Evidence map›Paper›PMID 29170660›Full record

ArticleFrontiers in microbiology2017

Effect of Dietary Forage to Concentrate Ratios on Dynamic Profile Changes and Interactions of Ruminal Microbiota and Metabolites in Holstein Heifers.

Jun Zhang, Haitao Shi, Yajing Wang, Shengli Li, Zhijun Cao, Shoukun Ji, Yuan He, Hongtao Zhang

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in microbiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 124 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
124citing papers in PubMed, 1 pooled it
15.5field-weighted citation impact, top 1% 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

124 citing papers in PubMed, 1 synthesis or guideline pooled it, 183 citations in OpenAlex.

  1. Pooled it
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64 more citing papers are in PubMed but not listed here.

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

8 authors at 2 institutions in 2 countries.

Jun ZhangState Key Laboratory of Animal Nutrition, Beijing Engineering Technology Research Center of Raw Milk Quality and Safety Control, College of Animal Science and Technology, China Agricultural University, Beijing, China.
Haitao ShiState Key Laboratory of Animal Nutrition, Beijing Engineering Technology Research Center of Raw Milk Quality and Safety Control, College of Animal Science and Technology, China Agricultural University, Beijing, China.
Yajing WangState Key Laboratory of Animal Nutrition, Beijing Engineering Technology Research Center of Raw Milk Quality and Safety Control, College of Animal Science and Technology, China Agricultural University, Beijing, China.
Shengli LiState Key Laboratory of Animal Nutrition, Beijing Engineering Technology Research Center of Raw Milk Quality and Safety Control, College of Animal Science and Technology, China Agricultural University, Beijing, China.
Zhijun CaoState Key Laboratory of Animal Nutrition, Beijing Engineering Technology Research Center of Raw Milk Quality and Safety Control, College of Animal Science and Technology, China Agricultural University, Beijing, China.
Shoukun JiState Key Laboratory of Animal Nutrition, Beijing Engineering Technology Research Center of Raw Milk Quality and Safety Control, College of Animal Science and Technology, China Agricultural University, Beijing, China.
Yuan HeState Key Laboratory of Animal Nutrition, Beijing Engineering Technology Research Center of Raw Milk Quality and Safety Control, College of Animal Science and Technology, China Agricultural University, Beijing, China.
Hongtao ZhangState Key Laboratory of Animal Nutrition, Beijing Engineering Technology Research Center of Raw Milk Quality and Safety Control, College of Animal Science and Technology, China Agricultural University, Beijing, China.
China Agricultural University · CNState Key Laboratory of Animal Nutrition

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A better understanding of global ruminal microbiota and metabolites under extensive feeding conditions is a prerequisite for optimizing rumen function and improving ruminant feed efficiency. Furthermore, the gap between the information on the ruminal microbiota and metabolites needs to be bridged. The aim of this study was to investigate the effects of a wide range of forage to concentrate ratios (F:C) on changes and interactions of ruminal microbiota and metabolites. Four diets with different F:C (80:20, 60:40, 40:60, and 20:80) were limit-fed to 24 Holstein heifers, and Illumina MiSeq sequencing and gas chromatography time-of-flight/mass spectrometry were used to investigate the profile changes of the ruminal microbes and metabolites, and the interaction between them. The predominant bacterial phyla in the rumen were

Indexed as

forage to concentrate ratioheiferhigh concentraterumen metabolomicsrumen microbiome

Identifiers

PMID29170660
PMCPMC5684179
OpenAlexW2767073498

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.