Evidence map›Paper›PMID 40343088›Full record

ArticlePeerJ2025

Yang Zhao, Juwei Wen, Yu Yang, Lina Jia, Qian Ma, Weiguo Jia, Wei Qi

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in PeerJ, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Yang ZhaoCollege of Life Science, Zhuhai College of Science and Technology, Zhuhai, China.
Juwei WenCollege of Life Science, Zhuhai College of Science and Technology, Zhuhai, China.
Yu YangCollege of Life Science, Zhuhai College of Science and Technology, Zhuhai, China.
Lina JiaCollege of Biotechnology, Tianjin University of Science and Technology, Tianjin, China.
Qian MaCollege of Biotechnology, Tianjin University of Science and Technology, Tianjin, China.
Weiguo JiaThe Center of Gerontology and Geriatrics, National Clinical Research Center of Geriatrics, West China Hospital, Sichuan University, Chengdu, China.
Wei QiCollege of Life Science, Zhuhai College of Science and Technology, Zhuhai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Increasing evidence has shown a close relation between the pathogenesis of type 2 diabetes mellitus (T2DM), which is a global health problem with multifactorial etiopathogenesis, and gut microbiota. Methods: During Results: Analysis of chemical compositions indicates that the total sugar content of SNP was found to be as high as 87.35 ± 0.13% (w/w). SNP treatment significantly improved the gas volume and composition in T2DM fecal matter. Moreover, intestinal flora degraded SNP to produce SCFAs, thus regulating SCFA production and composition. Metabolomic analysis implied that SNP shows potential to regulate the five gut metabolites (L-valine, L-leucine, L-isoleucine, L-alanine, and xylitol) in T2DM fecal matter. Furthermore, dysbiosis of gut microbiota induced by T2DM was reversed by SNP. The evidence includes decreasing

Indexed as

Diabetes Mellitus, Type 2FermentationGastrointestinal MicrobiomePolysaccharidesScrophulariaDysbiosisFatty Acids, VolatileFecesHumansMaleFatty Acids, VolatilePolysaccharidesGut microbiotaPolysaccharideScrophularia ningpoensisT2DM

Identifiers

PMID40343088
PMCPMC12060902

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.