Evidence map›Paper›PMID 33011361›Full record

ReviewMicrobial pathogenesis2020

Porcine epidemic diarrhea virus: Molecular mechanisms of attenuation and vaccines.

Zhiwei Li, Zhiqian Ma, Yang Li, Sheng Gao, Shuqi Xiao

Abstract readReview
In one paragraph

Review in Microbial pathogenesis, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 93 papers.

0numbers the graph read from it
0cells of the map it votes in
93citing papers in PubMed
9.2field-weighted citation impact, top 1% 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

93 citing papers in PubMed, 148 citations in OpenAlex.

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33 more citing papers are in PubMed but not listed here.

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

5 authors at 2 institutions in 1 country.

Zhiwei LiCollege of Veterinary Medicine, Northwest A&F University, Yangling, Shaanxi, China.
Zhiqian MaCollege of Veterinary Medicine, Northwest A&F University, Yangling, Shaanxi, China.
Yang LiCollege of Veterinary Medicine, Northwest A&F University, Yangling, Shaanxi, China.
Sheng GaoCollege of Veterinary Medicine, Northwest A&F University, Yangling, Shaanxi, China.
Shuqi XiaoCollege of Veterinary Medicine, Northwest A&F University, Yangling, Shaanxi, China. Electronic address: xiaoshuqi@nwsuaf.edu.cn.
Northwest A&F University · CNNorth West Agriculture and Forestry University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Porcine epidemic diarrhea virus (PEDV) causes an emerging and re-emerging coronavirus disease characterized by vomiting, acute diarrhea, dehydration, and up to 100% mortality in neonatal suckling piglets, leading to huge economic losses in the global swine industry. Vaccination remains the most promising and effective way to prevent and control PEDV. However, effective vaccines for PEDV are still under development. Understanding the genomic structure and function of PEDV and the influence of the viral components on innate immunity is essential for developing effective vaccines. In the current review, we systematically describe the recent developments in vaccine against PEDV and the roles of structural proteins, non-structural proteins and accessory proteins of PEDV in affecting viral virulence and regulating innate immunity, which will provide insight into the rational design of effective and safe vaccines for PEDV or other coronaviruses.

Indexed as

AnimalsCoronavirus InfectionsImmunity, InnatePorcine epidemic diarrhea virusSwineSwine DiseasesVaccinationVaccines, AttenuatedViral ProteinsViral VaccinesVirulenceVaccines, AttenuatedViral ProteinsViral VaccinesGeneticsPorcine epidemic diarrhea virusVaccineVirulence

Identifiers

PMID33011361
PMCPMC7527827
OpenAlexW3090058219

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.