High-precision Helicobacter pylori infection diagnosis using a dual-element multimodal gas sensor array

Area of Science:

• Materials Science
• Biomedical Engineering
• Analytical Chemistry

Background:

• Helicobacter pylori infection is a global health concern requiring early diagnosis.
• Current diagnostic methods like urea breath tests (UBT) are inconvenient and potentially harmful.
• Existing gas sensor arrays (GSAs) for exhaled breath analysis lack reliability and sensitivity.

Purpose of the Study:

• To develop a novel dual-element multimodal gas sensor array (GSA) for improved H. pylori infection diagnosis.
• To enhance gas recognition and discrimination capabilities using multiple sensing signals.
• To establish a non-invasive, label-free diagnostic method for H. pylori.

Main Methods:

• Fabrication of dual-element graphene oxide (GO)-composite GSAs sensitized with PDDA and NH2-UiO66.
• Utilizing multimodal sensing signals: conductance (G), capacitance (C), and dissipation factor (DF).
• Testing sensor performance with standard gases and clinical exhaled breath (EB) samples.

Main Results:

• The developed GSA demonstrated high sensitivity, repeatability, and fast response/recovery across G, C, and DF signals.
• Multimodal sensing enabled detection of gas analyte physicochemical properties, enhancing discrimination.
• The GSA successfully differentiated standard gases and non-dehumidified EB samples.
• A clinical study on 52 EB samples yielded 94.1% accuracy, 100% sensitivity, and 90.9% specificity for H. pylori diagnosis.

Conclusions:

• The dual-element multimodal GSA offers a robust platform for sensitive and specific gas detection.
• This technology provides a promising non-invasive, label-free strategy for accurate H. pylori infection diagnosis.
• The multimodal sensing approach significantly improves upon conventional GSA limitations.