Evidence map›Paper›PMID 19230649›Full record

ArticleBiosensors & bioelectronics2009

Use of electric cell-substrate impedance sensing to assess in vitro cytotoxicity.

Daniel Opp, Brian Wafula, Jennifer Lim, Eric Huang, Jun-Chih Lo, Chun-Min Lo

Abstract read
In one paragraph

Article in Biosensors & bioelectronics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing 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

38 citing papers in PubMed.

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  15. Application of impedance measurement to investigate in vitro inhalation toxicity of bacteria.Journal of occupational medicine and toxicology (London, England) · 2021
    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

6 authors.

Daniel OppDepartment of Physics, University of South Florida, Tampa, FL 33620-5700, United States.
Brian Wafula
Jennifer Lim
Eric Huang
Jun-Chih Lo
Chun-Min Lo

Funding

c-Met Mediated Ovarian Cancer Cell MotilityR03CA123621 · NCI · UNIVERSITY OF SOUTH FLORIDA · PI LO, CHUN-MIN · 2007 to 2008
$145k
NCI NIH HHS 1R03CA123621-01A1NCI NIH HHS R03 CA123621
6 · The paper itself

Abstract

In vitro assessment of cytotoxicity based on electrochemical impedance spectroscopy (EIS) needs more quantitative methods to analyze the alteration of cell morphology and motility, and hence the potential risk to human health. Here, we applied electric cell-substrate impedance sensing (ECIS) to evaluate dose-dependent responses of human umbilical vein endothelial cells exposed to cytochalasin B. To detect subtle changes in cell morphology, the frequency-dependent impedance data of the cell monolayer were measured and analyzed with a theoretical cell-electrode model. To detect the alternation of cell micromotion in response to cytochalasin B challenge, time-series impedance fluctuations of cell-covered electrodes were monitored and the values of power spectrum, variance, and variance of the increments were calculated to verify the difference. While a dose-dependent relationship was generally observed from the overall resistance of the cell monolayer, the analysis of frequency-dependent impedance and impedance fluctuations distinguished cytochalasin B levels as low as 0.1 microM. Our results show that cytochalasin B causes a decrease of junctional resistance between cells, an increase of membrane capacitance, and the reduction in micromotion.

Indexed as

ApoptosisBiological AssayBiosensing TechniquesCells, CulturedCytochalasin BDose-Response Relationship, DrugElectric ImpedanceElectrochemistryEndothelial CellsEquipment DesignEquipment Failure AnalysisHumansPlethysmography, ImpedanceReproducibility of ResultsSensitivity and SpecificityToxicity TestsCytochalasin B

Identifiers

PMID19230649
PMCPMC2668605

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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.