Multiple recognition elements in biosensors: A review of antibiotic detection technologies

Area of Science:

• Environmental Science
• Analytical Chemistry
• Biotechnology

Background:

• Antibiotics are crucial for disease treatment but irrational use causes environmental pollution and health risks.
• Traditional antibiotic detection methods are costly, complex, and time-consuming.
• There is a critical need for rapid, sensitive, and field-deployable antibiotic detection technologies.

Purpose of the Study:

• To systematically review biosensor applications for antibiotic detection.
• To discuss the working principles of biosensors utilizing various recognition elements.
• To explore the integration of signal amplification and artificial intelligence in biosensor technology.

Main Methods:

• Review of biosensor principles based on enzymes, antibodies, cells, and aptamers.
• Analysis of signal amplification technologies and artificial intelligence in biosensor optimization.
• Evaluation of practical challenges and limitations of current biosensor approaches.

Main Results:

• Biosensors provide a cost-effective, sensitive, and accurate alternative for antibiotic detection.
• Signal amplification and AI enhance biosensor performance and data processing capabilities.
• Different recognition elements offer diverse advantages and disadvantages for specific antibiotic targets.

Conclusions:

• Biosensors are powerful tools for addressing the challenges of antibiotic detection in environmental and food safety.
• Integrating advanced technologies like AI and signal amplification is key to future biosensor development.
• Further research is needed to overcome practical challenges and optimize biosensor integration for widespread application.