Evidence map›Paper›PMID 35360657›Full record

ArticleEvidence-based complementary and alternative medicine : eCAM2022

Mining Important Herb Combinations of Traditional Chinese Medicine against Hypertension Based on the Symptom-Herb Network Combined with Network Pharmacology.

Zhenhai Sun, Yunsheng Xu, Wenrong An, Siling Bi, Sai Xu, Rui Zhang, Mingyang Cong, Shouqiang Chen

Open access · hybridAbstract read
In one paragraph

Article in Evidence-based complementary and alternative medicine : eCAM, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.9field-weighted citation impact, top 30% 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

4 citing papers in PubMed, 10 citations in OpenAlex.

  1. Review
  2. Article
  3. Markers of Vascular Dysfunction in Hypertension.Current medicinal chemistry · 2025
    Review
  4. Investigation of the molecular mechanism ofFrontiers in pharmacology · 2024
    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

8 authors at 1 institution in 1 country.

Zhenhai SunShandong University of Traditional Chinese Medicine, Jinan, China.ORCID https://orcid.org/0000-0002-2344-3109
Yunsheng XuThe Second Hospital, Shandong University of Traditional Chinese Medicine, Jinan, China.
Wenrong AnShandong University of Traditional Chinese Medicine, Jinan, China.ORCID https://orcid.org/0000-0002-7532-6457
Siling BiShandong University of Traditional Chinese Medicine, Jinan, China.ORCID https://orcid.org/0000-0002-7942-6471
Sai XuShandong University of Traditional Chinese Medicine, Jinan, China.ORCID https://orcid.org/0000-0002-9392-3001
Rui ZhangShandong University of Traditional Chinese Medicine, Jinan, China.ORCID https://orcid.org/0000-0001-6536-0056
Mingyang CongShandong University of Traditional Chinese Medicine, Jinan, China.ORCID https://orcid.org/0000-0001-6456-7637
Shouqiang ChenThe Second Hospital, Shandong University of Traditional Chinese Medicine, Jinan, China.ORCID https://orcid.org/0000-0001-7958-2370
Shandong University of Traditional Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although data mining methods are extensively used in the rule analysis of famous old traditional Chinese medicine (TCM) experts' prescriptions for the treatment of hypertension, most of them only mine the association between herbs and herbs, ignoring the importance of symptoms in the disease. This study collected 439 cases of hypertension treated by famous old TCM experts from the FangNet platform. Using the structure network algorithm, the symptom-herb network was constructed, which redefined the importance of herb in disease. Based on the network, 21 driver herbs, 76 herb pairs, and 41 symptom-herb associations were mined. Finally, the basic prescription composed of Gouteng (Uncariae Ramulus cum Uncis), Huanglian (Coptidis Rhizoma), Chuanxiong (Chuanxiong Rhizoma), Gegen (Puerariae Lobatae Radix), Danggui (Angelicae Sinensis Radix), and Huangqin (Scutellariae Radix) was found. These herbs are the most significant among all herbs, and they have a potential correlation with each other. To further verify the rationality of the data mining results, we adopted the network pharmacology method. Network pharmacological analysis shows that the five core targets in the basic prescription include IL6, VEGFA, TNF, TP53, and EGF, which link 10 significant active compounds and 7 important KEGG pathways. It was predicted that anti-inflammatory, antioxidant, vascular endothelial protection, emotion regulation, and ion channel intervention might be the main mechanisms of the basic prescription against hypertension. This study reveals the prescription rule of famous old TCM experts for treating hypertension from a new perspective, which provides a new approach to inherit the academic experience of famous old TCM experts and develop new drugs.

Identifiers

PMID35360657
PMCPMC8964163
OpenAlexW4221128523

What Socratic holds

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LicenceCC BY
Read underepoch 390

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 Socratic graph.