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New generation of electrochemical immunoassay based on polymeric nanoparticles for early detection of breast cancer

Overview of attention for article published in International Journal of Nanomedicine, April 2017
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34 Mendeley
Title
New generation of electrochemical immunoassay based on polymeric nanoparticles for early detection of breast cancer
Published in
International Journal of Nanomedicine, April 2017
DOI 10.2147/ijn.s127086
Pubmed ID
Authors

Fouzi Mouffouk, Sihem Aouabdi, Entesar Al-Hetlani, Hacene Serrai, Tareq Alrefae, Liaohai Leo Chen

Abstract

Screening and early diagnosis are the key factors for the reduction of mortality rate and treatment cost of cancer. Therefore, sensitive and selective methods that can reveal the low abundance of cancer biomarkers in a biological sample are always desired. Here, we report the development of a novel electrochemical biosensor for early detection of breast cancer by using bioconjugated self-assembled pH-responsive polymeric micelles. The micelles were loaded with ferrocene molecules as "tracers" to specifically target cell surface-associated epithelial mucin (MUC1), a biomarker for breast and other solid carcinoma. The synthesis of target-specific, ferrocene-loaded polymeric micelles was confirmed, and the resulting sensor was capable of detecting the presence of MUC1 in a sample containing about 10 cells/mL. Such a high sensitivity was achieved by maximizing the loading capacity of ferrocene inside the polymeric micelles. Every single event of binding between the antibody and antigen was represented by the signal of hundreds of thousands of ferrocene molecules that were released from the polymeric micelles. This resulted in a significant increase in the intensity of the ferrocene signal detected by cyclic voltammetry.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 34 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 5 15%
Student > Doctoral Student 3 9%
Student > Bachelor 3 9%
Lecturer > Senior Lecturer 2 6%
Researcher 2 6%
Other 3 9%
Unknown 16 47%
Readers by discipline Count As %
Chemistry 5 15%
Engineering 4 12%
Biochemistry, Genetics and Molecular Biology 2 6%
Business, Management and Accounting 1 3%
Earth and Planetary Sciences 1 3%
Other 3 9%
Unknown 18 53%