Evidence map›Paper›PMID 33925032›Full record

ReviewBioengineering (Basel, Switzerland)2021

COVID-19 Diagnostic Strategies Part II: Protein-Based Technologies.

Tina Shaffaf, Ebrahim Ghafar-Zadeh

Open access · goldAbstract readReview
In one paragraph

Review in Bioengineering (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.1field-weighted citation impact, top 19% 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

11 citing papers in PubMed, 20 citations in OpenAlex.

  1. Review
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  7. Receptor-binding domain-based immunoassays for serosurveillance differentiate efficiently between SARS-CoV2-exposed and non-exposed farmed mink.Journal of veterinary diagnostic investigation : official publication of the American Association of Veterinary Laboratory Diagnosticians, Inc · 2022
    Article
  8. Article
  9. Review
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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 at 1 institution in 1 country.

Tina ShaffafBiologically Inspired Sensors and Actuators Laboratory (BioSA), York University, Toronto, ON M3J1P3, Canada.
Ebrahim Ghafar-ZadehBiologically Inspired Sensors and Actuators Laboratory (BioSA), York University, Toronto, ON M3J1P3, Canada.ORCID 0000-0002-7090-2304
York University · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

After the initiation of the current outbreak, humans' lives have been profoundly impacted by COVID-19. During the first months, no rapid and reliable detecting tool was readily available to sufficiently respond to the requirement of massive testing. In this situation, when the development of an effective vaccine requires at least a few months, it is crucial to be prepared by developing and commercializing affordable, accurate, rapid and adaptable biosensors not only to fight Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) but also to be armed to avoid the pandemic in the earliest stages in the future. The COVID-19 diagnostic tools are categorized into two main groups of Nucleic Acid (NA)-based and protein-based tests. To date, nucleic acid-based detection has been announced as the gold-standard strategy for coronavirus detection; however, protein-based tests are promising alternatives for rapid and large-scale screening of susceptible groups. In this review, we discuss the current protein-based biosensing tools, the research advances and the potential protein-detecting strategies for COVID-19 detection. This narrative review aims to highlight the importance of the diagnostic tests, encourage the academic research groups and the companies to eliminate the shortcomings of the current techniques and step forward to mass-producing reliable point-of-care (POC) and point-of-need (PON) adaptable diagnostic tools for large-scale screening in the future outbreaks.

Indexed as

antigenic testsCOVID-19 detectionELISALFIApoint-of-care (POC) detectionprotein-based testsprotein microarrayrapid diagnostic testsSARS-CoV-2serological tests

Identifiers

PMID33925032
PMCPMC8145709
OpenAlexW3157963590

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.