Evidence map›Paper›PMID 33658763›Full record

ArticleDrug design, development and therapy2021

Predicting and Exploring the Mechanisms of Erzhi Pill in Prevention and Treatment of Osteoporosis Based on Network Pharmacology and Zebrafish Experiments.

Zhiguo Zhong, Yuyun Li, Yan Chen, Wen Chen, Siyan Li, Xiaohua Lv, Shiying Luo

Open access · goldAbstract read
In one paragraph

Article in Drug design, development and therapy, 2021. 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
1.0field-weighted citation impact, top 26% 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

7 citing papers in PubMed, 14 citations in OpenAlex.

  1. Protective Role of Erzhi Pills in HBiochemical genetics · 2026
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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

7 authors at 2 institutions in 1 country.

Zhiguo ZhongTraditional Chinese Medicine Department, Affiliated Hospital of Guangdong Medical University, Zhanjiang, 524023, People's Republic of China.
Yuyun LiDepartment of Pharmacology, School of Pharmacy, Guangdong Key Laboratory for Research and Development of Natural Drugs, Marine Biomedical Research Institute, Guangdong Medical University, Zhanjiang, 524023, People's Republic of China.
Yan ChenDepartment of Pharmacology, School of Pharmacy, Guangdong Key Laboratory for Research and Development of Natural Drugs, Marine Biomedical Research Institute, Guangdong Medical University, Zhanjiang, 524023, People's Republic of China.
Wen ChenDepartment of Pharmacology, School of Pharmacy, Guangdong Key Laboratory for Research and Development of Natural Drugs, Marine Biomedical Research Institute, Guangdong Medical University, Zhanjiang, 524023, People's Republic of China.
Siyan LiSchool of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, 510006, People's Republic of China.
Xiaohua LvDepartment of Pharmacology, School of Pharmacy, Guangdong Key Laboratory for Research and Development of Natural Drugs, Marine Biomedical Research Institute, Guangdong Medical University, Zhanjiang, 524023, People's Republic of China.
Shiying LuoDepartment of Pharmacology, School of Pharmacy, Guangdong Key Laboratory for Research and Development of Natural Drugs, Marine Biomedical Research Institute, Guangdong Medical University, Zhanjiang, 524023, People's Republic of China.ORCID 0000-0001-8235-9057
Guangdong Medical College · CNGuangzhou University of Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundErzhi Pill (EZP), a traditional Chinese medicine (TCM) prescription, has been widely applied to improve bone metabolism and treat osteoporosis (OP) in China. However, its effective constituents and mechanisms remain unclear.

methodsBy combining network pharmacology and zebrafish experiments, an integrative method was employed to address this problem. Firstly, the disease targets of OP were collected from two public gene databases. Secondly, the active compounds and drug targets of EZP were obtained from the traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP). Thirdly, a drug-target-disease interaction network was constructed, and the key active components were identified by analyzing the topological characteristics of the network. Finally, these predicted results were tested by zebrafish experiments and compared with those from the literature. Specifically, quercetin as an important representative active component of EZP was applied to wild type and transgenic zebrafish larvae to assess its effects on skull mineralization and osteoplastic differentiation.

resultsOur study identified 72 active compounds, 220 targets and 166 signaling pathways probably involved in the prevention and treatment of OP by EZP, wherein quercetin, apigenin, daidzein, luteolin, ursolic acid and kaempferol could be the key compounds, while PI3K-Akt signaling pathway, TNF signaling pathway and IL-17 signaling pathway could be the key signaling pathways. The experiments indicated that quercetin attenuated both the decrease of skull mineralization and the inhibition of skull osteoplastic differentiation in zebrafish larvae trigged by dexamethasone.

conclusionOur study not only investigated potentially effective constituents and mechanisms of EZP in the prevention and treatment of OP, but also provided a reference for the in-depth research, development and application of TCM.

Indexed as

AnimalsDose-Response Relationship, DrugDrugs, Chinese HerbalMedicine, Chinese TraditionalMolecular StructureOsteoporosisStructure-Activity RelationshipZebrafishDrugs, Chinese Herbalerzhi pillErzhi Pillmechanismsnetwork pharmacologyosteoporosisquercetinzebrafish

Identifiers

PMID33658763
PMCPMC7917472
OpenAlexW3130344566

What OpenQuestion holds

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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.