Evidence map›Paper›PMID 35799935›Full record

ArticleRSC advances2022

A SARS-Cov-2 sensor based on upconversion nanoparticles and graphene oxide.

Konstantina Alexaki, Maria Eleni Kyriazi, Joshua Greening, Lapatrada Taemaitree, Afaf H El-Sagheer, Tom Brown, Xunli Zhang, Otto L Muskens, Antonios G Kanaras

Abstract read
In one paragraph

Article in RSC advances, 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
–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

8 citing papers in PubMed.

  1. Article
  2. Review
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  4. Article
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  8. 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

9 authors.

Konstantina AlexakiSchool of Physics and Astronomy, Faculty of Engineering and Physical Sciences, University of Southampton Southampton SO17 1BJ UK a.kanaras@soton.ac.uk.ORCID https://orcid.org/0000-0002-8702-2696
Maria Eleni KyriaziCollege of Engineering and Technology, American University of the Middle East Kuwait.ORCID https://orcid.org/0000-0002-1427-0349
Joshua GreeningSchool of Physics and Astronomy, Faculty of Engineering and Physical Sciences, University of Southampton Southampton SO17 1BJ UK a.kanaras@soton.ac.uk.
Lapatrada TaemaitreeDepartment of Chemistry, University of Oxford, Chemistry Research Laboratory 12 Mansfield Road Oxford OX1 3TA UK.
Afaf H El-SagheerDepartment of Chemistry, University of Oxford, Chemistry Research Laboratory 12 Mansfield Road Oxford OX1 3TA UK.ORCID https://orcid.org/0000-0001-8706-1292
Tom BrownDepartment of Chemistry, University of Oxford, Chemistry Research Laboratory 12 Mansfield Road Oxford OX1 3TA UK.ORCID https://orcid.org/0000-0002-6538-3036
Xunli ZhangSchool of Engineering, Faculty of Engineering and Physical Sciences, University of Southampton Southampton SO17 1BJ UK.ORCID https://orcid.org/0000-0002-4375-1571
Otto L MuskensSchool of Physics and Astronomy, Faculty of Engineering and Physical Sciences, University of Southampton Southampton SO17 1BJ UK a.kanaras@soton.ac.uk.
Antonios G KanarasSchool of Physics and Astronomy, Faculty of Engineering and Physical Sciences, University of Southampton Southampton SO17 1BJ UK a.kanaras@soton.ac.uk.ORCID https://orcid.org/0000-0002-9847-6706

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Since the beginning of the COVID-19 pandemic, there has been an increased need for the development of novel diagnostic solutions that can accurately and rapidly detect SARS-CoV-2 infection. In this work, we demonstrate the targeting of viral oligonucleotide markers within minutes without the requirement of a polymerase chain reaction (PCR) amplification step

Identifiers

PMID35799935
PMCPMC9215703

What OpenQuestion holds

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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.