Evidence map›Paper›PMID 40896481›Full record

ArticleAnimal nutrition (Zhongguo xu mu shou yi xue hui)2025

Differential lipid metabolism in beef cattle: A comparative study of high and low residual feed intake bulls.

Xin Yi, Simeng Yi, Jinze Wang, Boping Ye, Xiaowen Zhu, Qingxiang Meng, Hao Wu, Zhenming Zhou

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Animal nutrition (Zhongguo xu mu shou yi xue hui), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

8 authors.

Xin YiState Key Laboratory of Animal Nutrition and Feeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China.
Simeng YiState Key Laboratory of Animal Nutrition and Feeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China.
Jinze WangState Key Laboratory of Animal Nutrition and Feeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China.
Boping YeState Key Laboratory of Animal Nutrition and Feeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China.
Xiaowen ZhuState Key Laboratory of Animal Nutrition and Feeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China.
Qingxiang MengState Key Laboratory of Animal Nutrition and Feeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China.
Hao WuState Key Laboratory of Animal Nutrition and Feeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China.
Zhenming ZhouState Key Laboratory of Animal Nutrition and Feeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study investigated lipid metabolism differences between low and high residual feed intake (LRFI and HRFI) bulls. Fifty-five Simmental bulls (449.84 ± 8.49 kg) were fed the same diet for 161 d to determine RFI values. At the end of experiment, back fat thickness (BFT) and rib eye area (REA) were measured via ultrasound, and serum samples were collected for lipid metabolism indicators. Post-slaughter, subcutaneous adipose tissue was analyzed for lipid metabolism indicators, histology, transcriptomics, and lipid metabolomics. Results 1) Ultrasound showed LRFI bulls had lower BFT (

Indexed as

Beef cattleLipid metabolismResidual feed intake

Identifiers

PMID40896481
PMCPMC12391812

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.