Evidence map›Paper›PMID 41059284›Full record

ArticleJournal of inflammation research2025

Mechanistic Insights into Qin Bi Yin for Psoriasis Treatment Using Network Pharmacology, Experimental Validation, and Molecular Docking.

Shouxu Zhang, Yue Du, Haomin Zhang, Xingwu Duan, Lingling Li

Abstract read
In one paragraph

Article in Journal of inflammation research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. Review
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

5 authors.

Shouxu ZhangDepartment of Dermatology, Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, 100700, People's Republic of China.
Yue DuDepartment of Dermatology, Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, 100700, People's Republic of China.
Haomin ZhangDepartment of Dermatology, Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, 100700, People's Republic of China.
Xingwu DuanDepartment of Dermatology, Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, 100700, People's Republic of China.
Lingling LiDepartment of Dermatology, Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, 100700, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: In this study, we investigated the potential mechanism of action of Qing Bi Yin (QBY) in psoriasis treatment via regulation of the sphingosine-1-phosphate (S1P)/sphingosine-1-phosphate receptor 1 (S1PR1) pathway and Th17 cell differentiation. Methods: Network pharmacology was used to identify potential targets and elucidate the potential mechanisms of QBY in psoriasis. The predicted mechanisms were validated with in vitro Th17 cell differentiation assays using isolated mouse splenic CD4+ T cells. Molecular docking was performed to evaluate the binding affinities between active compounds and key target proteins. Results: We identified 262 overlapping QBY psoriasis target genes. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed significant associations with the sphingolipid signaling pathway, Th17 cell differentiation, and IL-17 signaling pathway. Network algorithms were used to identify 10 key active compounds and five hub genes. QBY treatment suppresses S1P synthesis and Conclusion: QBY ameliorates psoriatic inflammation by regulating Th17 cell differentiation via the S1P/S1PR1 signaling pathway. These findings underscore the clinical translational potential of QBY and its active constituent glabridin.

Indexed as

network pharmacologypsoriasisS1PS1PR1Th17 differentiation

Identifiers

PMID41059284
PMCPMC12497865

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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.