Intervention effects and mechanism of Toddalia asiatica on cardiovascular damage in rats with collagen-induced arthritis / 中国药房

OBJECTIVE To investigate the intervention effects and potential mechanism of Miao medicine Toddalia asiatica on cardiovascular damage in rats with collagen-induced arthritis （CIA） based on vitamin D （VD） and neutrophil extracellular traps （NETs）. METHODS SD rats were randomly divided into the normal group （9 rats） and the modeling group （61 rats）. CIA model was prepared by multi-point injection of type Ⅱ bovine collagen+Fisher’s incomplete adjuvant； the model rats were randomly divided into the model group， methotrexate group （positive control， 1.5 mg/kg， twice a week）， vitamin D group [pathway validation， 1 000 IU/（kg·d）， once a day]， T. asiatica low-dose， medium-dose and high-dose groups [0.54， 1.08， 2.16 g/（kg·d）， calculated by crude drug， once a day]， with 9 rats in each group； they were given relevant medicine intragastrically for 4 consecutive weeks. Arthritis index scoring was performed after modeling and before administration， and plantar thickness was measured before and after the last administration； the histopathological changes of ankle joint， heart and abdominal aorta were observed in rats； the serum contents of myeloperoxidase （MPO）， interleukin-6 （IL-6） and 25-hydroxyvitamin D3 [25（OH）D3] were detected； the expressions of peptidylarginine deiminase 4 （PAD4）， NETs markers [citrullinated histone H3（CitH3）， MPO]， VD-related indicators [vitamin D receptor （VDR）， 25-hydroxyvitamin D-1α-hydroxylase （CYP27B1）] and IL-6 were determined in cardiac tissue. RESULTS Compared with the normal group， the plantar thickness of the arthritis index increased significantly in the model group （P＜0.01）. The obvious inflammatory cell infiltration and fibrous tissue hyperplasia were found in the ankle joint， the obvious myocardial fiber （No.2019YFC171250101） vacuoles and thickening of some surrounding blood vessel walls were found in the heart tissue， and the endothelial detachment was found in the abdominal aorta. The contents of MPO and IL-6 in serum increased significantly（P＜0.01），while the level of 25（OH）D3 decreased significantly （P＜0.01）； the protein expressions of PAD4， CitH3， MPO and IL-6 in myocardial tissue up-regulated significantly （P＜0.01）， while protein expression of VDR and CYP27B1 changed to acertain extent without significance （P＞0.05）. Compared with the model group， the pathological changes of ankle joints and cardiac tissue in rats were significantly improved in administration groups， and the above indicators were generally reversed （P＜0.05 or P＜0.01）. CONCLUSIONS T. asiatica can improve rheumatoid arthritis symptoms and cardiovascular damage by inhibiting the formation of NETs and inflammatory response， the mechanism of which may be associated with the regulation of VD expression.

Mechanism of Epimedium intervention in heart failure based on network pharmacology and molecular docking technology.

To analyze the pharmacological mechanism of Epimedium in regulating heart failure (HF) based on the network pharmacology method, and to provide a reference for the clinical application of Epimedium in treating HF. Obtaining the main active ingredients and their targets of Epimedium through TCMSP (Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform) database. Access to major HF targets through Genecards, OMIM, PharmGKB, Therapeutic Target Database, Drug Bank database. Protein interaction analysis using String platform and construction of PPI network. Subsequently, Cytoscape software was used to construct the "Epimedium active ingredient-heart failure target" network. Finally, the molecular docking is verified through the Systems Dock Web Site. The core active ingredients of Epimedium to regulate HF are quercetin, luteolin, kaempferol, etc. The core targets are JUN, MYC, TP53, HIF1A, ESR1, RELA, MAPK1, etc. Molecular docking validation showed better binding activity of the major targets of HF to the core components of Epimedium. The biological pathways that Epimedium regulates HF mainly act on lipid and atherosclerotic pathways, PI3K-Akt signaling pathway, and chemoattractant-receptor activation. And its molecular functions are mainly DNA-binding transcription factor binding, RNA polymerase II-specific DNA-binding transcription factor binding, and neurotransmitter receptor activity. This study reveals the multi-component, multi-target and multi-pathway mechanism of action of Epimedium in regulating mental failure, and provides a basis for the clinical development and utilization of Epimedium to intervene in HF.

Construction and analysis of heart failure diagnosis model based on random forest and artificial neural network.

Heart failure is a global health problem and the number of sufferers is increasing as the population grows and ages. Existing diagnostic techniques for heart failure have various limitations in the clinical setting and there is a need to develop a new diagnostic model to complement the existing diagnostic methods. In recent years, with the development and improvement of gene sequencing technology, more genes associated with heart failure have been identified. We screened for differentially expressed genes in heart failure using available gene expression data from the Gene Expression Omnibus database and identified 6 important genes by a random forest classifier (ASPN, MXRA5, LUM, GLUL, CNN1, and SERPINA3). And we have successfully constructed a new heart failure diagnostic model using an artificial neural network and validated its diagnostic efficacy in a public dataset. We calculated heart failure-related differentially expressed genes and obtained 24 candidate genes by random forest classification, and selected the top 6 genes as important genes for subsequent analysis. The prediction weights of the genes of interest were determined by the neural network model and the model scores were evaluated in 2 independent sample datasets (GSE16499 and GSE57338 datasets). Since the weights of RNA-seq predictions for constructing neural network models were theoretically more suitable for disease classification of RNA-seq data, the GSE57338 dataset had the best performance in the validation results. The diagnostic model derived from our study can be of clinical value in determining the likelihood of HF occurring through cardiac biopsy. In the meantime, we need to further investigate the accuracy of the diagnostic model based on the results of our study.