Evidence map›Paper›PMID 32256098›Full record

ArticleDiabetes, metabolic syndrome and obesity : targets and therapy2020

Yuxin Wang, Meishuo Ouyang, Xibao Gao, Shuai Wang, Chunyang Fu, Jiayi Zeng, Xiaodong He

Open access · goldAbstract read
In one paragraph

Article in Diabetes, metabolic syndrome and obesity : targets and therapy, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed
2.9field-weighted citation impact, top 8% 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

35 citing papers in PubMed, 56 citations in OpenAlex.

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  14. Metabolic Parkinson's disease.Frontiers in aging neuroscience · 2025
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  17. Review
  18. Review
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  20. 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

7 authors at 2 institutions in 2 countries.

Yuxin Wang *Department of Physical and Chemical Inspection, School of Public Health, Shandong University, Jinan, Shandong 250012, People's Republic of China.ORCID 0000-0003-2101-413X
Meishuo Ouyang *Department of Public Health, Graduate School of Medicine, Osaka University, Suita, Osaka 565-0871, Japan.
Xibao GaoDepartment of Physical and Chemical Inspection, School of Public Health, Shandong University, Jinan, Shandong 250012, People's Republic of China.
Shuai WangInstitute of Toxicology, School of Public Health, Shandong University, Jinan, Shandong 250012, People's Republic of China.
Chunyang FuDepartment of Physical and Chemical Inspection, School of Public Health, Shandong University, Jinan, Shandong 250012, People's Republic of China.
Jiayi ZengDepartment of Physical and Chemical Inspection, School of Public Health, Shandong University, Jinan, Shandong 250012, People's Republic of China.
Xiaodong HeDepartment of Physical and Chemical Inspection, School of Public Health, Shandong University, Jinan, Shandong 250012, People's Republic of China.
Shandong University · CNThe University of Osaka · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe purpose of this study was to explore the difference and association between intestinal microbiota and plasma metabolomics between type 2 diabetes mellitus (T2DM) and normal group and to identify potential microbiota biomarkers that contribute the most to the difference in metabolites.

methodsSix male ZDF model (fa/fa) rats were fed by a Purina #5008 Lab Diet (crude protein 23.5%, crude fat 6.5%) for 3 weeks and their age-matched 6 ZDF control (fa/+) rats were fed by normal rodent diet. Their stool and blood samples were collected at 12 weeks. To analyze the microbial populations in these samples, we used a 16S rRNA gene sequencing approach. Liquid chromatography-mass spectrometry (LC-MS) followed by multivariate statistical analysis was applied to the plasma metabolites profiling. Correlation analysis of them was calculated by Pearson statistical method.

resultsTwelve potential biomarkers of intestinal microbial flora and 357 differential metabolites were found in ZDF fa/fa rats, among which there are three flora that contributed the most to the perturbation of metabolites, including genus

conclusionOur study demonstrates the alterations of the abundance and diversity of the intestinal microbiota and the perturbation of metabolites in ZDF rats (fa/fa). We found three potential biomarkers of intestinal microbiota that may lead to perturbation in plasma metabolites. This may prompt new pathogenesis of obesity-related T2DM, but we also need to study further about the causal relationship between intestinal microbe and T2DM, so as to find the target of T2DM treatment or preventive measures.

Indexed as

16S rRNA sequencingintestinal microbiotaplasma metabolomicstype 2 diabetes mellitusZucker diabetic fatty rats

Identifiers

PMID32256098
PMCPMC7090210
OpenAlexW3010997277

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.