Evidence map›Paper›PMID 36920691›Full record

ReviewAdvances in experimental medicine and biology2023

Application of Pseudotyped Viruses.

Qianqian Cui, Weijin Huang

Abstract readReview
PubMed Publisher
In one paragraph

Review in Advances in experimental medicine and biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

2 authors.

Qianqian CuiDivision of HIV/AIDS and Sex-transmitted Virus Vaccines, National Institutes for Food and Drug Control (NIFDC) and WHO Collaborating Center for Standardization and Evaluation of Biologicals, Beijing, China.
Weijin HuangDivision of HIV/AIDS and Sex-transmitted Virus Vaccines, National Institutes for Food and Drug Control (NIFDC) and WHO Collaborating Center for Standardization and Evaluation of Biologicals, Beijing, China. huangweijin@nifdc.org.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Highly pathogenic emerging and reemerging viruses have serious public health and socioeconomic implications. Although conventional live virus research methods can more reliably investigate disease pathogenicity and evaluate antiviral products, they usually depend on high-level biosafety laboratories and skilled researchers; these requirements hinder in vitro assessments of efficacy, as well as efforts to test vaccines and antibody drugs. In contrast, pseudotyped viruses (i.e., single-round infectious viruses that mimic the membrane structures of various live viruses) are widely used in studies of highly pathogenic viruses because they can be handled in biosafety level 2 facilities. This chapter provides a concise overview of various aspects of pseudotyped virus technologies, including (1) exploration of the mechanisms of viral infection; (2) evaluation of the efficacies of vaccines and monoclonal antibodies based on pseudovirion-based neutralization assay; (3) assessment of antiviral agents (i.e., antibody-based drugs and inhibitors); (4) establishment of animal models of pseudotyped virus infection in vivo; (5) investigation of the evolution, infectivity, and antigenicity of viral variants and viral glycosylation; and (6) prediction of antibody-dependent cell-mediated cytotoxic activity.

Indexed as

AntigensViral PseudotypingAnimalsAntibodies, NeutralizingAntibodies, ViralNeutralization TestsAntibodies, NeutralizingAntibodies, ViralAntigensApplicationInfection mechanismIn vitroIn vivoNeutralizing antibodiesPseudotyped virus

Identifiers

PMID36920691

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.