Evidence map›Paper›PMID 35599642›Full record

ReviewBioengineering & translational medicine2022

Nanomaterials-based sensors for the detection of COVID-19: A review.

Gowhar A Naikoo, Fareeha Arshad, Israr U Hassan, Tasbiha Awan, Hiba Salim, Mona Z Pedram, Waqar Ahmed, Vaishwik Patel, Ajay S Karakoti, Ajayan Vinu

Abstract readReview
In one paragraph

Review in Bioengineering & translational medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Review
  6. Review
  7. Article
  8. Review
  9. Batteryless wireless magnetostrictive FeSensors and actuators. A, Physical · 2023
    Article
  10. Review
  11. Review
  12. Review
  13. Nanomaterials-based sensors for the detection of COVID-19: A review.Bioengineering & translational medicine · 2022
    Review
  14. 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

10 authors.

Gowhar A NaikooDepartment of Mathematics and Sciences College of Arts and Applied Sciences, Dhofar University Salalah Sultanate of Oman.
Fareeha ArshadDepartment of Mathematics and Sciences College of Arts and Applied Sciences, Dhofar University Salalah Sultanate of Oman.
Israr U HassanCollege of Engineering, Dhofar University Salalah Sultanate of Oman.
Tasbiha AwanDepartment of Mathematics and Sciences College of Arts and Applied Sciences, Dhofar University Salalah Sultanate of Oman.
Hiba SalimDepartment of Mathematics and Sciences College of Arts and Applied Sciences, Dhofar University Salalah Sultanate of Oman.
Mona Z PedramFaculty of Mechanical Engineering-Energy Division K.N. Toosi University of Technology Tehran Iran.
Waqar AhmedSchool of Mathematics and Physics, College of Science University of Lincoln Lincoln UK.
Vaishwik PatelGlobal Innovative Center for Advanced Nanomaterials College of Engineering, Science and Environment, The University of Newcastle Callaghan Australia.ORCID https://orcid.org/0000-0002-3495-0093
Ajay S KarakotiGlobal Innovative Center for Advanced Nanomaterials College of Engineering, Science and Environment, The University of Newcastle Callaghan Australia.
Ajayan VinuGlobal Innovative Center for Advanced Nanomaterials College of Engineering, Science and Environment, The University of Newcastle Callaghan Australia.ORCID https://orcid.org/0000-0002-7508-251X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the threat of increasing SARS-CoV-2 cases looming in front of us and no effective and safest vaccine available to curb this pandemic disease due to its sprouting variants, many countries have undergone a lockdown 2.0 or planning a lockdown 3.0. This has upstretched an unprecedented demand to develop rapid, sensitive, and highly selective diagnostic devices that can quickly detect coronavirus (COVID-19). Traditional techniques like polymerase chain reaction have proven to be time-inefficient, expensive, labor intensive, and impracticable in remote settings. This shifts the attention to alternative biosensing devices that can be successfully used to sense the COVID-19 infection and curb the spread of coronavirus cases. Among these, nanomaterial-based biosensors hold immense potential for rapid coronavirus detection because of their noninvasive and susceptible, as well as selective properties that have the potential to give real-time results at an economical cost. These diagnostic devices can be used for mass COVID-19 detection to understand the rapid progression of the infection and give better-suited therapies. This review provides an overview of existing and potential nanomaterial-based biosensors that can be used for rapid SARS-CoV-2 diagnostics. Novel biosensors employing different detection mechanisms are also highlighted in different sections of this review. Practical tools and techniques required to develop such biosensors to make them reliable and portable have also been discussed in the article. Finally, the review is concluded by presenting the current challenges and future perspectives of nanomaterial-based biosensors in SARS-CoV-2 diagnostics.

Indexed as

biosensorscoronavirus sensorCOVID‐19nanomaterial‐based biosensorspandemicpoint of care diagnosisSARS‐CoV‐2

Identifiers

PMID35599642
PMCPMC9110902

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.