Evidence map›Paper›PMID 35696869›Full record

ArticleBiosensors & bioelectronics2022

Artificial intelligence-assisted colorimetric lateral flow immunoassay for sensitive and quantitative detection of COVID-19 neutralizing antibody.

Haoyang Tong, Chaoyu Cao, Minli You, Shuang Han, Zhe Liu, Ying Xiao, Wanghong He, Chang Liu, Ping Peng, Zhenrui Xue and 3 more

Abstract read
In one paragraph

Article in Biosensors & bioelectronics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.

0numbers the graph read from it
0cells of the map it votes in
41citing 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

41 citing papers in PubMed.

  1. Review
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  3. [Nanomaterial-driven Lateral Flow Immunoassay: Technological Development and Application].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2026
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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

13 authors.

Haoyang TongThe Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, PR China; Bioinspired Engineering and Biomechanics Center (BEBC), Xi'an Jiaotong University, Xi'an, 710049, PR China.
Chaoyu CaoThe Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, PR China; Bioinspired Engineering and Biomechanics Center (BEBC), Xi'an Jiaotong University, Xi'an, 710049, PR China.
Minli YouThe Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, PR China; Bioinspired Engineering and Biomechanics Center (BEBC), Xi'an Jiaotong University, Xi'an, 710049, PR China. Electronic address: youminli@xjtu.edu.cn.
Shuang HanBioinspired Engineering and Biomechanics Center (BEBC), Xi'an Jiaotong University, Xi'an, 710049, PR China; Department of Gastroenterology of Honghui Hospital, Xi'an, 710054, PR China.
Zhe LiuThe Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, PR China; Bioinspired Engineering and Biomechanics Center (BEBC), Xi'an Jiaotong University, Xi'an, 710049, PR China; Department of Rehabilitation Medicine, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, PR China.
Ying XiaoClinical Laboratory, Xi'an Jiaotong University School Hospital, Xi'an, 710061, PR China.
Wanghong HeBioinspired Engineering and Biomechanics Center (BEBC), Xi'an Jiaotong University, Xi'an, 710049, PR China; Key Laboratory of Shaanxi Province for Craniofacial Precision Medicine Research, College of Stomatology, Xi'an Jiaotong University, Xi'an, 710049, PR China.
Chang LiuThe Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, PR China; Bioinspired Engineering and Biomechanics Center (BEBC), Xi'an Jiaotong University, Xi'an, 710049, PR China.
Ping PengBioinspired Engineering and Biomechanics Center (BEBC), Xi'an Jiaotong University, Xi'an, 710049, PR China; Department of Transfusion Medicine, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, 400038, PR China.
Zhenrui XueBioinspired Engineering and Biomechanics Center (BEBC), Xi'an Jiaotong University, Xi'an, 710049, PR China; Department of Transfusion Medicine, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, 400038, PR China.
Yan GongDiyinan Biotech Company, Suzhou, 215000, PR China.
Chunyan YaoBioinspired Engineering and Biomechanics Center (BEBC), Xi'an Jiaotong University, Xi'an, 710049, PR China; Department of Transfusion Medicine, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, 400038, PR China.
Feng XuThe Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, PR China; Bioinspired Engineering and Biomechanics Center (BEBC), Xi'an Jiaotong University, Xi'an, 710049, PR China. Electronic address: fengxu@mail.xjtu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Currently, vaccination is the most effective medical measure to improve group immunity and prevent the rapid spread of COVID-19. Since the individual difference of vaccine effectiveness is inevitable, it is necessary to evaluate the vaccine effectiveness of every vaccinated person to ensure the appearance of herd immunity. Here, we developed an artificial intelligent (AI)-assisted colorimetric polydopamine nanoparticle (PDA)-based lateral flow immunoassay (LFIA) platform for the sensitive and accurate quantification of neutralizing antibodies produced from vaccinations. The platform integrates PDA-based LFIA and a smartphone-based reader to test the neutralizing antibodies in serum, where an AI algorithm is also developed to accurately and quantitatively analyze the results. The developed platform achieved a quantitative detection with 160 ng/mL of detection limit and 625-10000 ng/mL of detection range. Moreover, it also successfully detected totally 50 clinical serum samples, revealing a great consistency with the commercial ELISA kit. Comparing with commercial gold nanoparticle-based LFIA, our PDA-based LFIA platform showed more accurate quantification ability for the clinical serum. Therefore, we envision that the AI-assisted PDA-based LFIA platform with sensitive and accurate quantification ability is of great significance for large-scale evaluation of vaccine effectiveness and other point-of-care immunoassays.

Indexed as

Biosensing TechniquesCOVID-19Metal NanoparticlesAntibodies, NeutralizingArtificial IntelligenceColorimetryGoldHumansImmunoassayLimit of DetectionAntibodies, NeutralizingGoldArtificial intelligenceCOVID-19Lateral flow immunoassayNeutralizing antibodyPolydopamine

Identifiers

PMID35696869
PMCPMC9174064

What OpenQuestion holds

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Registered trials

None linked

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.