Evidence map›Paper›PMID 38780275›Full record

ArticlemSystems2024

Liyuan Cai, Xinkai Wang, Xiaoyan Zhu, Yunzheng Xu, Wenxia Qin, Jing Ren, Qin Jiang, Xianghua Yan

Abstract read
In one paragraph

Article in mSystems, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 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.

Liyuan CaiNational Key Laboratory of Agricultural Microbiology, Frontiers Science Center for Animal Breeding and Sustainable Production, Hubei Hongshan Laboratory, College of Animal Sciences and Technology, Huazhong Agricultural University, Wuhan, Hubei, China.
Xinkai WangNational Key Laboratory of Agricultural Microbiology, Frontiers Science Center for Animal Breeding and Sustainable Production, Hubei Hongshan Laboratory, College of Animal Sciences and Technology, Huazhong Agricultural University, Wuhan, Hubei, China.
Xiaoyan ZhuNational Key Laboratory of Agricultural Microbiology, Frontiers Science Center for Animal Breeding and Sustainable Production, Hubei Hongshan Laboratory, College of Animal Sciences and Technology, Huazhong Agricultural University, Wuhan, Hubei, China.
Yunzheng XuNational Key Laboratory of Agricultural Microbiology, Frontiers Science Center for Animal Breeding and Sustainable Production, Hubei Hongshan Laboratory, College of Animal Sciences and Technology, Huazhong Agricultural University, Wuhan, Hubei, China.
Wenxia QinNational Key Laboratory of Agricultural Microbiology, Frontiers Science Center for Animal Breeding and Sustainable Production, Hubei Hongshan Laboratory, College of Animal Sciences and Technology, Huazhong Agricultural University, Wuhan, Hubei, China.
Jing RenNational Key Laboratory of Agricultural Microbiology, Frontiers Science Center for Animal Breeding and Sustainable Production, Hubei Hongshan Laboratory, College of Animal Sciences and Technology, Huazhong Agricultural University, Wuhan, Hubei, China.
Qin JiangNational Key Laboratory of Agricultural Microbiology, Frontiers Science Center for Animal Breeding and Sustainable Production, Hubei Hongshan Laboratory, College of Animal Sciences and Technology, Huazhong Agricultural University, Wuhan, Hubei, China.ORCID 0000-0003-4635-4931
Xianghua YanNational Key Laboratory of Agricultural Microbiology, Frontiers Science Center for Animal Breeding and Sustainable Production, Hubei Hongshan Laboratory, College of Animal Sciences and Technology, Huazhong Agricultural University, Wuhan, Hubei, China.ORCID 0000-0003-2238-6218

Funding

China Postdoctoral Science Foundation (China Postdoctoral Foundation Project) 2019TQ0108MOE | Fundamental Research Funds for the Central Universities (Fundamental Research Fund for the Central Universities) Project 2662023DKPY002the National Key Research and Development Project 2023YFD1301304
6 · The paper itself

Abstract

The gut microbiota contributes to skeletal muscle energy metabolism and is an indirect factor affecting meat quality. However, the role of specific gut microbes in energy metabolism and fiber size of skeletal muscle in chickens remains largely unknown. In this study, we first performed cecal microbiota transplantation from Chinese indigenous Jingyuan chickens (JY) to Arbor Acres chickens (AA), to determine the effects of microbiota on skeletal muscle fiber and energy metabolism. Then, we used metagenomics, gas chromatography, and metabolomics analysis to identify functional microbes. Finally, we validated the role of these functional microbes in regulating the fiber size via glucose metabolism in the skeletal muscle of chickens through feeding experiments. The results showed that the skeletal muscle characteristics of AA after microbiota transplantation tended to be consistent with that of JY, as the fiber diameter was significantly increased, and glucose metabolism level was significantly enhanced in the pectoralis muscle.

Indexed as

ChickensFatty Acids, VolatileGastrointestinal MicrobiomeGlucoseLactobacillusAnimalsEnergy MetabolismFecal Microbiota TransplantationMuscle Fibers, SkeletalMuscle, SkeletalFatty Acids, VolatileGlucosechickenfiber sizeglucose metabolismLactobacillusskeletal muscle

Identifiers

PMID38780275
PMCPMC11237663

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.