Evidence map›Paper›PMID 33193526›Full record

ArticleFrontiers in plant science2020

Efficient Plant Production of Recombinant NS1 Protein for Diagnosis of Dengue.

Mariana Fonseca Xisto, Roberto Sousa Dias, Elias Feitosa-Araujo, John Willians Oliveira Prates, Cynthia Canedo da Silva, Sérgio Oliveira de Paula

Open access · goldAbstract read
In one paragraph

Article in Frontiers in plant science, 2020. 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
0.7field-weighted citation impact, top 30% 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, 7 citations in OpenAlex.

  1. Biotechnology reports (Amsterdam, Netherlands) · 2024
    Article
  2. Article
  3. Review
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

6 authors at 1 institution in 1 country.

Mariana Fonseca XistoDepartment of General Biology, Federal University of Viçosa, Viçosa, Brazil.
Roberto Sousa DiasDepartment of General Biology, Federal University of Viçosa, Viçosa, Brazil.
Elias Feitosa-AraujoDepartment of Plant Biology, Federal University of Viçosa, Viçosa, Brazil.
John Willians Oliveira PratesDepartment of Microbiology, Federal University of Viçosa, Viçosa, Brazil.
Cynthia Canedo da SilvaDepartment of Microbiology, Federal University of Viçosa, Viçosa, Brazil.
Sérgio Oliveira de PaulaDepartment of General Biology, Federal University of Viçosa, Viçosa, Brazil.
Universidade Federal de Viçosa · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dengue fever is endemic in more than 120 countries, which account for 3.9 billion people at risk of infection worldwide. The absence of a vaccine with effective protection against the four serotypes of this virus makes differential molecular diagnosis the key step for the correct treatment of the disease. Rapid and efficient diagnosis prevents progression to a more severe stage of this disease. Currently, the limiting factor in the manufacture of dengue (DENV) diagnostic kits is the lack of large-scale production of the non-structural 1 (NS1) protein (antigen) to be used in the capture of antibodies from the blood serum of infected patients. In this work, we use plant biotechnology and genetic engineering as tools for the study of protein production for research and commercial purposes. Gene transfer, integration and expression in plants is a valid strategy for obtaining large-scale and low-cost heterologous protein production. The authors produced NS1 protein of the dengue virus serotype 2 (NS1DENV2) in the

Indexed as

Arabidopsis thalianadenguediagnosis 2NS1 proteinplant expression

Identifiers

PMID33193526
PMCPMC7649140
OpenAlexW3096288141

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.