Evidence map›Paper›PMID 30774267›Full record

ReviewJournal of clinical and experimental hepatology

Methods for Studying Gut Microbiota: A Primer for Physicians.

Aditya N Sarangi, Amit Goel, Rakesh Aggarwal

Abstract readReview
In one paragraph

Review in Journal of clinical and experimental hepatology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

27 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Trial
  4. Trial
  5. Article
  6. Review
  7. Review
  8. Review
  9. Article
  10. Review
  11. Review
  12. A Proteogenomic Approach to Unveiling the Complex Biology of the Microbiome.International journal of molecular sciences · 2024
    Review
  13. Article
  14. Article
  15. Analysis of the Nasal Microbiota in Healthy and Diseased Pigs.Methods in molecular biology (Clifton, N.J.) · 2024
    Article
  16. Review
  17. Review
  18. Review
  19. BioMed research international · 2022
    Review
  20. 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

3 authors.

Aditya N SarangiBiomedical Informatics Center, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow 226014, India.
Amit GoelDepartment of Gastroenterology, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow 226014, India.
Rakesh AggarwalBiomedical Informatics Center, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow 226014, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Human gastrointestinal tract contains a large variety of microbes, in particular bacteria. Studies in recent years have strongly suggested a role for these microbes, collectively referred to as gut microbiota, in the maintenance of homeostasis during health. In addition, alterations in gut microbiota have been reported in several diseases, including those related to the gastrointestinal tract and several systemic conditions, and are believed to play a pathogenetic role in at least some of these. Given the close association between the human gut and liver, the association with gut microbiota appears to be particularly strong for a wide variety of liver diseases. This piece, aimed primarily at physicians, reviews in brief the methods used to study gut microbiota, with particular emphasis on those that use sequences of bacterial 16S rRNA gene or its components.

Indexed as

16S rRNA16S rRNA data analysis, microbial diversityBDI, Beta Diversity Indexgut microbiotametagenomenext generation sequencingOTUs, Operational Taxonomic UnitsPCR, Polymerase Chain Reaction

Identifiers

PMID30774267
PMCPMC6363981

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.