Evidence map›Paper›PMID 35454245›Full record

ReviewAnimals : an open access journal from MDPI2022

Nutritional Modulation, Gut, and Omics Crosstalk in Ruminants.

Mohamed Abdelrahman, Wei Wang, Aftab Shaukat, Muhammad Fakhar-E-Alam Kulyar, Haimiao Lv, Adili Abulaiti, Zhiqiu Yao, Muhammad Jamil Ahmad, Aixin Liang, Liguo Yang

Open access · goldAbstract readReview
In one paragraph

Review in Animals : an open access journal from MDPI, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.9field-weighted citation impact, top 31% 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

3 citing papers in PubMed, 9 citations in OpenAlex.

  1. Big Data and AI-Powered Modeling: A Pathway to Sustainable Precision Animal Nutrition.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Review
  2. Article
  3. Review
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

10 authors at 1 institution in 2 countries.

Mohamed AbdelrahmanKey Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agriculture University, Wuhan 430070, China.ORCID 0000-0001-6860-3543
Wei WangKey Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agriculture University, Wuhan 430070, China.
Aftab ShaukatKey Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agriculture University, Wuhan 430070, China.ORCID 0000-0003-1670-6916
Muhammad Fakhar-E-Alam KulyarCollege of Veterinary Medicine, Huazhong Agricultural University, Wuhan 430070, China.ORCID 0000-0002-9512-5230
Haimiao LvKey Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agriculture University, Wuhan 430070, China.
Adili AbulaitiKey Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agriculture University, Wuhan 430070, China.ORCID 0000-0002-1898-7945
Zhiqiu YaoKey Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agriculture University, Wuhan 430070, China.
Muhammad Jamil AhmadKey Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agriculture University, Wuhan 430070, China.ORCID 0000-0002-5986-8635
Aixin LiangKey Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agriculture University, Wuhan 430070, China.
Liguo YangKey Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agriculture University, Wuhan 430070, China.ORCID 0000-0003-1389-4640
Huazhong Agricultural University · CN

Funding

China Agriculture Research System of MOF and MARA China Agriculture Research System of MOF and MARA
6 · The paper itself

Abstract

Ruminant nutrition has significantly revolutionized a new and prodigious molecular approach in livestock sciences over the last decade. Wide-spectrum advances in DNA and RNA technologies and analysis have produced a wealth of data that have shifted the research threshold scheme to a more affluent level. Recently, the published literature has pointed out the nutrient roles in different cellular genomic alterations among different ruminant species, besides the interactions with other factors, such as age, type, and breed. Additionally, it has addressed rumen microbes within the gut health and productivity context, which has made interpreting homogenous evidence more complicated. As a more systematic approach, nutrigenomics can identify how genomics interacts with nutrition and other variables linked to animal performance. Such findings should contribute to crystallizing powerful interpretations correlating feeding management with ruminant production and health through genomics. This review will present a road-mapping discussion of promising trends in ruminant nutrigenomics as a reference for phenotype expression through multi-level omics changes.

Indexed as

feedomicsgene expressionnutrigenomicsnutritionruminanttranscriptome

Identifiers

PMID35454245
PMCPMC9029867
OpenAlexW4223451731

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.