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<p>This study aims to develop an efficient and accurate method for detecting human serum albumin (HSA) in urine using lateral flow immunochromatography analysis (LFIA) and a smartphone-based application (App). First, a LFIA test strip using colloidal gold as the labeling material was developed and optimized. A detecting accessory was designed and produced, including a strip kit that can package the LFIA test strip, and a test cartridge that can mount the smartphone on top of it. Then an App was constructed to automatically identify the concentration of HSA on the test strip using photos taken by smartphone. The detection limit of HSA by the proposed platform is 2&#xa0;µg/mL, and the quantitative range is 5 ~ 200&#xa0;µg/mL. The coefficient of variation is less than 18.3% and the accuracy is between 95.3% and 108.0%. Twenty urine samples from patients were tested for HSA by both the intelligent platform and ELISA. Results of the two methods showed good precision and accuracy, with a correlation coefficient of 0.9814. In conclusion, the LFIA strip for HSA is small, portable and low cost. By combining with intelligent analysis, it can be used for self-testing at home or monitoring in the clinic thereby realizing early diagnosis of HSA-related diseases.</p> Graphical abstract <p></p>

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An intelligent platform for monitoring human serum albumin in urine based on lateral flow immunochromatography

  • 期刊论文

  • 发表日期：

    2026年1月23日

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  • Jiayu Gu,
  • Hao Chen,
  • Dan Li,
  • Xiner Hu,
  • Zhenyu Zhou,
  • Xiaofei Wang,
  • Ningqi Xia,
  • Bin Lu,
  • Diya Lv,
  • Yan Cao

摘要

This study aims to develop an efficient and accurate method for detecting human serum albumin (HSA) in urine using lateral flow immunochromatography analysis (LFIA) and a smartphone-based application (App). First, a LFIA test strip using colloidal gold as the labeling material was developed and optimized. A detecting accessory was designed and produced, including a strip kit that can package the LFIA test strip, and a test cartridge that can mount the smartphone on top of it. Then an App was constructed to automatically identify the concentration of HSA on the test strip using photos taken by smartphone. The detection limit of HSA by the proposed platform is 2 µg/mL, and the quantitative range is 5 ~ 200 µg/mL. The coefficient of variation is less than 18.3% and the accuracy is between 95.3% and 108.0%. Twenty urine samples from patients were tested for HSA by both the intelligent platform and ELISA. Results of the two methods showed good precision and accuracy, with a correlation coefficient of 0.9814. In conclusion, the LFIA strip for HSA is small, portable and low cost. By combining with intelligent analysis, it can be used for self-testing at home or monitoring in the clinic thereby realizing early diagnosis of HSA-related diseases.

Graphical abstract