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Related Concept Videos

Atomic Force Microscopy01:08

Atomic Force Microscopy

Atomic force microscopy (AFM) is a type of scanning probe microscopy that can analyze topographic details of various specimens like ceramics, glass, polymers, and biological samples. AFM offers over 1000 times more resolution than the optical imaging system. Images generated from AFM are three-dimensional surface profiles, offering an advantage over the flat, two-dimensional images from other imaging techniques.
The AFM Probe
The probe is regarded as the heart of any AFM setup and comprises the...

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Design and Assembly of an Ultra-light Motorized Microdrive for Chronic Neural Recordings in Small Animals
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Precise Artificial Intelligence Nanomotor Tracking-Powered Amplification-Free Digital MicroRNA Sensing.

Jingjing Shi1, Zuhua Yu2, Hui Tian2

  • 1Key Laboratory of Applied Surface and Colloid Chemistry, Ministry of Education, Key Laboratory of Analytical Chemistry for Life Science of Shaanxi Province, School of Chemistry & Chemical Engineering, Shaanxi Normal University, Xi'an, Shaanxi Province 710119, P. R. China.

Analytical Chemistry
|April 17, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces an AI-powered digital assay for sensitive microRNA detection without amplification. This novel method uses fluorescent nanomotors for real-time sensing in open systems, advancing nucleic acid analysis.

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Area of Science:

  • Biotechnology
  • Nanotechnology
  • Molecular Diagnostics

Background:

  • Digital nucleic acid assays are state-of-the-art but often require sealed microchambers and amplification.
  • Existing methods face limitations in complexity and sensitivity for certain applications.

Purpose of the Study:

  • To develop a novel, amplification-free digital assay for sensitive microRNA detection.
  • To leverage artificial intelligence (AI) and nanomotor tracking for real-time sensing.

Main Methods:

  • Developed an AI-facilitated digital fluorescence nanomotor tracking-powered assay (AI-dFNA).
  • Utilized single target miRNA-templated, amplification-free ligation to drive fluorescent nanoparticles.
  • Employed a self-developed AI algorithm for nanomotor motion analysis and signal discrimination.

Main Results:

  • Achieved highly sensitive, one-step detection of microRNAs.
  • Demonstrated real-time digital sensing without enclosed microchambers or amplification.
  • Showcased the ability to differentiate varying fluorescence colors for multiplexed miRNA analysis.

Conclusions:

  • AI-dFNA offers a simplified, amplification-free approach for digital nucleic acid sensing.
  • This technology enables sensitive and real-time detection of microRNAs.
  • Pioneers a new direction for next-generation digital nucleic acid sensing platforms.