Publications by authors named "Dai-Yan Zhang"

Article Synopsis
  • The study focuses on identifying chemical-target interactions in traditional medicine, specifically looking at the herbal treatments for cardiovascular diseases.
  • The research utilizes the node2vec algorithm alongside molecular docking to predict and verify drug-herb interactions using data from known cardiovascular drugs and common herbs.
  • Results showed node2vec outperformed other algorithms, successfully predicting interactions, with follow-up experiments confirming the effectiveness of some herbal chemicals in enhancing protein stability and inducing gene expression changes.
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Rheumatoid arthritis (RA) is a chronic autoimmune disease triggered by a cascading inflammatory response. Sigesbeckia Herba (SH) has long been utilized as a traditional remedy to alleviate symptoms associated with rheumatism. Our previous study found that leocarpinolide B (LB), a sesquiterpene lactone isolated from the whole plant of SH, possesses potent a anti-inflammatory effect on macrophages.

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Ethnopharmacological Relevance: Salvia miltiorrhiza (Danshen, DS), the dried root and rhizome of Salvia miltiorrhiza Bunge and Ligusticum chuanxiong (Chuanxiong, CX), the dried rhizomes of Ligusticum striatum DC are effective in invigorating blood circulation and eliminating stasis which is highly related with cardiovascular disease (CVD).

Aim Of Study: The identification of activity-based chemical markers is very important, but the complex mechanism of "multi-component, multi-target, and multi-effect" within traditional Chinese medicine (TCM) poses a great challenge to this work. In this study, we combined network pharmacological prediction with experimental validation of the DS and CX to explore an effective method for discovering quality control (QC) of antithrombotic herbs by clarifying the intermediate layer "module/cluster" between the whole complex system and a single component.

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In this study, a high-performance thin layer chromatography (HPTLC) method by two step gradient elution with two mobile phases was developed for the simultaneous analysis of seven constituents in Ophiopogonis Radix. The chromatography was performed on silica gel 60 F plate with dichloromethane-methanol-ethyl acetate-water (70:25:12:3, ///) and dichloromethane-methanol (300:1, /) as the mobile phase for two step gradient elution. Then, the HPTLC profiles were observed after derivatization with 10% sulfuric acid in ethanol solution.

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Traditional Chinese medicine(TCM) has unique advantages in the prevention and treatment of diseases owing to its holistic view and more than 2 000 years of experience in the clinical use of natural medicine. The "holistic" characteristic of TCM gives birth to a new generation of research paradigm featuring "network" and "system", which has been developing rapidly in the era of biomedical big data and artificial intelligence. Network pharmacology, a representative research field, provides new ideas and methods for the research of the interdiscipline of artificial intelligence and medicine, the analysis of massive biomedical data, and the transformation from data to knowledge.

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In this study; a spectrum-effect relationship analysis combined with a high-performance liquid chromatography-mass spectrometry (LC-MS) analysis was established to screen and identify active components that can inhibit thrombin and factor Xa (THR and FXa) in Salviae Miltiorrhizae Radix et Rhizoma-Chuanxiong Rhizoma (Danshen-Chuanxiong) herbal pair. Ten potential active compounds were predicted through a canonical correlation analysis (CCA), and eight of them were tentatively identified through an LC-MS analysis. Furthermore; the enzyme inhibitory activity of six available compounds; chlorogenic acid; -ligustilide; caffeic acid; ferulic acid; tanshinone I and tanshinone IIA; were tested to verify the feasibility of the method.

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