Evidence map›Paper›PMID 35316730›Full record

ArticleBioelectrochemistry (Amsterdam, Netherlands)2022

Design and simulation of a millifluidic device for differential detection of SARS-CoV-2 and H1N1 based on triboelectricity.

Tara Ghafouri, Negin Manavizadeh

Abstract read
In one paragraph

Article in Bioelectrochemistry (Amsterdam, Netherlands), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Review
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

2 authors.

Tara GhafouriNanostructured-Electronic Devices Laboratory, Faculty of Electrical Engineering, K. N. Toosi University of Technology, Tehran 1631714191, Iran.
Negin ManavizadehNanostructured-Electronic Devices Laboratory, Faculty of Electrical Engineering, K. N. Toosi University of Technology, Tehran 1631714191, Iran. Electronic address: manavizadeh@kntu.ac.ir.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Differential diagnosis of pathogenic diseases, presently coronavirus disease 2019 (COVID-19) and influenza, is crucial with due attention to their superspreading events, presumably long incubation period, particular complications, and treatments. In this paper, a label-free, self-powered, and ultrafast immunosensor device working based on triboelectric effect is proposed. Equilibrium constants of specific antibody-antigen reactions are accompanied by IEP-relevant electric charges of antigens to recognize SARS-CoV-2 and H1N1. Simulation attributes including fluid flow and geometrical parameters are optimized so that the maximum capture efficiency of 85.63% is achieved. Accordingly, antibody-antigen complexes form electric double layers (EDLs) across the channel interfaces. The resultant built-in electric field affects the following external electric field derived from triboelectricity, leading to the variation of open-circuit voltage as a sensing metric. The device is flexible to operate in conductor-to-dielectric single-electrode and contact-separation modes simultaneously. While the detection limit is reduced utilizing the single-electrode mode compared to the latter one, surface treatment of the triboelectric pair contributes to the sensitivity enhancement. A threshold value equal to -4.113 V is featured to discriminate these two viruses in a vast detectable region; however, further surface engineering can allow the on-site detection of any electrically-charged pathogen applying the emerging triboelectric immunosensor enjoying a lower detection limit.

Indexed as

Biosensing TechniquesCOVID-19Influenza A Virus, H1N1 SubtypeHumansImmunoassaySARS-CoV-2Antibody-antigen interactionElectric double layer (EDL)Respiratory diseasesTriboelectric effectVirus detection

Identifiers

PMID35316730
PMCPMC8923711

What OpenQuestion holds

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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.