Evidence map›Paper›PMID 38872796›Full record

ArticleFrontiers in veterinary science2024

The regulatory mechanism of garlic skin improving the growth performance of fattening sheep through metabolism and immunity.

Yongjie Xu, Mingliang Yi, Shixin Sun, Lei Wang, Zijun Zhang, Yinghui Ling, Hongguo Cao

Abstract read
In one paragraph

Article in Frontiers in veterinary science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 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

7 authors.

Yongjie Xu *College of Animal Science and Technology, Anhui Agricultural University, Hefei, China.
Mingliang Yi *College of Animal Science and Technology, Anhui Agricultural University, Hefei, China.
Shixin SunCollege of Animal Science and Technology, Anhui Agricultural University, Hefei, China.
Lei WangCollege of Animal Science and Technology, Anhui Agricultural University, Hefei, China.
Zijun ZhangCollege of Animal Science and Technology, Anhui Agricultural University, Hefei, China.
Yinghui LingCollege of Animal Science and Technology, Anhui Agricultural University, Hefei, China.
Hongguo CaoCollege of Animal Science and Technology, Anhui Agricultural University, Hefei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Garlic skin (GAS) has been proven to improve the growth performance of fattening sheep. However, the mechanism by which GAS affects fattening sheep is not yet clear. The aim of this study is to investigate the effects of adding GAS to feed on the growth performance, rumen and fecal microbiota, serum and urine metabolism, and transcriptomics of rumen epithelial cells in fattening sheep. Methods: GAS with 80 g/kg dry matter (DM) was added to the diet of fattening sheep to study the effects of GAS on gut microbiota, serum and urine metabolism, and transcriptome of rumen epithelial tissue in fattening sheep. Twelve Hu sheep (body weights; BW, 23.0 ± 2.3 kg and ages 120 ± 3.5 d) were randomly divided into two groups. The CON group was the basal diet, while the GAS group was supplemented with GAS in the basal diet. The trial period was 10 weeks, with the first 2 weeks being the pre-trial period. Results: The daily average weight gain of fattening sheep in the GAS group was significantly higher than that in the CON group ( Conclusion: Adding GAS can improve the energy metabolism and immune function of fattening sheep by altering gut microbiota, metabolome, and transcriptome, thereby improving the growth performance of fattening sheep.

Indexed as

fattening sheepGASgrowth performancemetabolismtranscriptome

Identifiers

PMID38872796
PMCPMC11171129

What OpenQuestion holds

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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.