Evidence map›Paper›PMID 36277473›Full record

ArticleJournal of immunology research2022

A Network Pharmacology Study on the Cervix Prescription for Treatment of Cervical Cancer.

Yingping Zhu, Liangping Wang, Leilai Xu, Pian Ying

Abstract read
In one paragraph

Article in Journal of immunology research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

4 authors.

Yingping ZhuDepartment of Obstetrics and Gynecology, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, 310006, China.
Liangping WangAffiliated People's Hospital of Hangzhou Medical College, Zhejiang Provincial People's Hospital, China.ORCID https://orcid.org/0000-0002-1145-4986
Leilai XuDepartment of Obstetrics and Gynecology, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, 310006, China.
Pian YingDepartment of Obstetrics and Gynecology, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, 310006, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Based on the method of network pharmacology to explore the mechanism of the cervical prescription (CP) in the treatment of cervical cancer (CC). Methods: We obtained the active ingredients and potential targets in the CP from the literature and the systematic pharmacological analysis platform of traditional Chinese medicine (BATMAN-TCM); the database was used to search for targets related to cervical cancer and to map CP and targets; the core targets were screened, and the protein-protein interaction network (PPI) was constructed using the TCM compound-target network and STRING database. Gene ontology (GO) and Kyoto Gene and Genome Encyclopedia (KEGG) pathway enrichment analysis of overlapping targets were performed using DAVID 6.8 online tool. Results: The CP contains 2 active ingredients, corresponding to 301 nonreactive targets; 10 GO biological process related items and 73 signal pathways were obtained. Cell experiments confirmed that the medicated serum of CP could effectively inhibit the proliferation and invasion ability of Hela cells. Conclusion: This study provides valuable information for TCM researchers and clinicians to better understand the main therapeutic targets and therapeutic roles of herbal decoctions in clinical settings. The results of our study preliminarily clarified that the cervical prescription has an inhibitory effect on cervical cancer cells.

Indexed as

Drugs, Chinese HerbalUterine Cervical NeoplasmsCervix UteriFemaleHeLa CellsHumansMedicine, Chinese TraditionalNetwork PharmacologyPrescriptionsDrugs, Chinese Herbal

Identifiers

PMID36277473
PMCPMC9581665

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Registered trials

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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.