Evidence map›Paper›PMID 32604724›Full record

ReviewInternational journal of molecular sciences2020

Alejandro Llanes, Carlos M Restrepo, Zuleima Caballero, Sreekumari Rajeev, Melissa A Kennedy, Ricardo Lleonart

Abstract readReview
In one paragraph

Review in International journal of molecular sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 1 pooled it
–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

32 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Review
  12. Review
  13. Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. Review
  19. Article
  20. Article
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

6 authors.

Alejandro LlanesCentro de Biología Celular y Molecular de Enfermedades, Instituto de Investigaciones Científicas y Servicios de Alta Tecnología (INDICASAT AIP), Panama City 0801, Panama.ORCID 0000-0002-6949-2782
Carlos M RestrepoCentro de Biología Celular y Molecular de Enfermedades, Instituto de Investigaciones Científicas y Servicios de Alta Tecnología (INDICASAT AIP), Panama City 0801, Panama.ORCID 0000-0003-1311-1132
Zuleima CaballeroCentro de Biología Celular y Molecular de Enfermedades, Instituto de Investigaciones Científicas y Servicios de Alta Tecnología (INDICASAT AIP), Panama City 0801, Panama.ORCID 0000-0003-4538-9489
Sreekumari RajeevCollege of Veterinary Medicine, University of Florida, Gainesville, FL 32610, USA.ORCID 0000-0001-6600-9102
Melissa A KennedyCollege of Veterinary Medicine, University of Tennessee, Knoxville, TN 37996, USA.
Ricardo LleonartCentro de Biología Celular y Molecular de Enfermedades, Instituto de Investigaciones Científicas y Servicios de Alta Tecnología (INDICASAT AIP), Panama City 0801, Panama.ORCID 0000-0002-5830-6315

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the 21st century, three highly pathogenic betacoronaviruses have emerged, with an alarming rate of human morbidity and case fatality. Genomic information has been widely used to understand the pathogenesis, animal origin and mode of transmission of coronaviruses in the aftermath of the 2002-2003 severe acute respiratory syndrome (SARS) and 2012 Middle East respiratory syndrome (MERS) outbreaks. Furthermore, genome sequencing and bioinformatic analysis have had an unprecedented relevance in the battle against the 2019-2020 coronavirus disease 2019 (COVID-19) pandemic, the newest and most devastating outbreak caused by a coronavirus in the history of mankind. Here, we review how genomic information has been used to tackle outbreaks caused by emerging, highly pathogenic, betacoronavirus strains, emphasizing on SARS-CoV, MERS-CoV and SARS-CoV-2. We focus on shared genomic features of the betacoronaviruses and the application of genomic information to phylogenetic analysis, molecular epidemiology and the design of diagnostic systems, potential drugs and vaccine candidates.

Indexed as

Genome, ViralAnimalsBetacoronavirusCoronavirus InfectionsCOVID-19Drug DesignGenes, ViralHumansMiddle East Respiratory Syndrome CoronavirusMolecular EpidemiologyPandemicsPhylogenyPneumonia, ViralSARS-CoV-2Severe Acute Respiratory SyndromeSevere acute respiratory syndrome-related coronavirusViral VaccinesbetacoronavirusesCOVID-19genomicsMERS-CoVSARS-CoVSARS-CoV-2

Identifiers

PMID32604724
PMCPMC7352669

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.