Visualizing research trends and identifying hotspots of herbal components for treating cardiovascular diseases: A bibliometric analysis from 2000 to 2023.

OBJECTIVE: The objective of this study was to investigate the global research trends in herbal medicine for the treatment of cardiovascular disease (CVD) from 2000 to 2023. A bibliometric approach was employed to analyze international collaborations, knowledge structures, emerging trends, and research frontiers. METHOD: The Web of Science (WOS) core collection was utilized as the database, employing the search formula (((TS = (traditional Chinese medicine)) OR TS = (Chinese herbal medicinal ingredient)) OR TS = (Chinese herbal medicinal constituent)) AND TS = (cardiovascular disease) to conduct the search. The search period spanned from January 1, 2000, to February 14, 2023, and the literature type included articles and reviews. RESULTS: A total of 1478 papers were included in the analysis after searching the WOS database and excluding conference proceedings, news articles, retractions, editorials, and letters. China demonstrated the highest number of publications, followed by the United States and Taiwan (China). The institution with the highest publications was the Chinese Academy of Medical Sciences. China, the United States, and India were the main countries involved in research in this field, and there was significant collaboration among them. The hotspots related to herbal components for treating cardiovascular diseases from 2000 to 2023 included systematic reviews, ischemic reperfusion injury, global burden, type 2 diabetes, and protection. CONCLUSION: This paper provides a reference for the future development of herbal research in cardiovascular aspects by revealing the current status, hotspots, and trends of global herbal research in cardiovascular factors over more than 20 years. Identification of potential collaborators and institutions can assist researchers in exploring new directions for future research and discovering new perspectives for potential collaborations in this field.

Exploring the mechanism of Erchen decoction in the treatment of atherosclerosis based on network pharmacology and molecular docking.

BACKGROUND: Atherosclerosis (AS) is the cause of most cardiovascular diseases and imposes a huge economic burden on society. Erchen decoction (ECD) is an effective formula for treating AS, but its therapeutic mechanism remains unclear. This study will explore the mechanism of ECD mechanism for treating AS using network pharmacology and molecular docking. METHODS: We searched ECD chemical composition information and related targets via Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform and SwissTargetPrediction databases, and gene names correction was performed using the UniProt database. AS-related targets were retrieved from OMIM, GeneCards, and DrugBank databases, and Venny 2.1 were used for intersection analysis. Protein-protein interaction network was constructed by the STRING database, and an interactive network of the drug-component-target-disease was drawn using the Cytoscape 3.9.0 software. Gene ontology and Kyoto Gene and Genome Encyclopedia enrichment analysis were performed by the DAVID database, and molecular docking validation of vital active ingredients and action targets of ECD was performed using AutoDock Vina software. RESULTS: The 127 active components of ECD act on AS by regulating 231 targets and 151 pathways. The 6 core components are quercetin, polyporenic acid C, 18α-hydroxyglycyrrhetic acid, glyuranolide, 3beta-hydroxychloroxy-24-methylene-8-lanostene-21-oic acid, and obacunone. They may regulate AS by regulating core target genes, such as JUN, SRC, AKT1, PTGS2, ESR1, AR, MAPK1, MAPK3, and RELA, and acting on multiple vital pathways, such as AGE-RAGE signaling pathway in diabetic complications, Lipid and AS, and Fluid shear stress and AS. Molecular docking showed that the selected target protein had good binding activity to the active ingredient. CONCLUSIONS: ECD has the characteristics of multi-components, multi-targets and multi-pathways in the treatment of AS. The results provide a theoretical basis for the clinical application of ECD and its mechanism.

The preliminary development and clinical verification of the positive index score scale of "Heart Arthralgia Syndrome".

BACKGROUND: In recent years, the age of onset for coronary heart disease (CHD) has become one of the leading causes of death worldwide. The medical treatments occasionally cause side effects; therefore, there is still an urgent need to develop new therapeutic modalities for CHD in clinical practice. "Heart Arthralgia Syndrome (HAS)" is a general term for CHD with arthralgia symptoms proposed by our team based on clinical experience. At present, there is little in-depth research on the treatment of HAS by TCM. Pick Complex Therapy (PCT) is an innovative and developed theory of collateral acupuncture therapy for HAS. METHODS: We collected data from 276 patients who met the criteria for (coronary heart disease with numbness of neck, shoulder, waist, and leg). We selected 24 diagnostic criteria for HAS by means of multiple methods, including Cronbach's α coefficient, retest reliability, subjective evaluation, discrete trend, Pearson's rank correlation coefficient and factor analysis method. We thereafter evaluated the reliability, validity and responsiveness of the scale. In the clinical validation phase, we verified whether the preliminary developed positive index (PI) scale can guide clinical practice. Forty (40) patients with HAS were selected in the study. SPSS23.0 statistical software was used for statistical processing and analysis. RESULTS: Assessment results of the initial PI scale for HAS: the average time to complete the scale was 7.47 ± 3.59 minutes. Cronbach's α coefficient for the initial table was 0.711, the retest reliability was 0.897, the Kaiser-Meyer-Olkin test result was 0.844, and the Bartlett test result was 2502.300. Following maximum variance rotation analysis, the cumulative variance contribution rate was determined to be 66.605%. In the clinical validation phase of the PI scale, we tested 40 patients before and after the PCT treatments. After 3 measurements, the correlation between the PI scale for HAS and the angina pectoris grading scoring method table decreased gradually. The last 2 measurement results of study indicated that there was a significant correlation between the PI scale and thrombin time, while physical and chemical examination showed no significant changes. CONCLUSION: The PI scale for HAS can be widely used in the clinic as a preliminary evaluation tool for guiding PCT.

