Single-Protein Determinations by Magnetofluorescent Qubit Imaging with Artificial-Intelligence Augmentation at the...

Area of Science:

• Quantum Metrology
• Nanotechnology
• Biosensing

Background:

• Conventional point-of-care testing (POCT) faces limitations in sensitivity, leading to missed detections and impacting early clinical diagnosis.
• Existing methods struggle with high risks of false positives and negatives, hindering routine outpatient care.

Purpose of the Study:

• To develop a highly sensitive mini quantum sensor for point-of-care testing (POCT) applications.
• To leverage quantum precision metrology and artificial intelligence (AI) for enhanced biosensing capabilities.

Main Methods:

• Fabrication of a core-shelled fluorescent nanodiamond (FND@SiO2) sensor with magnetofluorescent qubit tagging.
• Characterization using spectroscopy and parametrization for high modulation depth at near-zero magnetic field.
• AI-driven analysis using Unet-ConvLSTM-Attention architecture for qubit dot identification and signal processing.

Main Results:

• Achieved single-FND resolution and a wide-field modulation depth ≥15%.
• Demonstrated an ultralow limit of detection (LOD) for viral nucleocapsid protein, exceeding conventional methods by over 2000-fold.
• AI augmentation enabled deterministic detection of single proteins in human saliva with LOD 7800-times lower than colloidal gold, rivaling RT-qPCR and SIMOA.

Conclusions:

• The AI-aided quantum sensor offers unparalleled sensitivity, speed, and cost-effectiveness for next-generation POCT.
• This quantum metrology approach, enhanced by AI digitization, shows significant promise for advanced biosensing and clinical diagnostics.