Evidence map›Paper›PMID 36439829›Full record

ArticleFrontiers in microbiology2022

The impact of Traditional Chinese Medicine on mouse gut microbiota abundances and interactions based on Granger causality and pathway analysis.

Yi Zhang, Dahan Zhang, Xiaogang Bai, Yang Chen, Qinwei Qiu, Xiaoxiao Shang, Yusheng Deng, Hongyan Yang, Xiaodong Fang, Zhimin Yang and 1 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in microbiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.5field-weighted citation impact, top 38% 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

6 citing papers in PubMed, 6 citations in OpenAlex.

  1. Review
  2. Gut Microbiota-Mediated Mechanisms of Traditional Chinese Medicine in Obesity Management.Diabetes, metabolic syndrome and obesity : targets and therapy · 2026
    Review
  3. Review
  4. Review
  5. Article
  6. 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

11 authors at 4 institutions in 1 country.

Yi ZhangDepartment of Scientific Research, Kangmeihuada GeneTech Co., Ltd., (KMHD), Shenzhen, China.
Dahan ZhangDepartment of Scientific Research, Kangmeihuada GeneTech Co., Ltd., (KMHD), Shenzhen, China.
Xiaogang BaiDepartment of Scientific Research, Kangmeihuada GeneTech Co., Ltd., (KMHD), Shenzhen, China.
Yang ChenState Key Laboratory of Dampness Syndrome of Chinese Medicine, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
Qinwei QiuState Key Laboratory of Dampness Syndrome of Chinese Medicine, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
Xiaoxiao ShangState Key Laboratory of Dampness Syndrome of Chinese Medicine, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
Yusheng DengState Key Laboratory of Dampness Syndrome of Chinese Medicine, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
Hongyan YangState Key Laboratory of Dampness Syndrome of Chinese Medicine, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
Xiaodong FangDepartment of Scientific Research, Kangmeihuada GeneTech Co., Ltd., (KMHD), Shenzhen, China.
Zhimin YangState Key Laboratory of Dampness Syndrome of Chinese Medicine, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
Lijuan HanDepartment of Scientific Research, Kangmeihuada GeneTech Co., Ltd., (KMHD), Shenzhen, China.
Guangzhou University of Chinese Medicine · CNChinese Academy of Sciences · CNHebei University of Science and Technology · CNKangmei Pharmaceutical (China) · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: The intestinal microbiota is essential in absorbing nutrients and defending against pathogens and is associated with various diseases, including obesity, type 2 diabetes, and hypertension. As an alternative medicine, Traditional Chinese Medicine (TCM) has long been used in disease treatment and healthcare, partly because it may mediate gut microbiota. However, the specific effects of TCM on the abundance and interactions of microbiota remain unknown. Moreover, using TCM ingredients and data detailing changes in the abundance of gut microorganisms, we developed bioinformatic methods that decipher the impact of TCM on microorganism interactions. Methods: The dynamics of gut microorganisms affected by TCM treatments is explored using a mouse model, which provided the abundance of 70 microorganisms over time. The Granger causality analysis was used to measure microorganism interactions. Novel "serial connection" and "diverging connection" models were used to identify molecular mechanisms underlying the impact of TCM on gut microorganism interactions, based on microorganism proteins, TCM chemical ingredients, and KEGG reaction equations. Results: Conclusions: Because most of the nine TCMs are medicinal and edible plants, we expect the methods and results presented can be used to optimize and integrate microbiota and TCMs into healthcare processes. Moreover, as a control study, these results can be combined with future disease mouse models to link variations in species abundance with particular diseases.

Indexed as

bioinformaticsGranger causalityintestinal microbiologymolecular mechanismsTraditional Chinese Medicine

Identifiers

PMID36439829
PMCPMC9692106
OpenAlexW4308803735

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.