Evidence map›Paper›PMID 40950607›Full record

ArticleFrontiers in microbiology2025

Identifying gut microbiota

Yi Li, Senlin Wang, Song Zhang, Ergan Li, Meifang Liang, Youqin Li, Anke Liuli, Li Deng, Yanjun Liu, Tongtong Zhang and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in microbiology, 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

13 authors.

Yi Li *Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Senlin Wang *Division of Liver Surgery, Department of General Surgery, West China Hospital, Sichuan University, Chengdu, China.
Song Zhang *Department of Pediatrics, Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.
Ergan LiCollege of Animal Science and Veterinary Medicine, Southwest Minzu University, Chengdu, China.
Meifang LiangCollege of Life Science and Engineering, Southwest Jiaotong University, Chengdu, China.
Youqin LiThe Center of Obesity and Metabolic Diseases, Department of General Surgery, The Affiliated Hospital of Southwest Jiaotong University, The Third People's Hospital of Chengdu, Chengdu, Sichuan, China.
Anke LiuliCollege of Life Science and Engineering, Southwest Jiaotong University, Chengdu, China.
Li DengCollege of Life Science and Engineering, Southwest Jiaotong University, Chengdu, China.
Yanjun LiuObesity and Metabolism Medicine-Engineering Integration Laboratory, Department of General Surgery, The Affiliated Hospital of Southwest Jiaotong University, The Third People's Hospital of Chengdu, Chengdu, China.
Tongtong ZhangObesity and Metabolism Medicine-Engineering Integration Laboratory, Department of General Surgery, The Affiliated Hospital of Southwest Jiaotong University, The Third People's Hospital of Chengdu, Chengdu, China.
Di XinDepartment of Hepatobiliary and Pancreatic Surgery and Zhejiang Provincial Key Laboratory of Pancreatic Disease, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
Yongmei LiDepartment of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Zhonghui FengObesity and Metabolism Medicine-Engineering Integration Laboratory, Department of General Surgery, The Affiliated Hospital of Southwest Jiaotong University, The Third People's Hospital of Chengdu, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Obesity is a global health issue, with sharply increasing rates due to excessive food intake and reduced physical activity, leading to an increased risk of various chronic diseases, such as type 2 diabetes and cardiovascular diseases. Fat distribution plays a significant role in health, with visceral fat being particularly associated with metabolic syndrome. Currently, computed tomography (CT) and magnetic resonance imaging (MRI) are the gold standards for measuring visceral fat, but they are costly and involve radiation risks. The gut microbiota is closely related to obesity, and dysbiosis may lead to obesity and metabolic disorders. Research on the relationship between visceral fat and the gut microbiota can aid in the development of new diagnostic and therapeutic approaches. Methods: We selected 31 participants with class II obesity (body mass index between 35 and 40) and divided those samples into two groups on the basis of their VSR (visceral-to-subcutaneous fat volume ratio) measured by CT, analyzed their fecal. Microbiota through 16S rDNA sequencing. Results: Results reveal significant differences in microbial composition between the visceral and subcutaneous obesity groups through 16S analysis of their fecal microbiota. The visceral obesity group presented a greater abundance of the Conclusion: This study measured visceral and subcutaneous fat volumes via CT and revealed that the composition of the gut microbiota is related to the type of obesity. In addition, we found that

Indexed as

Faecalibacteriumgut microbiotaobesitysubcutaneous fatvisceral fat

Identifiers

PMID40950607
PMCPMC12426024

What Socratic 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 Socratic graph.