ArticleAnnals of medicine and surgery (2012)2024
Exploring the mechanism of Si-Ni-San against depression by UPLC-Q-TOF-MS/MS integrated with network pharmacology: experimental research.
Article in Annals of medicine and surgery (2012), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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Who cites it
2 citing papers in PubMed, 3 citations in OpenAlex.
- Wubie Fanchun Formula-inducible metabolites in primary ovarian insufficiency model mice that facilitate ovarian renovation.Pharmaceutical biology · 2026Article
- Si-Ni-San alleviates depression-like behavior via regulating the gut microbiota-tryptophan metabolism-AhR/NF-κB pathway axis.Chinese medicine · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Depression is becoming an urgent mental health problem. Si-Ni-San has been widely used to treat depression, yet its underlying pharmacological mechanism is poorly understood. Thus, we aim to explore the antidepressant mechanism of Si-Ni-San by chemical analysis and in-silico methods. Methods: Compounds in Si-Ni-San were determined by ultra-high performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (UPLC-Q-TOF-MS/MS). Then, bioactive compounds were obtained from Traditional Chinese Medicines for Systems Pharmacology Database and Analysis Platform and SwissADME, and the potential targets of which were acquired from SwissTargetPrediction. Depression-related targets were collected from GeneCards. The intersection between compound-related targets and depression-related targets were screened out, and the overlapped targets were further performed protein-protein interaction, biological functional and pathway enrichment analysis. Finally, networks of Si-Ni-San against depression were constructed and visualized by Cytoscape. Results: One hundred nineteen compounds in Si-Ni-San were determined, of which 24 bioactive compounds were obtained. Then, 137 overlapped targets of Si-Ni-San against depression were collected. AKT1, PIK3R1, PIK3CA, mTOR, MAPK1 and MAPK8 were the key targets. Furthermore, PI3K-Akt signalling pathway, serotonergic synapse, MAPK signalling pathway and neurotrophin signalling pathway were involved in the antidepressant mechanism of Si-Ni-San. It showed that components like sinensetin, hesperetin, liquiritigenin, naringenin, quercetin, albiflorin and paeoniflorin were the mainly key active compounds for the antidepressant effect of Si-Ni-San. Conclusions: This study demonstrated the key components, key targets and potential pharmacological mechanisms of Si-Ni-San against depression. These results indicate that Si-Ni-San is a promising therapeutic approach for treatment of depression, and may provide evidence for the research and development of drugs for treating depression.
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Registered trials
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