Evidence map›Paper›PMID 27525065›Full record

ReviewClinical & translational immunology2016

Experimental design considerations in microbiota/inflammation studies.

Robert J Moore, Dragana Stanley

Open access · goldAbstract readReview
In one paragraph

Review in Clinical & translational immunology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 1 pooled it
4.2field-weighted citation impact, top 6% 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

25 citing papers in PubMed, 1 synthesis or guideline pooled it, 52 citations in OpenAlex.

  1. Pooled it
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  9. Microbiome-Friend or Foe of Pancreatic Cancer?Journal of clinical medicine · 2021
    Review
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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 2 institutions in 2 countries.

Robert J MooreSchool of Science, RMIT University, Bundoora, Victoria, Australia; Infection and Immunity Program, Monash Biomedicine Discovery Institute and Department of Microbiology, Monash University, Clayton, Victoria, Australia.
Dragana StanleySchool of Medical and Applied Sciences, Central Queensland University, Rockhampton , Queensland, Australia.
Central Queensland University · AUDiscovery Institute · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There is now convincing evidence that many inflammatory diseases are precipitated, or at least exacerbated, by unfavourable interactions of the host with the resident microbiota. The role of gut microbiota in the genesis and progression of diseases such as inflammatory bowel disease, obesity, metabolic syndrome and diabetes have been studied both in human and in animal, mainly rodent, models of disease. The intrinsic variation in microbiota composition, both within one host over time and within a group of similarly treated hosts, presents particular challenges in experimental design. This review highlights factors that need to be taken into consideration when designing animal trials to investigate the gastrointestinal tract microbiota in the context of inflammation studies. These include the origin and history of the animals, the husbandry of the animals before and during experiments, details of sampling, sample processing, sequence data acquisition and bioinformatic analysis. Because of the intrinsic variability in microbiota composition, it is likely that the number of animals required to allow meaningful statistical comparisons across groups will be higher than researchers have generally used for purely immune-based analyses.

Identifiers

PMID27525065
PMCPMC4973323
OpenAlexW2486179031

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.