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Electrochemical aptasensors based on the gold nanostructures
1Nanomedicine and Nanobiology Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.
This review highlights gold nanostructure-based electrochemical aptasensors for disease diagnosis. These sensors show promise for detecting various analytes, including biomarkers and pathogens, advancing early disease detection.
Area of Science:
- Biomedical Sciences
- Nanotechnology
- Analytical Chemistry
Background:
- Electrochemical aptasensors are emerging diagnostic tools with significant research interest.
- Gold (Au) nanostructures offer unique properties for enhancing sensor performance.
Purpose of the Study:
- To review and compare recent trends in gold nanostructure-based electrochemical aptasensors.
- To categorize aptasensors based on analytes (pharmaceuticals, biomolecules, toxins, ions, hazardous chemicals, disease biomarkers, pathogens) and diagnostic techniques.
- To analyze key features including aptamer type, Au nanostructures, detection methods, and performance metrics.
Main Methods:
- Systematic review and comparative analysis of existing literature on gold nanostructure-based electrochemical aptasensors.
- Categorization of aptasensors by analyte type and detection methodology.
- Evaluation of sensor performance parameters: detection range and limit of detection (LOD).
Main Results:
- A comprehensive overview of aptasensors for diverse analytes, including pharmaceuticals, biomolecules, toxins, ions, hazardous chemicals, disease biomarkers, and pathogens.
- Discussion of various diagnostic techniques and mechanisms employed in these aptasensors.
- Analysis of the critical role of aptamer selection and gold nanostructure design in sensor efficacy.
Conclusions:
- Gold nanostructure-based electrochemical aptasensors are versatile tools for detecting a wide range of analytes.
- These aptasensors hold significant potential for early disease diagnosis and environmental monitoring.
- Further research and in-depth analysis of sensor features are crucial for optimizing diagnostic applications.
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