Evidence map›Paper›PMID 35512584›Full record

ArticleBiosensors & bioelectronics2022

Electronic field effect detection of SARS-CoV-2 N-protein before the onset of symptoms.

I Novodchuk, M Kayaharman, I Prassas, A Soosaipillai, R Karimi, I A Goldthorpe, E Abdel-Rahman, J Sanderson, E P Diamandis, M Bajcsy and 1 more

Open access · greenAbstract read
In one paragraph

Article in Biosensors & bioelectronics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.9field-weighted citation impact, top 7% of its field
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

8 citing papers in PubMed, 29 citations in OpenAlex.

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  8. Built-In Packaging for Single Terminal Devices.Sensors (Basel, Switzerland) · 2022
    Article
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

11 authors at 2 institutions in 1 country.

I NovodchukMechanical and Mechatronics Engineering, University of Waterloo, Waterloo, ON, Canada; Waterloo Institute for Nanotechnology (WIN), University of Waterloo, Waterloo, ON, Canada. Electronic address: inovodch@uwaterloo.ca.
M KayaharmanWaterloo Institute for Nanotechnology (WIN), University of Waterloo, Waterloo, ON, Canada; Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada.
I PrassasDepartment of Pathology and Laboratory Medicine, Mount Sinai Hospital, Toronto, Canada.
A SoosaipillaiDepartment of Pathology and Laboratory Medicine, Mount Sinai Hospital, Toronto, Canada.
R KarimiDept. of Physics and Astronomy, University of Waterloo, Waterloo, ON, Canada.
I A GoldthorpeWaterloo Institute for Nanotechnology (WIN), University of Waterloo, Waterloo, ON, Canada; Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada.
E Abdel-RahmanDept. of Systems Design Engineering, University of Waterloo, Waterloo, ON, Canada.
J SandersonDept. of Physics and Astronomy, University of Waterloo, Waterloo, ON, Canada.
E P DiamandisDepartment of Pathology and Laboratory Medicine, Mount Sinai Hospital, Toronto, Canada; Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Canada.
M BajcsyDepartment of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada; Institute for Quantum Computing, University of Waterloo, Waterloo, ON, Canada.
M YavuzMechanical and Mechatronics Engineering, University of Waterloo, Waterloo, ON, Canada; Waterloo Institute for Nanotechnology (WIN), University of Waterloo, Waterloo, ON, Canada.
University of Waterloo · CAMount Sinai Hospital · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As part of the efforts to contain the pandemic, researchers around the world have raced to develop testing platforms to detect the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes the Coronavirus disease 2019 (COVID-19). Within the different detection platforms studied, the field effect transistor (FET) is a promising device due to its high sensitivity and fast detection capabilities. In this work, a graphene-based FET which uses a boron and nitrogen co-doped graphene oxide gel (BN-GO gel) transducer functionalized with nucleoprotein antibodies, has been investigated for the detection of SARS-CoV-2 nucleocapsid (N)-protein in buffer. This biosensor was able to detect the viral protein in less than 4 min, with a limit of detection (LOD) as low as 10 ag/mL and a wide linear detection range stretching over 11 orders of magnitude from 10 ag/mL-1 μg/mL. This represents the lowest LOD and widest detection range of any COVID-19 sensor and thus can potentially enable the detection of infected individuals before they become contagious. In addition to its potential use in the COVID-19 pandemic, our device serves as a proof-of-concept of the ability of functionalized BN-GO gel FETs to be used for ultrasensitive yet robust biosensors.

Indexed as

Biosensing TechniquesCOVID-19ElectronicsHumansPandemicsSARS-CoV-2BiosensorCovid-19FETGraphene

Identifiers

PMID35512584
PMCPMC9052636
OpenAlexW4225155416

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.