LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Ultrasensitive miRNA-21 Biosensor Based on Zn(TCPP) PET-RAFT Polymerization Signal Amplification and Multiple Logic Gate Molecular Recognition.

Photo by jonasvincentbe from unsplash

Quantitative measurement of microRNAs (miRNAs) is extremely important in plenty of biomedical applications especially cancer diagnosis but remains a great challenge. In this work, we developed a logic gate recognition… Click to show full abstract

Quantitative measurement of microRNAs (miRNAs) is extremely important in plenty of biomedical applications especially cancer diagnosis but remains a great challenge. In this work, we developed a logic gate recognition biosensing platform based on the "trinity" molecular recognition mode for quantifying miRNAs with a detection limit of 4.48 aM, along with a linear range from 0.1 nM to 10 aM under optimal experimental conditions. In order to obtain excellent detection performance, we adopted a Zn(TCPP) photocatalytic electron transfer reversible addition-fragmentation chain transfer (PET-RAFT) polymerization signal amplification strategy. The light-induced PET-RAFT has developed green applications of free radical polymerization in the field of biosensors. This is the first report on the preparation of signal amplification biosensors using PET-RAFT for tumor marker detection. With the outstanding detection performance, we can apply the sensor system to the early screening of lung cancer patients.

Keywords: recognition; pet raft; signal amplification; raft; polymerization

Journal Title: ACS applied materials & interfaces
Year Published: 2023

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.