Evidence map›Paper›PMID 41404529›Full record

ArticleFood science & nutrition2025

Metabolites in Longissimus Lumborum From Beef Cattle Differ in Fat Content.

Zhen Ma, Fanrong Cui, Lei Chen, Xiao Wang, Wenjie Yu, Hao Jiang, Zongsheng Zhao, Xiangmin Yan

Abstract read
In one paragraph

Article in Food science & nutrition, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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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

8 authors.

Zhen MaCollege of Animal Science and Technology Shihezi University Shihezi Xinjiang China.
Fanrong CuiInstitute of Animal Husbandry Xinjiang Academy of Animal Husbandry Urumqi Xinjiang China.
Lei ChenCollege of Animal Science and Technology Shihezi University Shihezi Xinjiang China.
Xiao WangYili Vocational and Technical College Yili Xinjiang China.
Wenjie YuCollege of Animal Sciences Jilin University Changchun Jilin China.
Hao JiangCollege of Animal Sciences Jilin University Changchun Jilin China.
Zongsheng ZhaoCollege of Animal Science and Technology Shihezi University Shihezi Xinjiang China.
Xiangmin YanInstitute of Animal Husbandry Xinjiang Academy of Animal Husbandry Urumqi Xinjiang China.ORCID https://orcid.org/0000-0002-8085-8941

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Improving meat quality is an important goal in beef production. Therefore, a deeper understanding of the biochemical characteristics that drive muscle development and fat deposition and their effects on final quality is important in the fields of meat science and animal production. Recent research has shown that metabolites can be utilized as biological indicators for measuring meat quality. Therefore, the general meat quality, texture profile, and differentially abundant metabolites in longissimus lumborum from 10 Kazakh (with low fat content) cattle (KAZ) and 10 Xinjiang brown (with high fat content) cattle (BC) were analyzed. A total of 800 metabolites were detected, among which were 47 differentially abundant metabolites (DAMs), including 1 amine, 1 heterocyclic compound, 1 tryptamine choline pigment, 18 amino acid derivatives, 3 benzene and its substituted derivatives, 5 fatty acyls, 3 glycoproteins, 5 nucleotides and their metabolites, 5 organic acids and their derivatives, and 5 carbohydrates and their metabolites. The top 5 up- and downregulated DAMs between the two breeds included Arg-Lys, Pro-Glu-Val, 4-(aminomethyl) indole, N6-(2-hydroxyethyl) adenosine, methyldopa, and biliverdin, which are related to metabolic pathways such as arginine and proline metabolism, galactose metabolism, endocrine resistance, and glycerolipid metabolism, potentially affecting meat quality, including sensory acceptability. These results suggest that metabolites are potentially useful biological indicators for measuring meat quality and provide an important theoretical basis for improving beef flavor and taste.

Indexed as

differentially abundant metaboliteslongissimus lumborummeat qualitytexture profile analysis

Identifiers

PMID41404529
PMCPMC12704019

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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.