Evidence map›Paper›PMID 34941021›Full record

ArticleCurrent protocols2021

Guinea Pig Model of Mycobacterium tuberculosis Infection.

Elizabeth Creissen, Linda Izzo, Clinton Dawson, Angelo A Izzo

Erratum issuedAbstract read
PubMed Publisher
In one paragraph

Article in Current protocols, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.3field-weighted citation impact, top 38% 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

6 citing papers in PubMed, 9 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 2 countries.

Elizabeth CreissenColorado State University, Fort Collins, Colorado.
Linda IzzoColorado State University, Fort Collins, Colorado.
Clinton DawsonColorado State University, Fort Collins, Colorado.
Angelo A IzzoColorado State University, Fort Collins, Colorado.
Colorado State University · USUniversity of Sydney · AU

Funding

NIAIDNIH
6 · The paper itself

Abstract

Guinea pigs have been used as a model for Mycobacterium tuberculosis infection for many years and have been more recently adopted as a model for testing new tuberculosis (TB) vaccines. From the time of Robert Koch, who used guinea pigs to test theories about the newly discovered pathogen, the guinea pig has modeled active human infections, as it is susceptible to infection with low numbers of organisms. This article describes the modern use of the guinea pig to examine the pathology of the disease and the protocols used to examine specific outcomes associated with aerosol infection with virulent M. tuberculosis. The guinea pig is used extensively to investigate the ability of new TB vaccines to reduce TB disease, and two models have been employed. The first is the long-term disease model, in which vaccinated guinea pigs are monitored for disease after infection, and the second is the short-term assessment of mycobacterial burden model, which can determine the ability of a vaccine to reduce organism burden. © 2021 Wiley Periodicals LLC. Basic Protocol 1: Preparation of virulent Mycobacterium tuberculosis seed stocks for animal infections Basic Protocol 2: Preparation of virulent Mycobacterium tuberculosis working stocks for animal infections Basic Protocol 3: Preparation of M. tuberculosis for aerosol infection of guinea pigs Basic Protocol 4: Injection of guinea pigs Basic Protocol 5: Blood collection from live guinea pigs Basic Protocol 6: Guinea pig euthanasia.

Indexed as

Mycobacterium tuberculosisTuberculosisTuberculosis VaccinesAnimalsDisease Models, AnimalGuinea PigsTuberculosis Vaccinesguinea pigimmune responseMycobacterium tuberculosispulmonary infectionvaccinationvaccines

Identifiers

PMID34941021
OpenAlexW4200557366

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.