Title |
Rapid, Automated, and Specific Immunoassay to Directly Measure Matrix Metalloproteinase-9–Tissue Inhibitor of Metalloproteinase-1 Interactions in Human Plasma Using AlphaLISA Technology: A New Alternative to Classical ELISA
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Published in |
Frontiers in immunology, July 2017
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DOI | 10.3389/fimmu.2017.00853 |
Pubmed ID | |
Authors |
Helena Pulido-Olmo, Elena Rodríguez-Sánchez, José Alberto Navarro-García, María G. Barderas, Gloria Álvarez-Llamas, Julián Segura, Marisol Fernández-Alfonso, Luis M. Ruilope, Gema Ruiz-Hurtado |
Abstract |
The protocol describes a novel, rapid, and no-wash one-step immunoassay for highly sensitive and direct detection of the complexes between matrix metalloproteinases (MMPs) and their tissue inhibitor of metalloproteinases (TIMPs) based on AlphaLISA(®) technology. We describe two procedures: (i) one approach is used to analyze MMP-9-TIMP-1 interactions using recombinant human MMP-9 with its corresponding recombinant human TIMP-1 inhibitor and (ii) the second approach is used to analyze native or endogenous MMP-9-TIMP-1 protein interactions in samples of human plasma. Evaluating native MMP-9-TIMP-1 complexes using this approach avoids the use of indirect calculations of the MMP-9/TIMP-1 ratio for which independent MMP-9 and TIMP-1 quantifications by two conventional ELISAs are needed. The MMP-9-TIMP-1 AlphaLISA(®) assay is quick, highly simplified, and cost-effective and can be completed in less than 3 h. Moreover, the assay has great potential for use in basic and preclinical research as it allows direct determination of native MMP-9-TIMP-1 complexes in circulating blood as biofluid. |
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Switzerland | 1 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
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Unknown | 23 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 8 | 35% |
Student > Master | 3 | 13% |
Researcher | 3 | 13% |
Student > Bachelor | 3 | 13% |
Lecturer | 1 | 4% |
Other | 3 | 13% |
Unknown | 2 | 9% |
Readers by discipline | Count | As % |
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Biochemistry, Genetics and Molecular Biology | 6 | 26% |
Medicine and Dentistry | 3 | 13% |
Chemistry | 2 | 9% |
Agricultural and Biological Sciences | 2 | 9% |
Nursing and Health Professions | 1 | 4% |
Other | 3 | 13% |
Unknown | 6 | 26% |