An Enhanced Bimetallic Optical Fiber SPR Biosensor Using Graphene Oxide for the Label-Free and Sensitive Detection of Human IgG.

Qiang Xu, Huiting Yin, Mei Cui, Renliang Huang, Rongxin Su

Abstract read

In one paragraph

Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing 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

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

Nanomaterial-Enabled Fiber-Optic SPR Biosensor for Continuous and Noninvasive Body Fluid Monitoring:Progress and Prospects.Nanomaterials (Basel, Switzerland) · 2026
Review
High-sensitivity U-shaped biosensor for rabbit IgG detection based on PDA/AuNPs/PDA sandwich structure.Nanophotonics (Berlin, Germany) · 2025
Article

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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

5 authors.

Qiang XuTianjin Key Laboratory for Marine Environmental Research and Service, School of Marine Science and Technology, Tianjin University, Tianjin 300072, China.

Huiting YinNingbo Key Laboratory of Green Petrochemical Carbon Emission Reduction Technology and Equipment, Zhejiang Institute of Tianjin University, Ningbo 315201, China.

Mei CuiState Key Laboratory of Chemical Engineering, Tianjin Key Laboratory of Membrane Science and Desalination Technology, School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China.

Renliang HuangTianjin Key Laboratory for Marine Environmental Research and Service, School of Marine Science and Technology, Tianjin University, Tianjin 300072, China.ORCID 0000-0003-0797-3473

Rongxin SuTianjin Key Laboratory for Marine Environmental Research and Service, School of Marine Science and Technology, Tianjin University, Tianjin 300072, China.

Funding

National Key Research and Development Program of China No. 2020YFC0811102

6 · The paper itself

Abstract

A fiber-reinforced SPR sensor based on silver-nucleated gold-shell bimetallic nanoparticles and graphene oxide was developed and applied to human IgG detection. The refractive index (RI) sensitivity of the Ag@Au/GO fiber SPR sensor is as high as 4715.9 nm/RIU in the RI range of 1.333-1.365. Staphylococcus aureus protein A (SPA) can specifically recognize and bind to the fragment crystallizable (Fc) of the antibody; it facilitates the highly targeted immobilization of the antibody. SPA and rabbit anti-human IgG were immobilized on the surface of the Ag@Au/GO fiber SPR sensor for the detection of different concentrations of human IgG with a sensitivity of 0.53 nm/μg/mL and detection limits of 0.037 μg/mL. This biosensor based on the mixed structure of GO and Ag@Au combined the common advantages of the two materials. Therefore, our study provides a simple platform for biological analysis and has a good application prospect.

Indexed as

Biosensing TechniquesGraphiteImmunoglobulin GSurface Plasmon ResonanceAnimalsGoldHumansLimit of DetectionMetal NanoparticlesOptical FibersRabbitsSilverStaphylococcal Protein AStaphylococcus aureusGoldgraphene oxideGraphiteImmunoglobulin GSilverStaphylococcal Protein Aantibodybimetal sensorfiber-optic SPRgraphene oxidehuman IgG

Identifiers

PMID40096495

DOI10.3390/s25051630

PMCPMC11902575

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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.