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Record W4226241653

Network Pharmacology and Molecular Docking Study of the Chinese Miao Medicine Sidaxue in the Treatment of Rheumatoid Arthritis

2022· article· en· W4226241653 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2022
Typearticle
Languageen
FieldMedicine
TopicTraditional Chinese Medicine Analysis
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPI3K/AKT/mTOR pathwayProtein kinase BRheumatoid arthritisArthritisMedicinePharmacologySignal transductionAngiogenesisSTAT1Cancer researchInflammationImmunologyBiologyReceptorInternal medicineCell biology
DOInot available

Abstract

fetched live from OpenAlex

Ning Wu,1,* Taohua Yuan,1,* ZhiXin Yin,1 Xiaotian Yuan,1 Jianfei Sun,1 Zunqiu Wu,1 Qilong Zhang,1 Carl Redshaw,2 Shenggang Yang,1 Xiaotian Dai3 1Guizhou Medical University, Guiyang, Guizhou, People’s Republic of China; 2Department of Chemistry, University of Hull, Hull, Yorkshire, HU6 7RX, UK; 3Department of Mathematics and Statistics, University of Calgary, Calgary, AB, Canada*These authors contributed equally to this workCorrespondence: Shenggang Yang, Guizhou Medical University, Guiyang, Guizhou, 550025, People’s Republic of China, Tel/Fax +86 13158000576, Email yangshenggang2021@126.com Xiaotian Dai, Department of Mathematics and Statistics, University of Calgary, Calgary, AB, T2N 1N4, Canada, Tel/Fax +1 435 754 4980, Email xiaotian.dai@uCalgary.caPurpose: This study aimed to investigate the molecular mechanisms of Compound Sidaxue (SX), a prescription of Chinese Miao medicine, in treating rheumatoid arthritis (RA) using network pharmacology and in vivo experimental approaches.Methods: Network pharmacology was adopted to detect the active components of four Traditional Chinese herbal medicine (TCM) of SX, and the key targets and signaling pathways in the treatment of RA were predicted, and the key components and targets were screened for molecular docking. The predicted targets and pathways were validated in bovine type II collagen and incomplete Freund’s adjuvant emulsifier-induced rat RA model.Results: In this study, we identified 33 active components from SX, predicted to act on 44 RA-associated targets by network pharmacology. PPI network demonstrated that TNF-α, VEGF-A, IL-2, IL-6, AKT, PI3K, STAT1 may serve as the key targets of SX for the treatment of RA. The main functional pathways involving these key targets include PI3K-AKT signaling pathway, TNF signaling pathway, NF-κB signaling pathway. Molecular docking analysis found that the active components β-amyrin, cajanin, eleutheroside A have high affinity for TNF-α, VEGFA, IL-2, AKT, and PI3K, etc. SX can improve joint swelling in Collagen-induced arthritis (CIA) rats, reduce inflammatory cell infiltration and angiogenesis in joint synovial tissue, and down-regulate IL-2, IL-6, TNF-α, VEGF, PI3K, AKT, p-AKT, NF-κBp65, the expression of p-NF-κBp65, STAT1, and PTGS2 are used to control the exacerbation of inflammation and alleviate the proliferation of synovial pannus, and at the same time play the role of cartilage protection to achieve the effect of treating RA.Conclusion: Through a network pharmacology approach and animal study, we predicted and validated the active compounds of SX and their potential targets for RA treatment. The results suggest that SX can markedly alleviate CIA rat by modulating the VEGF/PI3K/AKT signaling pathway, TNF-α signaling pathway, IL/NF-κB signaling pathway.Keywords: network pharmacology, molecular docking, rheumatoid arthritis, Sidaxue, VEGF/PI3K/AKT signaling pathway, TNF-α signaling pathway, IL/NF-κB signaling pathway

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.119
GPT teacher head0.515
Teacher spread0.395 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it