Evidence map›Paper›PMID 26542532›Full record

SynthesisCurrent microbiology2016

A Meta-analysis of Bacterial Diversity in the Feces of Cattle.

Minseok Kim, James E Wells

Abstract readMeta-Analysis
PubMed Publisher
In one paragraph

Synthesis in Current microbiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
–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

34 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Longitudinal assessment of the prevalence ofFrontiers in microbiology · 2025
    Article
  6. Article
  7. Uncovering newMicrobiology spectrum · 2024
    Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Gut microbiota and meat quality.Frontiers in microbiology · 2022
    Review
  19. Review
  20. Composition of Fecal Microbiota in Grazing and Feedlot Angus Beef Cattle.Animals : an open access journal from MDPI · 2021
    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

2 authors.

Minseok KimU.S. Department of Agriculture, U.S. Meat Animal Research Center, P.O. Box 166, State Spur 18D, Clay Center, NE, 68933, USA.
James E WellsU.S. Department of Agriculture, U.S. Meat Animal Research Center, P.O. Box 166, State Spur 18D, Clay Center, NE, 68933, USA. Jim.Wells@ars.usda.gov.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this study, we conducted a meta-analysis on 16S rRNA gene sequences of bovine fecal origin that are publicly available in the RDP database. A total of 13,663 sequences including 603 isolate sequences were identified in the RDP database (Release 11, Update 1), where 13,447 sequences were assigned to 10 phyla, 17 classes, 28 orders, 59 families, and 110 genera, while the remaining 216 sequences could not be assigned to a known phylum. Firmicutes and Bacteroidetes were the first and the second predominant phyla, respectively. About 41 % of the total sequences could not be assigned to a known genus. The total sequences were assigned to 1252 OTUs at 97 % sequence similarity. A small number of OTUs shared among datasets indicate that fecal bacterial communities of cattle are greatly affected by various factors, specifically diet. This study may guide future studies to further analyze fecal bacterial communities of cattle.

Indexed as

BiodiversityAnimalsBacteriaCattleCluster AnalysisDNA, BacterialDNA, RibosomalFecesMolecular Sequence DataPhylogenyRNA, Ribosomal, 16SSequence Analysis, DNADNA, BacterialDNA, RibosomalRNA, Ribosomal, 16S

Identifiers

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.