Evidence map›Paper›PMID 36119040›Full record

ReviewFrontiers in immunology2022

Potential mouse models of coronavirus-related immune injury.

Fu-Yao Nan, Cai-Jun Wu, Jia-Hui Su, Lin-Qin Ma

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.3field-weighted citation impact, top 44% 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

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

4 authors at 1 institution in 1 country.

Fu-Yao NanDongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China.
Cai-Jun WuDepartment of Emergency Medicine, Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China.
Jia-Hui SuDongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China.
Lin-Qin MaDepartment of Emergency Medicine, Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China.
Dongzhimen Hospital Affiliated to Beijing University of Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Basic research for prevention and treatment of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), continues worldwide. In particular, multiple newly reported cases of autoimmune-related diseases after COVID-19 require further research on coronavirus-related immune injury. However, owing to the strong infectivity of SARS-CoV-2 and the high mortality rate, it is difficult to perform relevant research in humans. Here, we reviewed animal models, specifically mice with coronavirus-related immune disorders and immune damage, considering aspects of coronavirus replacement, viral modification, spike protein, and gene fragments. The evaluation of mouse models of coronavirus-related immune injury may help establish a standardised animal model that could be employed in various areas of research, such as disease occurrence and development processes, vaccine effectiveness assessment, and treatments for coronavirus-related immune disorders. COVID-19 is a complex disease and animal models cannot comprehensively summarise the disease process. The application of genetic technology may change this status.

Indexed as

COVID-19Spike Glycoprotein, CoronavirusAnimalsDisease Models, AnimalHumansMiceSARS-CoV-2Spike Glycoprotein, Coronavirusspike protein, SARS-CoV-2coronavirusCOVID-19immune injurymouse modelSARS-CoV-2

Identifiers

PMID36119040
PMCPMC9478437
OpenAlexW4294204256

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.