Evidence map›Paper›PMID 24459398›Full record

ReviewJournal of pharmacy & bioallied sciences2014

Farmed deer: A veterinary model for chronic mycobacterial diseases that is accessible, appropriate and cost-effective.

Frank Griffin

Open access · goldAbstract readReview
In one paragraph

Review in Journal of pharmacy & bioallied sciences, 2014. 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
0.4field-weighted citation impact, top 34% 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, 3 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

1 author at 1 institution in 2 countries.

Frank GriffinDepartment of Microbiology and Immunology, Disease Research Laboratory, University of Otago, Dunedin, New Zealand.
Christie's · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although most studies in immunology have used inbred mice as the experimental model to study fundamental immune mechanisms they have been proven to be limited in their ability to chart complex functional immune pathways, such as are seen in outbred populations of humans or animals. Translation of the findings from inbred mouse studies into practical solutions in therapeutics or the clinic has been remarkably unproductive compared with many other areas of clinical practice in human and veterinary medicine. Access to an unlimited array of mouse strains and an increasing number of genetically modified strains continues to sustain their paramount position in immunology research. Since the mouse studies have provided little more than the dictionary and glossary of immunology, another approach will be required to write the classic exposition of functional immunity. Domestic animals such as ruminants and swine present worthwhile alternatives as models for immunological research into infectious diseases, which may be more informative and cost effective. The original constraint on large animal research through a lack of reagents has been superseded by new molecular technologies and robotics that allow research to progress from gene discovery to systems biology, seamlessly. The current review attempts to highlight how exotic animals such as deer can leverage off the knowledge of ruminant genomics to provide cost-effective models for research into complex, chronic infections. The unique opportunity they provide relates to their diversity and polymorphic genotypes and the integrity of their phenotype for a range of infectious diseases.

Indexed as

Deerimmune markersinfectious diseasesvaccine development

Identifiers

PMID24459398
PMCPMC3895287
OpenAlexW2004725539

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.