Evidence map›Paper›PMID 41577847›Full record

ArticleMikrochimica acta2026

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

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

Abstract read
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In one paragraph

Article in Mikrochimica acta, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Jiayu Gu *School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China.
Hao Chen *College of Pharmacy, Naval Medical University, Shanghai, 200433, China.
Dan LiEastern Hepatobiliary Surgery Hospital, Naval Medical University, Shanghai, 200433, China.
Xiner HuShanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, 200092, China.
Zhenyu ZhouShanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, 200092, China.
Xiaofei WangCollege of Pharmacy, Naval Medical University, Shanghai, 200433, China.
Ningqi XiaCollege of Pharmacy, Naval Medical University, Shanghai, 200433, China.
Bin LuCollege of Pharmacy, Naval Medical University, Shanghai, 200433, China.
Diya LvCollege of Pharmacy, Naval Medical University, Shanghai, 200433, China. lvdy2020@163.com.
Yan CaoSchool of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China. caoyan@smmu.edu.cn.

Funding

National Natural Science Foundation of China 82174092National Natural Science Foundation of China 82473892National Natural Science Foundation of Shanghai 21ZR1483000National Natural Science Foundation of Shanghai 22ZR1476900
6 · The paper itself

Abstract

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.

Indexed as

Chromatography, AffinitySerum Albumin, HumanGold ColloidHumansLimit of DetectionReagent StripsSmartphoneGold ColloidReagent StripsSerum Albumin, HumanColloidal goldHuman serum albuminIntelligent detectionLateral flow immunochromatography; Test stripSmartphone-based detection application

Identifiers

PMID41577847

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.