Evidence map›Paper›PMID 39590814›Full record

ArticleMetabolites2024

Effects of Acorns on Meat Quality and Lipid Metabolism-Related Gene Expression in Muscle Tissues of Yuxi Black Pigs.

Zhe Sun, Yadi Chang, Luyao Huang, Siyuan An, Dongyang Liu, Jinzhou Zhang, Zhiguo Miao

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Metabolites, 2024. 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
–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

3 citing papers in PubMed.

  1. Article
  2. Article
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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

7 authors.

Zhe SunCollege of Animal Science and Veterinary Medicine, Henan Institute of Science and Technology, Xinxiang 453003, China.ORCID 0009-0005-5978-8300
Yadi ChangCollege of Animal Science and Veterinary Medicine, Henan Institute of Science and Technology, Xinxiang 453003, China.
Luyao HuangCollege of Animal Science and Veterinary Medicine, Henan Institute of Science and Technology, Xinxiang 453003, China.
Siyuan AnCollege of Animal Science and Veterinary Medicine, Henan Institute of Science and Technology, Xinxiang 453003, China.
Dongyang LiuCollege of Animal Science and Veterinary Medicine, Henan Institute of Science and Technology, Xinxiang 453003, China.
Jinzhou ZhangCollege of Animal Science and Veterinary Medicine, Henan Institute of Science and Technology, Xinxiang 453003, China.
Zhiguo MiaoCollege of Animal Science and Veterinary Medicine, Henan Institute of Science and Technology, Xinxiang 453003, China.

Funding

Innovative Research Team (in Science and Technology) in University of Henan Province 22IRTSTHN026Provincial key Technology Research and development program of Henan 232102111055the Pig Industry Technology System Innovation Team Project of Henan Province HARS-22-12-G1
6 · The paper itself

Abstract

objectivesThe aim of this study was to investigate the effects of acorn diets on the composition of fatty acid (FA) and the intramuscular fat (IMF) content in Yuxi black pigs.

methodsNinety Yuxi black pigs with similar body weight (99.60 ± 2.32 kg) were randomly divided into five groups. The control group was fed a basal diet, and the AD20, AD30, AD40, and AD50 groups were fed experimental diets which contained 20%, 30%, 40%, and 50% acorns, respectively. The feeding experiment lasted for 120 days.

resultsThe results showed that compared with the control group, the content of SFA in

conclusionsThese results demonstrated that the addition of appropriate amounts of acorn to the diet (a 30% acorn diet) could improve the nutritional value of pork.

Indexed as

acornfatty acidsintramuscular fatYuxi black pigs

Identifiers

PMID39590814
PMCPMC11596760

What OpenQuestion holds

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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.