Evidence map›Paper›PMID 31579297›Full record

ArticleAnalytical methods : advancing methods and applications2018

Continuous monitoring of adenosine and its metabolites using microdialysis coupled to microchip electrophoresis with amperometric detection.

Shamal M Gunawardhana, Susan M Lunte

Abstract read
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Article in Analytical methods : advancing methods and applications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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.

Shamal M GunawardhanaRalph N. Adams Institute for Bioanalytical Chemistry, University of Kansas, Lawrence, KS, USA.
Susan M LunteRalph N. Adams Institute for Bioanalytical Chemistry, University of Kansas, Lawrence, KS, USA.

Funding

Understanding the mechanobiology of stem cells in a microengineered 3D cardiac tissue environment with cardiomyopathyP20GM103638 · NIGMS · UNIVERSITY OF KANSAS LAWRENCE · PI LUNTE, SUSAN M · 2012 to 2021
$22.1M
NIGMS NIH HHS P20 GM103638
6 · The paper itself

Abstract

Rapid monitoring of concentration changes of neurotransmitters and energy metabolites is important for understanding the biochemistry of neurological disease as well as for developing therapeutic options. This paper describes the development of a separation-based sensor using microchip electrophoresis (ME) with electrochemical (EC) detection coupled to microdialysis (MD) sampling for continuous on-line monitoring of adenosine and its downstream metabolites. The device was fabricated completely in PDMS. End-channel electrochemical detection was accomplished using a carbon fiber working electrode embedded in the PDMS. The separation conditions for adenosine, inosine, hypoxanthine, and guanosine were investigated using a ME-EC chip with a 5-cm long separation channel. The best resolution was achieved using a background electrolyte consisting of 35 mM sodium borate at pH 10, 15% dimethyl sulfoxide (DMSO), and 2 mM sodium dodecyl sulphate (SDS), and a field strength of 222 V/cm. Under these conditions, all four purines were separated in less than 85 s. Using a working electrode detection potential of 1.4 vs Ag/AgCl, the limits of detection were 25, 33, 10, and 25 μM for adenosine, inosine, hypoxanthine, and guanosine, respectively. The ME-EC chip was then coupled to microdialysis sampling using a novel all-PDMS microdialysis-microchip interface that was reversibly sealed. This made alignment of the working electrode with the end of the separation channel much easier and more reproducible than could be obtained with previous MD-ME-EC systems. The integrated device was then used to monitor the enzymatic conversion of adenosine to inosine

Identifiers

PMID31579297
PMCPMC6774626

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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.