Evidence map›Paper›PMID 35103810›Full record

ReviewApplied microbiology and biotechnology2022

Non-primate animal models for pertussis: back to the drawing board?

Nevio Cimolai

Open access · bronzeAbstract readReview
In one paragraph

Review in Applied microbiology and biotechnology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 48% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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

1 author at 1 institution in 1 country.

Nevio CimolaiFaculty of Medicine, The University of British Columbia, Vancouver, Canada. ncimolai@mail.ubc.ca.ORCID http://orcid.org/0000-0003-2743-0556
University of British Columbia · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite considerable progress in the understanding of clinical pertussis, the contemporary emergence of antimicrobial resistance for Bordetella pertussis and an evolution of concerns with acellular component vaccination have both sparked a renewed interest. Although simian models of infection best correlate with the observed attributes of human infection, several animal models have been used for decades and have positively contributed in many ways to the related science. Nevertheless, there is yet the lack of a reliable small animal model system that mimics the combination of infection genesis, variable upper and lower respiratory infection, systemic effects, infection resolution, and vaccine responses. This narrative review examines the history and attributes of non-primate animal models for pertussis and places context with the current use and needs. Emerging from the latter is the necessity for further such study to better create the optimal model of infection and vaccination with use of current molecular tools and a broader range of animal systems. KEY POINTS: • Currently used and past non-primate animal models of B. pertussis infection often have unique and focused applications. • A non-primate animal model that consistently mimics human pertussis for the majority of key infection characteristics is lacking. • There remains ample opportunity for an improved non-primate animal model of pertussis with the use of current molecular biology tools and with further exploration of species not previously considered.

Indexed as

Whooping CoughAnimalsBordetella pertussisDisease Models, AnimalHumansPertussis VaccineVaccinationPertussis VaccineBordetella pertussisColonizationInfectionModelPathogenesis

Identifiers

PMID35103810
PMCPMC8803574
OpenAlexW4213135463

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.