Reconstruction and Differential Expression Profiling Core Target Analyses of the circRNA-miRNA-mRNA Network Based on Competitive Endogenous RNAs in Ulcerative Colitis.

Ulcerative colitis (UC) is a common autoimmune disease worldwide. Circular RNA (circRNA) is a type of noncoding ribonucleic acids (ncRNAs). In addition to their roles in numerous biological processes, circRNAs are also linked to a vast range of diseases including UC. Although previous studies have examined many circRNAs, the physiological and pathological roles of the circRNA-associated competing endogenous RNA (ceRNA) network in UC remain unclear. Thus, we constructed a circRNA-miRNA-mRNA network based on the ceRNA hypothesis by analyzing data from the National Center for Biotechnology Information Gene Expression Omnibus (NCBI-GEO) database. Genes with higher degree values than others in the ceRNA network were selected as central nodes when constructing the corresponding core subnetworks. To fully understand the biological function of the ceRNA network, we entered all differentially expressed mRNAs (DEmRNAs) from the ceRNA network into the Database for Annotation and Integrated Discovery (DAVID), which was used to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. We further entered DEmRNAs into the STRING database for protein-protein interaction (PPI) network analysis. The results elucidated that the ceRNA network comprised 403 circRNA nodes, 5 miRNA nodes, 138 mRNA nodes, and 559 edges. Three core ceRNA subnetworks centered on hsa-miR-342-3p, hsa-miR-199a-5p, and hsa-miR-142-3p were reconstructed in this study. GO and KEGG enrichment analyses identified 167 enriched GO categories and 14 enriched KEGG pathway terms. The core PPI network was composed of 15 core targets, of which CD44, HIF1A, and MMP2 were the most significant. In summary, 3 hub miRNAs (hsa-miR-342-3p, hsa-miR-199a-5p, hsa-miR-142-3p) and 3 hub genes (CD44, HIF1A, and MMP2) might play an important role in the development of UC. These hub nodes, first proposed here, might also be used as potential diagnostic markers and therapeutic targets.

Mining Important Herb Combinations of Traditional Chinese Medicine against Hypertension Based on the Symptom-Herb Network Combined with Network Pharmacology.

Although data mining methods are extensively used in the rule analysis of famous old traditional Chinese medicine (TCM) experts' prescriptions for the treatment of hypertension, most of them only mine the association between herbs and herbs, ignoring the importance of symptoms in the disease. This study collected 439 cases of hypertension treated by famous old TCM experts from the FangNet platform. Using the structure network algorithm, the symptom-herb network was constructed, which redefined the importance of herb in disease. Based on the network, 21 driver herbs, 76 herb pairs, and 41 symptom-herb associations were mined. Finally, the basic prescription composed of Gouteng (Uncariae Ramulus cum Uncis), Huanglian (Coptidis Rhizoma), Chuanxiong (Chuanxiong Rhizoma), Gegen (Puerariae Lobatae Radix), Danggui (Angelicae Sinensis Radix), and Huangqin (Scutellariae Radix) was found. These herbs are the most significant among all herbs, and they have a potential correlation with each other. To further verify the rationality of the data mining results, we adopted the network pharmacology method. Network pharmacological analysis shows that the five core targets in the basic prescription include IL6, VEGFA, TNF, TP53, and EGF, which link 10 significant active compounds and 7 important KEGG pathways. It was predicted that anti-inflammatory, antioxidant, vascular endothelial protection, emotion regulation, and ion channel intervention might be the main mechanisms of the basic prescription against hypertension. This study reveals the prescription rule of famous old TCM experts for treating hypertension from a new perspective, which provides a new approach to inherit the academic experience of famous old TCM experts and develop new drugs.

Detection of Herbal Combinations and Pharmacological Mechanisms of Clinical Prescriptions for Coronary Heart Disease Using Data Mining and Network Pharmacology.

