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Cited by 378

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Complementary Detection of Prostate-Specific Antigen Using In2O3 Nanowires and Carbon Nanotubes

Li, Chao, Curreli, Marco, Lin, Henry, Lei, Bo, Ishikawa, F. N., Datar, Ram, Cote, Richard J., Thompson, Mark E., Zhou, Chongwu·2005·Journal of the American Chemical Society

Abstract

We report complementary detection of prostate-specific antigen (PSA) using n-type In2O3 nanowires and p-type carbon nanotubes. Our innovation involves developing an approach to covalently attach antibodies to In2O3 NW surfaces via the onsite surface synthesis of phosphonic acid-succinylimide ester. Electronic measurements under dry conditions revealed complementary response for In2O3 NW and SWNT devices after the binding of PSA. Real-time detection in solution has also been demonstrated for PSA down to 5 ng/mL, a benchmark concentration significant for clinical diagnosis of prostate cancer, which is the most frequently diagnosed cancer.

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Metadata

Authors
Li, C., Curreli, M., Lin, H., Lei, B., Ishikawa, F. N., Datar, R., Cote, R. J., Thompson, M. E., & Zhou, C.
Venue
Journal of the American Chemical Society
Published
2005-08-19
Volume
127
Issue
36
Pages
12484-12485
ISSN
  • 0002-7863 (ISSN-L)
  • 1520-5126
OpenAlex
W2324358220
Cited by
378
References
1
FWCI
15.90
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Complementary Detection of Prostate-Specific Antigen Using In2O3 Nanowires and Carbon Nanotubes. https://app.cochat.ai/papers/10.1021/ja053761g
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Li, C., Curreli, M., Lin, H., Lei, B., Ishikawa, F. N., Datar, R., Cote, R. J., Thompson, M. E., & Zhou, C. (2005). Complementary Detection of Prostate-Specific Antigen Using In2O3 Nanowires and Carbon Nanotubes. Journal of the American Chemical Society. https://doi.org/10.1021/ja053761g

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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.