Evidence map›Paper›PMID 34409907›Full record

ReviewExpert review of molecular diagnostics2021

Potential of CRISPR/Cas system in the diagnosis of COVID-19 infection.

V Edwin Hillary, Savarimuthu Ignacimuthu, S Antony Ceasar

Abstract readReview
In one paragraph

Review in Expert review of molecular diagnostics, 2021. 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. Review
  2. Review
  3. Article
  4. Review
  5. Review
  6. Review
  7. Review
  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

3 authors.

V Edwin HillaryDivision of Biotechnology, Entomology Research Institute, Loyola College, University of Madras, Chennai, India.
Savarimuthu IgnacimuthuXavier Research Foundation, St.Xavier's College, Palayamkottai, Tirunelveli, India.
S Antony CeasarDepartment of Biosciences, Rajagiri College of Social Sciences, Cochin, India.ORCID 0000-0003-4106-1531

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionEmerging novel infectious diseases and persistent pandemics with potential to destabilize normal life remain a public health concern for the whole world. The recent outbreak of pneumonia caused by Coronavirus infectious disease-2019 (COVID-19) resulted in high mortality due to a lack of effective drugs or vaccines. With a constantly increasing number of infections with mutated strains and deaths across the globe, rapid, affordable and specific detections with more accurate diagnosis and improved health treatments are needed to combat the spread of this novel pathogen COVID-19. AREAS COVERED: Researchers have started to utilize the recently invented clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated proteins (CRISPR/Cas)-based tools for the rapid detection of novel COVID-19. In this review, we summarize the potential of CRISPR/Cas system for the diagnosis and enablement of efficient control of COVID-19. EXPERT OPINION: Multiple groups have demonstrated the potential of utilizing CRISPR-based diagnosis tools for the detection of SARS-CoV-2. In coming months, we expect more novel and rapid CRISPR-based kits for mass detection of COVID-19-infected persons within a fraction of a second. Therefore, we believe science will conquer COVID-19 in the near future.

Indexed as

Communicable DiseasesCOVID-19CRISPR-Cas SystemsHumansPandemicsRNA, ViralSARS-CoV-2RNA, ViralCOVID-19CRISPR/CasCRISPR/Cas12CRISPR/Cas13CRISPR/Cas9DETECTRdiagnosticsinfectious diseaseSHERLOCK

Identifiers

PMID34409907
PMCPMC8607542

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.