Evidence map›Paper›PMID 32690096›Full record

ReviewInfectious diseases of poverty2020

Biological, clinical and epidemiological features of COVID-19, SARS and MERS and AutoDock simulation of ACE2.

Xue-Yan Zhang, Hao-Jie Huang, Dong-Lin Zhuang, Moussa Ide Nasser, Ming-Hua Yang, Ping Zhu, Ming-Yi Zhao

Open access · goldAbstract readReview
In one paragraph

Review in Infectious diseases of poverty, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed, 1 pooled it
1.9field-weighted citation impact, top 8% 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

41 citing papers in PubMed, 1 synthesis or guideline pooled it, 93 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Review
  6. Article
  7. Review
  8. Article
  9. Review
  10. Plants with antiviral properties used in Otorhinolaryngology.Revista medica del Instituto Mexicano del Seguro Social · 2024
    Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Small molecules in the treatment of COVID-19.Signal transduction and targeted therapy · 2022
    Review
  16. Review
  17. Review
  18. Bayesian spatial modeling of COVID-19 case-fatality rate inequalities.Spatial and spatio-temporal epidemiology · 2022
    Article
  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

7 authors at 2 institutions in 1 country.

Xue-Yan ZhangDepartment of Pediatrics, The Third Xiangya Hospital, Central South University, Changsha, 410013, Hunan, China.
Hao-Jie HuangXiangya School of Medicine, Central South University, Changsha, 410013, Hunan, China.
Dong-Lin ZhuangGuangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510100, Guangdong, China.
Moussa Ide NasserGuangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510100, Guangdong, China.
Ming-Hua YangDepartment of Pediatrics, The Third Xiangya Hospital, Central South University, Changsha, 410013, Hunan, China.
Ping ZhuGuangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510100, Guangdong, China. tanganqier@163.com.
Ming-Yi ZhaoDepartment of Pediatrics, The Third Xiangya Hospital, Central South University, Changsha, 410013, Hunan, China. 36163773@qq.com.ORCID http://orcid.org/0000-0002-2884-0736
Central South University · CNGuangdong Academy of Medical Sciences · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe outbreak of coronavirus disease 2019 (COVID-19) has caused a public catastrophe and global concern. The main symptoms of COVID-19 are fever, cough, myalgia, fatigue and lower respiratory tract infection signs. Almost all populations are susceptible to the virus, and the basic reproduction number (R

methodsThis review compares the multifaceted characteristics of the three coronaviruses including COVID-19, SARS and MERS. Our researchers take the COVID-19, SARS, and MERS as key words and search literatures in the Pubmed database. We compare them horizontally and vertically which respectively means concluding the individual characteristics of each coronavirus and comparing the similarities and differences between the three coronaviruses.

resultsWe searched for studies on each outbreak and their solutions and found that the main biological differences among SARS-CoV-2, SARS-CoV and MERS-CoV are in ORF1a and the sequence of gene spike coding protein-S. We also found that the types and severity of clinical symptoms vary, which means that the diagnosis and nursing measures also require differentiation. In addition to the common route of transmission including airborne transmission, these three viruses have their own unique routes of transmission such as fecal-oral route of transmission COVID-19.

conclusionsIn evolutionary history, these three coronaviruses have some similar biological features as well as some different mutational characteristics. Their receptors and routes of transmission are not all the same, which makes them different in clinical features and treatments. We discovered through the autodock simulations that Met124 plays a key role in the efficiency of drugs targeting ACE2, such as remdesivir, chloroquine, ciclesonide and niclosamide, and may be a potential target in COVID-19.

Indexed as

Coronavirus InfectionsPandemicsPneumonia, ViralSevere Acute Respiratory SyndromeAngiotensin-Converting Enzyme 2AnimalsAntiviral AgentsBetacoronavirusClinical Laboratory TechniquesClinical Trials as TopicCOVID-19COVID-19 Drug TreatmentCOVID-19 TestingDisease ReservoirsHumansMiddle East Respiratory Syndrome CoronavirusACE2 protein, humanAngiotensin-Converting Enzyme 2Antiviral AgentsPeptidyl-Dipeptidase AReceptors, CoronavirusReceptors, VirusAutodockCoronavirusCOVID-19MERSSARS

Identifiers

PMID32690096
PMCPMC7369569
OpenAlexW3043177876

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.