ReviewBiotechnology and bioprocess engineering : BBE2012
Recent development of highly sensitive protease assay methods: Signal amplification through enzyme cascades.
Review in Biotechnology and bioprocess engineering : BBE, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
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.
Who cites it
1 citing paper in PubMed, 19 citations in OpenAlex.
- Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Proteases are involved in almost all biological processes, and therefore, aberrant activity of many of these enzymes is an important indicator of disease. Various methods have been developed to analyze protease activity, among which, protease assays based on resonance energy transfer are currently used most widely. However, quantitative methods with relatively higher sensitivity are needed, especially for disease diagnosis at early stages. One of the strategies to achieve higher sensitivity is to implement signal amplification of the protease activity. In this review, we briefly summarize the protease assay methods based on resonance energy transfer, and then elaborate the efforts to develop sensitive protease assays through signal amplification by using enzyme cascades.
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Registered trials
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.