Evidence map›Paper›PMID 31247894›Full record

ArticleSensors (Basel, Switzerland)2019

Influence of Electrode Connection Tracks on Biological Cell Measurements by Impedance Spectroscopy.

Arthur Luiz Alves de Araujo, Julien Claudel, Djilali Kourtiche, Mustapha Nadi

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. 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

4 authors.

Arthur Luiz Alves de AraujoInstitut Jean Lamour, Lorraine University (CNRS-UMR 7198), 54011 Nancy, France. alvesdea1@univ-lorraine.fr.
Julien ClaudelInstitut Jean Lamour, Lorraine University (CNRS-UMR 7198), 54011 Nancy, France.
Djilali KourticheInstitut Jean Lamour, Lorraine University (CNRS-UMR 7198), 54011 Nancy, France.
Mustapha NadiInstitut Jean Lamour, Lorraine University (CNRS-UMR 7198), 54011 Nancy, France. mustapha.nadi@univ-lorraine.fr.ORCID 0000-0002-8549-5713

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The limit of detection of a biological sensor is an important parameter because, when it is optimized, it allows the detection of a reduced number of biological cells and the reduction of the detection time. This parameter can be improved upon with a reduction in electrode size, but the rate of detection is similarly reduced as well. To avoid this problem, we propose a sensor matrix composed of 20 × 20 µm² coplanar square electrodes with a standard clean room manufacturing process. However, it was observed that the exposition of electrode connection tracks to the solution reduces the normalized impedance variation. In this pursuit, we propose in this paper an analysis of electrode connection tracks on the normalized impedance variation and cutoff frequencies to biological cell measurements by impedance spectroscopy. The experimental results were obtained using the E4990A Keysight impedance analyser (Keysight Technologies, Santa Rosa, CA, USA) with a frequency band ranging from 100 Hz to 12 MHz, thus allowing for good measurement accuracy. Therefore, it was found that, for the measurements between the electrodes with 9 µm of connection tracks in contact with the solution, the normalized impedance variation was from 3.7% to 4.2% for different measurements, while, for the electrodes with 40 µm of connection tracks in contact with the solution, the normalized impedance variation was from 1.8% to 2.1% for different measurements.

Indexed as

ElectrodesBiosensing TechniquesDielectric SpectroscopyEquipment Designbiological cell detectionbiosensorcoplanar electrodesimpedance spectroscopy

Identifiers

PMID31247894
PMCPMC6650941

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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.