Evidence map›Paper›PMID 25355078›Full record

ArticleScientific reports2014

Virus detection and quantification using electrical parameters.

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

Abstract read
In one paragraph

Article in Scientific reports, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
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  3. Review
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  5. 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.

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.
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

Here we identify and quantitate two similar viruses, human and feline immunodeficiency viruses (HIV and FIV), suspended in a liquid medium without labeling, using a semiconductor technique. The virus count was estimated by calculating the impurities inside a defined volume by observing the change in electrical parameters. Empirically, the virus count was similar to the absolute value of the ratio of the change of the virus suspension dopant concentration relative to the mock dopant over the change in virus suspension Debye volume relative to mock Debye volume. The virus type was identified by constructing a concentration-mobility relationship which is unique for each kind of virus, allowing for a fast (within minutes) and label-free virus quantification and identification. For validation, the HIV and FIV virus preparations were further quantified by a biochemical technique and the results obtained by both approaches corroborated well. We further demonstrate that the electrical technique could be applied to accurately measure and characterize silica nanoparticles that resemble the virus particles in size. Based on these results, we anticipate our present approach to be a starting point towards establishing the foundation for label-free electrical-based identification and quantification of an unlimited number of viruses and other nano-sized particles.

Indexed as

Biosensing TechniquesAnimalsHIVHumansImmunodeficiency Virus, FelineNanoparticlesReproducibility of ResultsSensitivity and SpecificityVirionViruses

Identifiers

PMID25355078
PMCPMC4213776

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.