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Gold Nanoparticles as a Direct and Rapid Sensor for Sensitive Analytical Detection of Biogenic Amines

Overview of attention for article published in Discover Nano, March 2017
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Title
Gold Nanoparticles as a Direct and Rapid Sensor for Sensitive Analytical Detection of Biogenic Amines
Published in
Discover Nano, March 2017
DOI 10.1186/s11671-017-2014-z
Pubmed ID
Authors

K. M. A. El-Nour, E. T. A. Salam, H. M. Soliman, A. S. Orabi

Abstract

A new optical sensor was developed for rapid screening with high sensitivity for the existence of biogenic amines (BAs) in poultry meat samples. Gold nanoparticles (GNPs) with particle size 11-19 nm function as a fast and sensitive biosensor for detection of histamine resulting from bacterial decarboxylation of histidine as a spoilage marker for stored poultry meat. Upon reaction with histamine, the red color of the GNPs converted into deep blue. The appearance of blue color favorably coincides with the concentration of BAs that can induce symptoms of poisoning. This biosensor enables a semi-quantitative detection of analyte in real samples by eye-vision. Quality evaluation is carried out by measuring histamine and histidine using different analytical techniques such as UV-vis, FTIR, and fluorescence spectroscopy as well as TEM. A rapid quantitative readout of samples by UV-vis and fluorescence methods with standard instrumentation were proposed in a short time unlike chromatographic and electrophoretic methods. Sensitivity and limit of detection (LOD) of 6.59 × 10(-4) and 0.6 μM, respectively, are determined for histamine as a spoilage marker with a correlation coefficient (R (2)) of 0.993.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 121 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 <1%
Unknown 120 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 20 17%
Student > Bachelor 14 12%
Student > Master 12 10%
Researcher 9 7%
Student > Doctoral Student 4 3%
Other 16 13%
Unknown 46 38%
Readers by discipline Count As %
Chemistry 20 17%
Engineering 9 7%
Agricultural and Biological Sciences 9 7%
Chemical Engineering 7 6%
Biochemistry, Genetics and Molecular Biology 6 5%
Other 16 13%
Unknown 54 45%