Submitted:
09 August 2025
Posted:
13 August 2025
You are already at the latest version
Abstract
Keywords:
1. Introduction
2. Nucleic Acid Aptamer
2.1. Nucleic Acid Aptamer
2.2. SELEX Technology
2.3. Separation of Target-Bonded and Non-Binding Aptamers
2.3.1. Capillary Electrophoresis SELEX Technology
2.3.2. Microfluidic SELEX Technology
2.3.3. Cell-SELEX Technology
3. Aptasensors
3.1. Aptasensors
3.2. Optical Aptasensors
3.2.1. Fluorescent Aptasensors
3.2.2. Colorimetric Aptasensors
3.2.3. Surface Plasmon Resonance Aptasensors
3.3. Field-Effect Transistor Aptasensors
3.4. Electrochemical Aptasensors
3.4.1. Electrochemical Impedance Spectroscopy Aptasensors
3.4.2. Voltammetric Aptasensors
3.4.3. Amperometric Aptasensors
4. Post-SELEX Optimization Process of Aptamers
4.1. Truncation
4.2. Other Post-SELEX Optimization Methods
5. Conclusion and Outlook
- (1)
- It is more difficult to screen aptamers for small molecule targets than for large ones. It is worthy of highlighting a new type of SELEX technology, named as Capture-SELEX, can be used in the field of screening aptamers for small molecule targets, despite that few SELEX technologies applied in this field [220].
- (2)
- Point-of-care (POC) diagnostic systems become more and more demanded in healthcare and clinical diagnosis, aptamer-based biosensing systems have proven their feasibility, but they are still in their infancy. There is still a significant gap in affordability, standardization and commercialization [221,222,223].
- (3)
- Wearable aptasensors are a brand-new field that combines flexible materials, artificial intelligence, machine learning and aptasensors, but it is still in its infancy at present. In the future, there are still huge challenges ahead in improving the consumption of wearable devices, collection of detection data and storage of wearable aptasensors under various physiological conditions and in complex external environments [224].
- (4)
- (5)
- The discovery of aptamers and their applications in sensing have become an interdisciplinary research field across physics, chemistry, biology, materials science and computer science, and several recent aptasensors designs have demonstrated that deep learning and predictive models can effectively enhance the performance of aptasensors while significantly shorten the discovery time of the aptamers as well as running costs [227,228,229,230,231,232,233]. In the future, the development and adoption of advanced predictive algorithms and computational tools are expected to play significant impact on the development of high-performance and low-cost aptasensors,
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