Evidence map›Paper›PMID 33718775›Full record

ReviewEmergent materials2021

Advances in emergent biological recognition elements and bioelectronics for diagnosing COVID-19.

Praopim Limsakul, Krit Charupanit, Chochanon Moonla, Itthipon Jeerapan

Abstract readReview
In one paragraph

Review in Emergent materials, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Review
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  4. 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

4 authors.

Praopim LimsakulDivision of Physical Science, Faculty of Science, Prince of Songkla University, Hat Yai, Songkhla, 90112 Thailand.
Krit CharupanitDepartment of Biomedical Sciences and Biomedical Engineering, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla, 90110 Thailand.
Chochanon MoonlaSchool of Chemistry, Institute of Science, Suranaree University of Technology, 111, University Avenue, Nakhon Ratchasima, 30000 Thailand.
Itthipon JeerapanDivision of Physical Science, Faculty of Science, Prince of Songkla University, Hat Yai, Songkhla, 90112 Thailand.ORCID 0000-0001-8016-6411

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Coronaviruses pose a serious threat to public health. Tremendous efforts are dedicated to advance reliable and effective detection of coronaviruses. Currently, the coronavirus disease 2019 (COVID-19) diagnosis mainly relies on the detection of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genetic materials by using reverse transcription-polymerase chain reaction (RT-PCR) assay. However, simpler and more rapid and reliable alternatives are needed to meet high demand during the pandemic. Biosensor-based diagnosis approaches become alternatives for selectively and rapidly detecting virus particles because of their biorecognition elements consisting of biomaterials that are specific to virus biomarkers. Here, we summarize biorecognition materials, including antibodies and antibody-like molecules, that are designed to recognize SARS-CoV-2 biomarkers and the advances of recently developed biosensors for COVID-19 diagnosis. The design of biorecognition materials or layers is crucial to maximize biosensing performances, such as high selectivity and sensitivity of virus detection. Additionally, the recent representative achievements in developing bioelectronics for sensing coronavirus are included. This review includes scholarly articles, mainly published in 2020 and early 2021. In addition to capturing the fast development in the fields of applied materials and biodiagnosis, the outlook of this rapidly evolving technology is summarized. Early diagnosis of COVID-19 could help prevent the spread of this contagious disease and provide significant information to medical teams to treat patients.

Indexed as

AntibodyAntibody-like moleculeBiorecognition materialCOVID-19SARS-CoV-2Virus

Identifiers

PMID33718775
PMCPMC7937783

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.