Evidence map›Paper›PMID 39337259›Full record

ArticleInternational journal of molecular sciences2024

A Visual Distance-Based Capillary Immunoassay Using Biomimetic Polymer Nanoparticles for Highly Sensitive and Specific C-Reactive Protein Quantification.

Ruodong Huang, Zhenbo Liu, Xinlin Jiang, Junqi Huang, Ping Zhou, Zongxia Mou, Dong Ma, Xin Cui

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2024. 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

8 authors.

Ruodong HuangKey Laboratory of Biomaterials of Guangdong Higher Education Institutes, Department of Biomedical Engineering, Jinan University, Guangzhou 5106https://susy.mdpi.com/manuscript/publishing/publish/5920461659f317d0555d60b6dae83b56#academic-editor-info32, China.
Zhenbo LiuKey Laboratory of Biomaterials of Guangdong Higher Education Institutes, Department of Biomedical Engineering, Jinan University, Guangzhou 5106https://susy.mdpi.com/manuscript/publishing/publish/5920461659f317d0555d60b6dae83b56#academic-editor-info32, China.
Xinlin JiangKey Laboratory of Biomaterials of Guangdong Higher Education Institutes, Department of Biomedical Engineering, Jinan University, Guangzhou 5106https://susy.mdpi.com/manuscript/publishing/publish/5920461659f317d0555d60b6dae83b56#academic-editor-info32, China.
Junqi HuangKey Laboratory of Biomaterials of Guangdong Higher Education Institutes, Department of Biomedical Engineering, Jinan University, Guangzhou 5106https://susy.mdpi.com/manuscript/publishing/publish/5920461659f317d0555d60b6dae83b56#academic-editor-info32, China.
Ping ZhouKey Laboratory of Biomaterials of Guangdong Higher Education Institutes, Department of Biomedical Engineering, Jinan University, Guangzhou 5106https://susy.mdpi.com/manuscript/publishing/publish/5920461659f317d0555d60b6dae83b56#academic-editor-info32, China.ORCID 0000-0002-2532-0954
Zongxia MouKey Laboratory of Biomaterials of Guangdong Higher Education Institutes, Department of Biomedical Engineering, Jinan University, Guangzhou 5106https://susy.mdpi.com/manuscript/publishing/publish/5920461659f317d0555d60b6dae83b56#academic-editor-info32, China.
Dong MaKey Laboratory of Biomaterials of Guangdong Higher Education Institutes, Department of Biomedical Engineering, Jinan University, Guangzhou 5106https://susy.mdpi.com/manuscript/publishing/publish/5920461659f317d0555d60b6dae83b56#academic-editor-info32, China.ORCID 0000-0002-1814-7348
Xin CuiKey Laboratory of Biomaterials of Guangdong Higher Education Institutes, Department of Biomedical Engineering, Jinan University, Guangzhou 5106https://susy.mdpi.com/manuscript/publishing/publish/5920461659f317d0555d60b6dae83b56#academic-editor-info32, China.ORCID 0000-0001-8371-353X

Funding

National Natural Science Foundation of China 32301244Natural Science Foundation of Guangdong Province 2021A1515011167, 2020A1515010332Science and Technology Program of Guangzhou 202102020840the Fundamental Research Funds for the Central Universities NA
6 · The paper itself

Abstract

The low-cost daily monitoring of C-reactive protein (CRP) levels is crucial for screening acute inflammation or infections as well as managing chronic inflammatory diseases. In this study, we synthesized novel 2-Methacryloyloxy ethyl phosphorylcholine (MPC)-based biomimetic nanoparticles with a large surface area to develop a visual CRP-quantification assay using affordable glass capillaries. The PMPC nanoparticles, synthesized via reflux precipitation polymerization, demonstrated multivalent binding capabilities, enabling rapid and specific CRP capture. In the presence of CRP, PMPC nanoparticles formed sandwich structures with magnetic nanoparticles functionalized with CRP antibodies, thereby enhancing detection sensitivity and specificity. These sandwich complexes were magnetically accumulated into visible and quantifiable stacks within the glass capillaries, allowing for the rapid, sensitive, and specific quantification of CRP concentrations with a detection limit of 57.5 pg/mL and a range spanning from 0 to 5000 ng/mL. The proposed visual distance-based capillary biosensor shows great potential in routine clinical diagnosis as well as point-of-care testing (POCT) in resource-limited settings.

Indexed as

C-Reactive ProteinNanoparticlesPolymersBiomimetic MaterialsBiosensing TechniquesHumansImmunoassayLimit of DetectionPhosphorylcholineC-Reactive ProteinPhosphorylcholinePolymersbiomimetic nanoparticlesC-reactive proteindistance-based immunoassayspecificity

Identifiers

PMID39337259
PMCPMC11431823

What OpenQuestion holds

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LicenceCC BY
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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.