ArticleMicromachines2023
A Microfluidic Device for Tobacco Ringspot Virus Detection by Electrochemical Impedance Spectroscopy.
Article in Micromachines, 2023. 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.
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Who cites it
1 citing paper in PubMed, 7 citations in OpenAlex.
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
Aiming at the problem of how to achieve the rapid detection of pathogenic microorganisms, this paper takes tobacco ringspot virus as the detection object, designs the impedance detection and analysis platform of tobacco ringspot virus based on microfluidic impedance method, establishes an equivalent circuit model to analyze the experimental results, and determines the optimal detection frequency of tobacco ringspot virus detection. Based on this frequency, an impedance-concentration regression model was established for the detection of tobacco ringspot virus in a tobacco ringspot virus detection device. Based on this model, a tobacco ringspot virus detection device was designed by using an AD5933 impedance detection chip. A comprehensive test study was carried out on the developed tobacco ringspot virus detection device through various testing methods, which verified the feasibility of the tobacco ringspot virus detection device and provided technical support for the field detection of pathogenic microorganisms.
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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.