journal article·2021-06

Fast and sensitive immuno-PCR assisted by plasmonic magnetic nanoparticles

Yuwei Qiu, Kunlun Jiang, Jingrui Wu, Hua Mi, Yung-Kang Peng, Yun Young Go, Hyun June Park, Jung-Hoon Lee

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Abstract

Abstract Immunoassay for quantitative protein detection is an important tool in biomedical and clinical researches. Various types of detection platforms have emerged from typical ELISA using chromogenic reporter to more advanced approaches including electric, electrochemiluminescent and fluorogenic reporters to create quantitative analysis. Among them, fluorescence-based immuno-polymerase chain reaction (iPCR) is regarded as one of the simplest and most sensitive strategy that combines the specificity of immunological recognition technology with the amplification power of PCR. However, most PCR-based immunoassays to date have relied on the costly and time-consuming Peltier block heating technology. Here, we introduce a plasmonic photothermal (PPT)-iPCR assay method based on plasmonic magnetic nanoparticles to reduce the required thermal cycling time of amplification without compromising the superior sensitivity of iPCR. PPT-iPCR is capable of sensitive and quantitative detection of tumor necrosis factor-α (TNF-α) proteins ranging from 0.1 pg/mL to 1000 pg/mL within 8 min. PPT-iPCR uses fast, energy-efficient and inexpensive LED-based devices and can be used with commercial kits without modification while achieving excellent sensitivity. Our strategy can be easily combined with mobile phones or micro-optics, thus laying the foundation for the development of inexpensive, highly mobile detection devices that can quickly and accurately analyze biomarkers in a variety of diagnostic applications.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Biosensors and Analytical Detection · Advanced biosensing and bioanalysis techniques · Gold and Silver Nanoparticles Synthesis and Applications

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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