Evidence map›Paper›PMID 35734184›Full record

ArticleFrontiers in immunology2022

New Avenues to Design

David Arranz-Solís, Jeroen P J Saeij

Open access · goldAbstract read
In one paragraph

Article 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 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.2field-weighted citation impact, top 26% 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

5 citing papers in PubMed, 7 citations in OpenAlex.

  1. Review
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  3. Article
  4. Advances towards the completeFaculty reviews · 2023
    Review
  5. 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

2 authors at 1 institution in 1 country.

David Arranz-SolísPathology, Microbiology and Immunology department, School of Veterinary Medicine, University of California Davis, Davis, CA, United States.
Jeroen P J SaeijPathology, Microbiology and Immunology department, School of Veterinary Medicine, University of California Davis, Davis, CA, United States.
University of California, Davis · US

Funding

Regulatory factors that determine Toxoplasma bradyzoite to merozoites conversion.R21AI139387 · NIAID · UNIVERSITY OF CALIFORNIA AT DAVIS · PI SAEIJ, JEROEN · 2018 to 2019
$432k
NIAID NIH HHS R21 AI139387
6 · The paper itself

Abstract

Toxoplasmosis is a worldwide disease affecting all warm-blooded animals, including humans. Vaccination strategies aimed at inducing an efficient immune response while preventing transmission have been attempted in the past. While many different approaches can partially protect immunized animals against subsequent infections, full and lasting protection is rarely attained and only with live-attenuated vaccines. In addition, vaccines based on mutant strains that are deficient in forming the chronic phase of the parasite (such as Toxovax™) cannot be extensively used due to their zoonotic potential and the possibility of reversion to virulent phenotypes. An increasing number of studies using emerging genetic-engineering tools have been conducted to design novel vaccines based on recombinant proteins, DNA or delivery systems such as nanoparticles. However, these are usually less efficient due to their antigenic simplicity. In this perspective article we discuss potential target genes and novel strategies to generate live-attenuated long-lasting vaccines based on tissue cysts and oocysts, which are the environmentally resistant chronic forms of

Indexed as

CystsProtozoan VaccinesToxoplasmaToxoplasmosis, AnimalAnimalsMiceOocystsVaccines, AttenuatedProtozoan VaccinesVaccines, AttenuatedcatsCRISPR/Cas9cystsoocystssporozoitesToxoplasmavaccine

Identifiers

PMID35734184
PMCPMC9207213
OpenAlexW4281921167

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.