Evidence map›Paper›PMID 37485499›Full record

ArticleFrontiers in microbiology2023

Ursolic acid ameliorates obesity of mice fed with high-fat diet via alteration of gut microbiota and amino acid metabolism.

Chunfeng Tian, Jie Li, Yan Bao, Long Gao, Lixin Song, Kai Li, Ming Sun

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 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.0field-weighted citation impact, top 14% 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

4 citing papers in PubMed, 13 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Review
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 3 institutions in 1 country.

Chunfeng Tian *School of Public Health, Baotou Medical College, Inner Mongolia University of Science and Technology, Baotou, China.
Jie Li *School of Public Health, Jiamusi University, Jiamusi, China.
Yan BaoSchool of Public Health, Baotou Medical College, Inner Mongolia University of Science and Technology, Baotou, China.
Long GaoSchool of Public Health, Baotou Medical College, Inner Mongolia University of Science and Technology, Baotou, China.
Lixin SongBaotou Disease Prevention Control Center, Baotou, China.
Kai LiSchool of Public Health, Baotou Medical College, Inner Mongolia University of Science and Technology, Baotou, China.
Ming SunSchool of Public Health, Baotou Medical College, Inner Mongolia University of Science and Technology, Baotou, China.
Baotou Medical College · CNInner Mongolia University of Science and Technology · CNJiamusi University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Obesity has been regarded as one of the major health problems worldwide. Studies demonstrated that ursolic acid (UA) can significantly ameliorate the progress of obesity. However, whether the effect of UA on obesity depends on the regulation of gut microbiota and metabolism is uncertain. To investigate the regulatory role of UA in obese mice from the perspective of intestinal microbiome and metabolomics analyses, an obese mice model was established with a high-fat diet, and the effect of UA on obesity was evaluated. The alterations of gut microbiota and metabolism related to obesity were evaluated by bioinformatic analysis. The results of the gut microbiota analysis showed that UA intervention could shift the Firmicutes to Bacteroidetes ratio at the phylum level and increase in the genera of

Indexed as

gut microbiotahigh-fat dietmetabolismmetabolomicsobesityursolic acid

Identifiers

PMID37485499
PMCPMC10359042
OpenAlexW4383373180

What OpenQuestion holds

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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.