Evidence map›Paper›PMID 37928663›Full record

ArticleFrontiers in microbiology2023

Dynamic changes of fecal microbiota in a weight-change model of Bama minipigs.

Bo Zeng, Li Chen, Fanli Kong, Chengcheng Zhang, Long Chen, Xu Qi, Jin Chai, Long Jin, Mingzhou Li

Open access · goldAbstract read
In one paragraph

Article in Frontiers in microbiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.8field-weighted citation impact, top 26% of its field
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

7 citing papers in PubMed, 5 citations in OpenAlex.

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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

9 authors at 4 institutions in 2 countries.

Bo ZengKey Laboratory of Livestock and Poultry Multi-omics, Ministry of Agriculture and Rural Affairs, and Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China.
Li ChenChongqing Academy of Animal Science, Chongqing, China.
Fanli KongCollege of Life Science, Sichuan Agricultural University, Ya'an, China.
Chengcheng ZhangKey Laboratory of Livestock and Poultry Multi-omics, Ministry of Agriculture and Rural Affairs, and Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China.
Long ChenKey Laboratory of Livestock and Poultry Multi-omics, Ministry of Agriculture and Rural Affairs, and Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China.
Xu QiKey Laboratory of Livestock and Poultry Multi-omics, Ministry of Agriculture and Rural Affairs, and Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China.
Jin ChaiKey Laboratory of Livestock and Poultry Multi-omics, Ministry of Agriculture and Rural Affairs, and Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China.
Long JinKey Laboratory of Livestock and Poultry Multi-omics, Ministry of Agriculture and Rural Affairs, and Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China.
Mingzhou LiKey Laboratory of Livestock and Poultry Multi-omics, Ministry of Agriculture and Rural Affairs, and Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China.
Sichuan Agricultural University · CNChongqing Academy of Animal Science · CNMinistry of Agriculture and Rural Affairs · CNMinistry of Agriculture · EE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Obesity is closely related to gut microbiota, however, the dynamic change of microbial diversity and composition during the occurrence and development process of obesity is not clear. Methods: A weight-change model of adult Bama pig (2 years, 58 individuals) was established, and weight gain (27 weeks) and weight loss (9 weeks) treatments were implemented. The diversity and community structures of fecal microbiota (418 samples) was investigated by using 16S rRNA (V3-V4) high-throughput sequencing. Results: During the weight gain period (1~27 week), the alpha diversity of fecal microbiota exhibited a "down-up-down" fluctuations, initially decreasing, recovering in the mid-term, and decreasing again in the later stage. Beta diversity also significantly changed over time, indicating a gradual deviation of the microbiota composition from the initial time point. Discussion: Both long-term fattening and weight loss induced by starvation led to substantial alterations in porcine gut microbiota, and the microbiota changes observed during weight gain could not be recovered during weight loss. This work provides valuable resources for both obesity-related research of human and microbiota of pigs.

Indexed as

16S rRNABama pigdietary restrictiongut microbiotaobesity

Identifiers

PMID37928663
PMCPMC10623433
OpenAlexW4387810191

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.