Evidence map›Paper›PMID 38064037›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2024

Recovery of Recombinant Rotaviruses by Reverse Genetics.

Chantal A Agbemabiese, Asha A Philip, John T Patton

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2024. 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
6.9field-weighted citation impact, top 3% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Review
  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

3 authors at 1 institution in 2 countries.

Chantal A AgbemabieseNoguchi Memorial Institute for Medical Research, University of Ghana, Accra, Ghana.
Asha A PhilipDepartment of Biology, Indiana University, Bloomington, IN, USA.
John T PattonDepartment of Biology, Indiana University, Bloomington, IN, USA. jtpatton@iu.edu.
Indiana University Bloomington · US

Funding

Rotavirus Vaccines Engineered as Vectors Against Other Enteric DiseasesR21AI144881 · NIAID · TRUSTEES OF INDIANA UNIVERSITY · PI PATTON, JOHN THOMAS · 2019 to 2020
$413k
NIAID NIH HHS R21 AI144881
6 · The paper itself

Abstract

Rotaviruses are the primary cause of severe gastroenteritis in infants and young children throughout the world. To combat rotavirus illness, several live oral vaccines have been developed, or are under development, that are formulated from attenuated human or human-animal reassortant strains of rotavirus. While the effectiveness of these vaccines is generally high in developed countries, the same vaccines are significantly less effective in many developing countries, where the need for rotavirus vaccines is greatest. Recently, reverse genetics systems have been developed that allow modification of the segmented double-stranded (ds)RNA genome of rotavirus, including reprogramming the genome to allow expression of additional proteins that may stimulate expanded neutralizing antibody responses in vaccinated children. The use of reverse genetics systems may not only lead to the development of more potent classes of vaccines but can be used to better explore the intricacies of rotavirus molecular biology and pathogenesis. In this article, we share protocols that can be used to generate recombinant rotaviruses, including modified strains that express foreign proteins.

Indexed as

GastroenteritisRotavirusRotavirus InfectionsVaccinesAnimalsChildChild, PreschoolHumansInfantReverse GeneticsVaccinesDouble-stranded RNAdsRNAGastroenteritisReverse geneticsRotavirusSegmented genome

Identifiers

PMID38064037
OpenAlexW4389484961

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.