Evidence map›Paper›PMID 27805364›Full record

ArticleAnalytical chemistry2016

Maximizing the Signal Gain of Electrochemical-DNA Sensors.

Philippe Dauphin-Ducharme, Kevin W Plaxco

Abstract read
In one paragraph

Article in Analytical chemistry, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.

0numbers the graph read from it
0cells of the map it votes in
47citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

47 citing papers in PubMed.

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  11. Modular DNA origami-based electrochemical detection of DNA and proteins.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Philippe Dauphin-DucharmeDepartment of Chemistry and Biochemistry, and ‡Center for Bioengineering, University of California Santa Barbara , Santa Barbara, California 93106, United States.
Kevin W PlaxcoDepartment of Chemistry and Biochemistry, and ‡Center for Bioengineering, University of California Santa Barbara , Santa Barbara, California 93106, United States.

Funding

A new approach to quantitative, point-of-care serologyR01AI107936 · NIAID · UNIVERSITY OF CALIFORNIA SANTA BARBARA · PI PLAXCO, KEVIN W · 2014 to 2017
$1.4M
NIAID NIH HHS R01 AI107936
6 · The paper itself

Abstract

Electrochemical DNA (E-DNA) sensors have emerged as a promising class of biosensors capable of detecting a wide range of molecular analytes (nucleic acids, proteins, small molecules, inorganic ions) without the need for exogenous reagents or wash steps. In these sensors, a binding-induced conformational change in an electrode-bound "probe" (a target-binding nucleic acid or nucleic-acid-peptide chimera) alters the location of an attached redox reporter, leading to a change in electron transfer that is typically monitored using square-wave voltammetry. Because signaling in this class of sensors relies on binding-induced changes in electron transfer rate, the signal gain of such sensors (change in signal upon the addition of saturating target) is dependent on the frequency of the square-wave potential pulse used to interrogate them, with the optimal square-wave frequency depending on the structure of the probe, the nature of the redox reporter, and other features of the sensor. Here, we show that, because it alters the driving force of the redox reaction and thus electron transfer kinetics, signal gain in this class of sensors is also strongly dependent on the amplitude of the square-wave potential pulse. Specifically, we show here that the simultaneous optimization of square-wave frequency and amplitude produces large (often more than 2-fold) increases in the signal gain of a wide range of E-DNA-type sensors.

Indexed as

Biosensing TechniquesElectrochemical TechniquesDNAKineticsOxidation-ReductionDNA

Identifiers

PMID27805364
PMCPMC5660313

What OpenQuestion holds

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Registered trials

None linked

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.