Evidence map›Paper›PMID 36444935›Full record

ArticlePharmaceutical biology2022

Integration of network pharmacology and intestinal flora to investigate the mechanism of action of Chinese herbal

Na Li, Mukaram Amatjan, Pengke He, Boheng Zhang, Xianyan Mai, Qianle Jiang, Haochen Xie, Xiaoni Shao

Abstract read
In one paragraph

Article in Pharmaceutical biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

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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

7 citing papers in PubMed.

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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

8 authors.

Na LiImmunotherapy Laboratory, College of Pharmacology, Southwest Minzu University, Chengdu, China.
Mukaram AmatjanImmunotherapy Laboratory, College of Pharmacology, Southwest Minzu University, Chengdu, China.
Pengke HeImmunotherapy Laboratory, College of Pharmacology, Southwest Minzu University, Chengdu, China.
Boheng ZhangImmunotherapy Laboratory, College of Pharmacology, Southwest Minzu University, Chengdu, China.
Xianyan MaiImmunotherapy Laboratory, College of Pharmacology, Southwest Minzu University, Chengdu, China.
Qianle JiangImmunotherapy Laboratory, College of Pharmacology, Southwest Minzu University, Chengdu, China.
Haochen XieQinghai Tibet Plateau Research Institute, Southwest Minzu University, Chengdu, China.
Xiaoni ShaoImmunotherapy Laboratory, College of Pharmacology, Southwest Minzu University, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

context

objectiveTo explore the therapeutic effect and mechanism of CF on HN. MATERIALS AND

methodsThrough network pharmacological methods, the targets of the active component of CF against HN were obtained. Subsequently, Male Wistar rats were divided into control, HN, allopurinol (50 mg/kg), CF high-dose (8.64 g/kg) and CF low-dose (2.16 g/kg) groups. The HN model was induced

resultsThe network pharmacology identified 83 key targets, 6 core genes and 200 signalling pathways involved in the treatment of HN. Compared to the HN group, CF (8.64 g/kg) significantly reduced the levels of UA, UREA and CREA (from 2.4 to 1.57 μMol/L, from 15.87 to 11.05 mMol/L and from 64.83 to 54.83 μMol/L, respectively), and mitigated renal damage. Furthermore, CF inhibited the expression of IL-6, TP53, TNF and JUN. It also altered the composition of gut microbiota, and ameliorated HN by increasing the relative abundance of some probiotics.

conclusionsThis work elucidated the therapeutic effect and underlying mechanism by which CF protects against HN from the view of the biodiversity of the intestinal flora, thus providing a scientific basis for the usage of CF.

Indexed as

Cichorium intybusGastrointestinal MicrobiomeHyperuricemiaAdenineAnimalsChinaEthambutolMaleNetwork PharmacologyRatsRats, WistarUreaAdenineEthambutolUreagut microorganismsmolecular dockingnephroprotective effecttraditional Chinese medicine formula

Identifiers

PMID36444935
PMCPMC9897651

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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.