Evidence map›Paper›PMID 37050924›Full record

ArticleFood & nutrition research2023

Yu-Han Jiang, Jing-Hui Bi, Min-Rui Wu, Shi-Jie Ye, Lei Hu, Long-Jie Li, Yang Yi, Hong-Xun Wang, Li-Mei Wang

Open access · goldAbstract read
In one paragraph

Article in Food & nutrition research, 2023. 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
1.6field-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

6 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Comprehensive Review on Fruit ofMolecules (Basel, Switzerland) · 2024
    Review
  3. Article
  4. Article
  5. Food & nutrition research · 2023
    Article
  6. 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

9 authors at 1 institution in 1 country.

Yu-Han JiangSchool of Life Science and Technology, Wuhan Polytechnic University, Wuhan, China.
Jing-Hui BiSchool of Life Science and Technology, Wuhan Polytechnic University, Wuhan, China.
Min-Rui WuSchool of Life Science and Technology, Wuhan Polytechnic University, Wuhan, China.
Shi-Jie YeSchool of Life Science and Technology, Wuhan Polytechnic University, Wuhan, China.
Lei HuSchool of Life Science and Technology, Wuhan Polytechnic University, Wuhan, China.
Long-Jie LiSchool of Life Science and Technology, Wuhan Polytechnic University, Wuhan, China.
Yang YiSchool of Food Science and Engineering, Wuhan Polytechnic University, Wuhan, China.
Hong-Xun WangSchool of Life Science and Technology, Wuhan Polytechnic University, Wuhan, China.
Li-Mei WangSchool of Life Science and Technology, Wuhan Polytechnic University, Wuhan, China.
Wuhan Polytechnic University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: 1,2,3,4,6-Penta-O-galloyl-β-D-glucose (β-PGG) is a polyphenol ellagic compound with a variety of pharmacological effects and has an inhibitory effect on lots of cancers. Objective: To explore the antitumor effects and mechanism of 1,2,3,4,6-Penta-O-galloyl-β-D-glucose on human hepatocellular carcinoma HepG2 cells. Design: A network pharmacology method was first used to predict the possible inhibition of hepatocellular carcinoma growth by 1,2,3,4,6-Penta-O-galloyl-β-D-glucose (β-PGG) through the p53 signaling pathway. Next, the Cell Counting Kit (CCK-8) assay was performed to evaluate changes in the survival rate of human hepatocellular carcinoma HepG2 cells treated with different concentrations of the drug; flow cytometry was used to detect changes in cell cycle, apoptosis, mitochondrial membrane potential (MMP) and intracellular Ca2+ concentration; real-time fluorescence quantification and immunoblotting showed that the expression of P53 genes and proteins associated with the p53 signaling pathway was significantly increased by β-PGG treatment. Reasult: It was found that β-PGG significantly inhibited survival of HepG2 cells, promoted apoptosis, decreased MMP and intracellular Ca2+ concentration, upregulated P53 gene and protein expression, increased CASP3 expression, and induced apoptosis in HepG2 cells. Conclusion: This study has shown that network pharmacology can accurately predict the target of β-PGG's anti-hepatocellular carcinoma action. Moreover, it was evident that β-PGG can induce apoptosis in HepG2 cells by activating the p53 signaling pathway to achieve its anti-hepatocellular carcinoma effect

Indexed as

1,2,3,4,6-Penta-O-galloyl-β-D-glucoseapoptosishepatocellular carcinomanetwork pharmacologyp53 signaling pathway

Identifiers

PMID37050924
PMCPMC10084503
OpenAlexW4361001403

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.