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Author Spotlight: Engineering Molecular Tools for Disease Detection and Imaging

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Published on: December 8, 2023

Engineering an integrated biosensing interface combining DNA-assisted clustering and explainable AI for biomarker

Haoze Chen¹, Zhenyun He², Zhichang Sun¹

¹School of Food Science and Engineering, Hainan University, Haikou, 570228, China.

Biosensors & Bioelectronics

|May 2, 2026

Summary

This study introduces an integrated biosensing framework for reliable point-of-care testing (POCT). It combines nanobody probes, DNA-assisted signal amplification, and AI for accurate biomarker detection in complex samples.

Keywords:

Biomarkers DNA-Assisted clustering Explainable AI Nanobody Point-of-care testing

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Published on: June 1, 2011

Area of Science:

Biomedical Engineering
Biosensing Technology
Artificial Intelligence in Diagnostics

Background:

Point-of-care testing (POCT) faces challenges in reliable signal readout within complex clinical samples.
Existing molecular amplification methods often struggle with consistency in real-world biological matrices.

Purpose of the Study:

To develop an integrated biosensing framework prioritizing readout reliability as a core engineering goal.
To create a generalizable strategy for trustworthy POCT systems by co-designing sensing and interpretation.

Main Methods:

Utilized a heptameric nanobody probe for multivalent target capture.
Employed a DNA-assisted clustering interface for gold nanoparticle reporter amplification.
Integrated a few-shot learning module (Prototypical Networks) for robust, interpretable classification.

Main Results:

Achieved a visual limit of detection of 2 ng/mL for alpha-fetoprotein.
Demonstrated quantitative consistency across diverse clinical serum samples.
The AI module effectively mitigated matrix effects and imaging variability for reliable readout.

Conclusions:

The integrated framework successfully addresses POCT readout reliability challenges.
This co-design approach of sensing and interpretation offers a generalizable strategy for trustworthy diagnostic platforms.
The system shows promise for clinical applications like hepatocellular carcinoma screening.