Evidence map›Paper›PMID 25966875›Full record

ArticleScientific reports2015

Label-free capacitance-based identification of viruses.

Mahmoud Al Ahmad, Farah Mustafa, Lizna M Ali, Jimsheena V Karakkat, Tahir A Rizvi

Abstract read
In one paragraph

Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
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  3. Review
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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

5 authors.

Mahmoud Al AhmadDepartment of Electrical Engineering, College of Engineering, United Arab Emirates University, Al Ain, UAE.
Farah MustafaDepartment of Biochemistry, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, UAE.
Lizna M AliDepartment of Microbiology and Immunology, College of Medicine and Health Sciences United Arab Emirates University, Al Ain, UAE.
Jimsheena V Karakkat1] Department of Electrical Engineering, College of Engineering, United Arab Emirates University, Al Ain, UAE [2] Department of Microbiology and Immunology, College of Medicine and Health Sciences United Arab Emirates University, Al Ain, UAE.
Tahir A RizviDepartment of Microbiology and Immunology, College of Medicine and Health Sciences United Arab Emirates University, Al Ain, UAE.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study was undertaken to quantitate a single virus suspension in culture medium without any pre-processing. The electrical capacitance per virus particle was used to identify the kind of virus present by measuring the suspension (virus plus medium) capacitance, de-embedding the medium contribution, and dividing by the virus count. The proposed technique is based on finding the single virus effective dielectric constant which is directly related to the virus composition. This value was used to identify the virus type accordingly. Two types of viruses thus tested were further quantified by a biochemical technique to validate the results. Furthermore, non-organic nanoparticles with known concentration and capacitance per particle were identified using the proposed method. The selectivity of the method was demonstrated by performing electrical measurements on a third virus, revealing that the proposed technique is specific and sensitive enough to permit detection of a few hundred virus particles per milliliter within a few minutes.

Indexed as

Electric CapacitanceAnimalsHumansNanoparticlesViruses

Identifiers

PMID25966875
PMCPMC4429349

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.