Evidence map›Paper›PMID 27279933›Full record

ArticleBiomicrofluidics2016

Micro electrical impedance spectroscopy on a needle for ex vivo discrimination between human normal and cancer renal tissues.

Joho Yun, Hyeon Woo Kim, Yangkyu Park, Jung-Joon Cha, Jeong Zoo Lee, Dong Gil Shin, Jong-Hyun Lee

Abstract read
In one paragraph

Article in Biomicrofluidics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

The trial behind it

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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

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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4 · The record

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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

7 authors.

Joho YunDepartment of Biomedical Science and Engineering, Gwangju Institute of Science and Technology (GIST) , Gwangju 500-712, South Korea.
Hyeon Woo KimDepartment of Biomedical Science and Engineering, Gwangju Institute of Science and Technology (GIST) , Gwangju 500-712, South Korea.
Yangkyu ParkSchool of Mechanical Engineering , GIST, Gwangju 500-712, South Korea.
Jung-Joon ChaDepartment of Biomedical Science and Engineering, Gwangju Institute of Science and Technology (GIST) , Gwangju 500-712, South Korea.ORCID 0000-0002-8299-1877
Jeong Zoo LeeDepartment of Urology, Pusan National University Hospital , 179 Gudeok-ro, Seo-gu, Busan 602-739, South Korea.
Dong Gil ShinDepartment of Urology, Pusan National University Hospital , 179 Gudeok-ro, Seo-gu, Busan 602-739, South Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ex-vivo discrimination between human normal and cancer renal tissues was confirmed using μEoN (micro electrical impedance spectroscopy-on-a-needle) by measuring and comparing the electrical impedances in the frequency domain. To quantify the extent of discrimination between dissimilar tissues and to determine the optimal frequency at which the discrimination capability is at a maximum, discrimination index (DI) was employed for both magnitude and phase. The highest values of DI for the magnitude and phase were 5.15 at 1 MHz and 3.57 at 1 kHz, respectively. The mean magnitude and phase measured at the optimal frequency for normal tissues were 5013.40 ± 94.39 Ω and -68.54 ± 0.72°, respectively; those for cancer tissues were 4165.19 ± 70.32 Ω and -64.10 ± 0.52°, respectively. A statistically significant difference (p< 0.05) between the two tissues was observed at all the investigated frequencies. To extract the electrical properties (resistance and capacitance) of these bio-tissues through curve fitting with experimental results, an equivalent circuit was proposed based on the μEoN structure on the condition that the μEoN was immersed in the bio-tissues. The average and standard deviation of the extracted resistance and capacitance for the normal tissues were 6.22 ± 0.24 kΩ and 280.21 ± 32.25 pF, respectively, and those for the cancer tissues were 5.45 ± 0.22 kΩ and 376.32 ± 34.14 pF, respectively. The electrical impedance was higher in the normal tissues compared with the cancer tissues. The μEoN could clearly discriminate between normal and cancer tissues by comparing the results at the optimal frequency (magnitude and phase) and those of the curve fitting (extracted resistance and capacitance).

Identifiers

PMID27279933
PMCPMC4874925

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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.