-S., Cho, H.-J., & Kim, I.-D.
- Venue
- Accounts of Chemical Research
- Publisher
- American Chemical Society (ACS)
- Published
- 2017-05-08
- Volume
- 50
- Issue
- 7
- Pages
- 1587-1596
- ISSN
- 0001-4842 (ISSN-L)
- 1520-4898
- OpenAlex
- W2612497745
- Cited by
- 264
- References
- 32
- FWCI
- 11.97
- Type
- journal article
- Language
- en
- Open access
- closed
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