ArticleRSC advances2018
Rapid colorimetric glucose detection
Article in RSC advances, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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Who cites it
2 citing papers in PubMed.
- Nanocellulose coated paper diagnostic to measure glucose concentration in human blood.Frontiers in bioengineering and biotechnology · 2022Article
- Surface modification of plasmonic noble metal-metal oxide core-shell nanoparticles.Nanoscale advances · 2019Review
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The chain reaction amplification mechanism (CRAM) has been extensively studied, but it has not been effectively developed at the molecular scale and still needs to consume amounts of monomers to show the macroscopic phenomenon needed for detection. Herein, rationally-designed silica-coated silver nanoparticles with acrylic acid-functionalization were used as a plasmonic nanosensor to realize highly sensitive and fast colorimetric glucose detection with less monomer consumption, which effectively integrated CRAM with the localized surface plasmon resonance effect, developing CRAM at the molecular scale. The glucose detection mechanism of the proposed sensor was based on free-radical polymerization by biocatalytic initiation, which would induce the aggregation of Ag NPs, leading to a decrease in the plasmon resonance intensity. As a result, the detection limit could reach 2.06 × 10
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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.