ArticleEvidence-based complementary and alternative medicine : eCAM2021
Exploring the Mechanism of Action of Herbal Medicine (
Article in Evidence-based complementary and alternative medicine : eCAM, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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.
Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.
- Chinese herbal medicines for the treatment of depression: a systematic review and network meta-analysis.Frontiers in pharmacology · 2024Pooled it
- Gan-Mai-Da-Zao-Tang attenuates age-induced skeletal muscle wasting and improves mitochondrial function in mice.Journal of traditional and complementary medicine · 2026Article
- Exploring the anti-diabetic potential of peimisine through bioinformatics analysis andFrontiers in pharmacology · 2026Article
- Luteolin and its antidepressant properties: From mechanism of action to potential therapeutic application.Journal of pharmaceutical analysis · 2025Review
- Efficacy of Danlou tablet on myocardial ischemia/ reperfusion injury assessed by network pharmacology and experimental verification.Journal of traditional Chinese medicine = Chung i tsa chih ying wen pan · 2024Article
- Article
- Integrating network pharmacology and an experimental validation strategy elucidates the protective effect and mechanism of callicarpa nudiflora against neuroinflammation.RSC advances · 2022Article
- Network pharmacology analysis and experimental verification reveal the mechanism of the traditional Chinese medicine YU-Pingfeng San alleviating allergic rhinitis inflammatory responses.Frontiers in plant science · 2022Article
- Exploring the Mechanism of Action of Herbal Medicine (Evidence-based complementary and alternative medicine : eCAM · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPoststroke depression (PSD) is the most common and serious neuropsychiatric complication occurring after cerebrovascular accidents, seriously endangering human health while also imposing a heavy burden on society. Nevertheless, it is difficult to control disease progression.
resultsThe network pharmacological analysis of GMDZD in PSD revealed 107 active ingredients with important biological effects, including quercetin, luteolin, kaempferol, naringenin, and isorhamnetin. In total, 203 potential targets for the treatment of this disease were screened, including STAT3, JUN, TNF, TPT53, AKT1, and EGFR. These drugs are widely enriched in a series of signaling pathways, such as TNF, HIF-1, and toll-like receptor. Moreover, molecular docking analysis showed that the core active components were tightly bound to their core targets, further confirming their anti-PSD effects.
conclusionThis prospective study was based on the integrated analysis of large data using network pharmacology technology to explore the feasibility of GMDZD for PSD treatment that was successfully validated by molecular docking. It reflects the multicomponent and multitarget characteristics of Chinese medicine and, more importantly, brings hope for the clinical treatment of PSD.
Identifiers
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Registered trials
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.