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A sandwich immunoassay using magnetic beads as bioreaction platforms and AuNPs as electroactive labels for the electrochemical detection of human IgG antibodies anti-Hepatitis B surface antigen (HBsAg), is here presented as an alternative to the standard methods used in hospitals for the detection of human antibodies directed against HBsAg (such as ELISA or MEIA). The electrochemical detection of AuNPs is carried out approaching their catalytic properties towards the hydrogen evolution in an acidic medium, without previous nanoparticle dissolution. The obtained results are a good promise toward the development of a fully integrated biosensing set-up. The developed technology based on this detection mode would be simple to use, low cost and integrated into a portable instrumentation that may allow its application even at doctor-office. The sample volumes required can be lower than those used in the traditional methods. This may lead to several other applications with interest for clinical control.
Immunoassay, Magnetosandwich immunoassay, Hepatitis B Surface Antigens, Metal Nanoparticles, Screen-printed electrodes, Biosensing Techniques, Electrochemical Techniques, Immunosensor, Hepatitis B, Magnetics, Immobilized Proteins, Microscopy, Electron, Transmission, Immunoglobulin G, Gold nanoparticles, Hydrogen evolution electrocatalysis, Humans, Gold, Hepatitis B Antibodies
Immunoassay, Magnetosandwich immunoassay, Hepatitis B Surface Antigens, Metal Nanoparticles, Screen-printed electrodes, Biosensing Techniques, Electrochemical Techniques, Immunosensor, Hepatitis B, Magnetics, Immobilized Proteins, Microscopy, Electron, Transmission, Immunoglobulin G, Gold nanoparticles, Hydrogen evolution electrocatalysis, Humans, Gold, Hepatitis B Antibodies
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| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
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