Though widely used in the treatment of coronary heart disease (CHD), the mechanism of traditional Chinese medicine (TCM) is still unclear because of its complex prescription rules. This study prospectively collected 715 prescriptions of TCM for the treatment of CHD. The characteristics of TCM in prescriptions were described and analyzed, and the rules of prescriptions were analyzed by using association rules. Frequency statistics showed that the high-frequency herbs with a frequency of more than 60% were Gan-cao, Huang-qi, Dang-gui, Chuan-xiong, Yan-hu-suo, and San-qi. The high-frequency herb combinations were summarized by using association rules. By using the method of the "Top N groups" to excavate the empirical prescriptions, the basic prescriptions for treating CHD were summarized. We named the intersection herbs of the basic prescriptions and the high frequency herbs as the core herbal prescription. To explore the possible mechanisms underlying the anti-CHD effect of the core herbal prescription, the bioactive components of core herbal prescription and their targets were screened out by using network pharmacology. Molecular docking was performed between the bioactive components and core targets. A total of 28 potential active ingredients and 5 core targets were identified for the treatment of CHD with core herbal prescription. The enrichment analysis results indicated that the mechanism of action mainly involved neuroactive ligand-receptor interaction and calcium signaling pathway. The commonly used herbal pairs for CHD with qi deficiency and blood stasis syndrome were Huang-qi and Dang-gui. The mechanism of action of common herbal pairs was also studied by network pharmacology. This study summarized the prescription rule of TCM in the treatment of CHD and may provide a new idea for the treatment of CHD.

Mechanisms of Rhizoma Coptidis against type 2 diabetes mellitus explored by network pharmacology combined with molecular docking and experimental validation.

This study systematically explored the underlying mechanism of Rhizoma Coptidis against type 2 diabetes mellitus (T2DM) by using network pharmacology and molecular docking and experimental validation. We retrieved and screened active compounds of Rhizoma Coptidis and corresponding T2DM-related targets across multiple databases. PPI networks of the genes were constructed using STRING, and the core targets were screened via topological analysis. GO and KEGG enrichment analyses were performed by using DAVID. Finally, molecular docking and experimental studies were performed after bioinformatic analysis for verification. There were 14 active compounds and 19 core targets of Rhizoma Coptidis-T2DM, of which quercetin was identified as the main compound and IL6, VEGFA and TNF were the most significant core targets. GO and KEGG enrichment analyses showed that Rhizoma Coptidis ameliorated T2DM by regulating multiple biological processes and pathways. Docking studies indicated that IL6, VEGFA and TNF could stably bind with all active compounds of Rhizoma Coptidis. The results of our experiments revealed that Rhizoma Coptidis could inhibit the expression of IL6 and TNFα and enhance islet cell viability. This study suggests anti-inflammatory therapeutic effects of Rhizoma Coptidis on T2DM, thereby providing a scientific basis and new insight for further research on the antidiabetic effect of Rhizoma Coptidis.

Efficacy and safety of Huangkui capsule for diabetic nephropathy: A protocol for systematic review and meta-analysis.

BACKGROUND: Diabetic nephropathy (DN) is 1 of the most serious complications of diabetes mellitus and the leading cause of end-stage renal disease in the world. Huangkui capsule, extracted from Abelmoschus manihot (L.) medic (AM), has been widely used to treat DN. However, there is no consensus on the efficacy of Huangkui capsule for DN. This study aims to perform meta-analysis to systematically review the efficacy and safety of Huangkui capsule. METHODS: The following 9 electronic databases will be comprehensively searched: PubMed, web of science, MEDLINE, Embase, Cochrane Library, China National Knowledge Infrastructure, Chinese Scientific Journals Database, Wanfang data, and Chinese BioMedicine Literature Database. The retrieval time is from their inception to May 2021. According to the inclusion and exclusion criteria, 2 reviewers independently completed the study selection, data extraction, risk of bias assessment, and data synthesis. Review Manager Version 5.3 software will be used to conduct meta-analysis. RESULTS: This study provides a high-quality synthesis to assess the efficacy of Huangkui capsule for treating diabetic nephropathy. CONCLUSION: The result of this systematic review will provide objective evidence-based basis to judge the effectiveness and safety of Huangkui capsule on diabetic nephropathy.

A clustering method of Chinese medicine prescriptions based on modified firefly algorithm.

This paper is aimed to study the clustering method for Chinese medicine (CM) medical cases. The traditional K-means clustering algorithm had shortcomings such as dependence of results on the selection of initial value, trapping in local optimum when processing prescriptions form CM medical cases. Therefore, a new clustering method based on the collaboration of firefly algorithm and simulated annealing algorithm was proposed. This algorithm dynamically determined the iteration of firefly algorithm and simulates sampling of annealing algorithm by fitness changes, and increased the diversity of swarm through expansion of the scope of the sudden jump, thereby effectively avoiding premature problem. The results from confirmatory experiments for CM medical cases suggested that, comparing with traditional K-means clustering algorithms, this method was greatly improved in the individual diversity and the obtained clustering results, the computing results from this method had a certain reference value for cluster analysis on CM prescriptions.