Smartphone-Based Quantitative Analysis of Protein Array Signals for Biomarker Detection in Lupus

Guang Yang, Yaxi Li, Chenling Tang, Feng Lin, Tianfu Wu, Jiming Bao

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Fluorescence-based microarray offers great potential in clinical diagnostics due to its high-throughput capability, multiplex capabilities, and requirement for a minimal volume of precious clinical samples. However, the technique relies on expensive and complex imaging systems for the analysis of signals. In the present study, we developed a smartphone-based application to analyze signals from protein microarrays to quantify disease biomarkers. The application adopted Android Studio open platform for its wide access to smartphones, and Python was used to design a graphical user interface with fast data processing. The application provides multiple user functions such as “Read”, “Analyze”, “Calculate” and “Report”. For rapid and accurate results, we used ImageJ, Otsu thresholding, and local thresholding to quantify the fluorescent intensity of spots on the microarray. To verify the efficacy of the application, three antigens each with over 110 fluorescent spots were tested. Particularly, a positive correlation of over 0.97 was achieved when using this analytical tool compared to a standard test for detecting a potential biomarker in lupus nephritis. Collectively, this smartphone application tool shows promise for cheap, efficient, and portable on-site detection in point-of-care diagnostics.

Original languageEnglish (US)
Article number330
JournalChemosensors
Volume10
Issue number8
DOIs
StatePublished - Aug 2022
Externally publishedYes

Keywords

  • biomarker
  • clinical diagnostics
  • fluorescent microarray
  • image processing
  • smartphone application

ASJC Scopus subject areas

  • Analytical Chemistry
  • Physical and Theoretical Chemistry

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