Dataset Information

DTGS: Method for Effective Components Identification from Traditional Chinese Medicine Formula and Mechanism Analysis.

ABSTRACT: Because of the complexity of the components in Traditional Chinese Medicine formula (TCM formula), it is still a challenge to identify its effective components, to elucidate the mechanism of the components, and to discover the relationship between components and therapy objectives. In this paper, a method called directed TCM grammar systems (dTGS) for effective component identification was proposed using entity grammar systems (EGS) as the theoretical framework. The component-disease relationship of a TCM formula (i.e., Bai-Hu decoction plus Wasting-Thirsting formula, BHDWT) and one disease (i.e., type 2 diabetes mellitus) treated with it was studied, and the effective component groups (ECGs) were identified. 19 compounds were found acting on 20 proteins in type 2 diabetes mellitus (T2D) disease network, and 15 compounds were determined as the candidate effective components. Results indicated that this method can be used to identify the effective components and provide an innovative way to elucidate the molecular mechanism of TCM formulas.

SUBMITTER: Luo J

PROVIDER: S-EPMC3878852 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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dTGS: Method for Effective Components Identification from Traditional Chinese Medicine Formula and Mechanism Analysis.

Luo Ji J Ren Yinglong Y Gu Hao H Wu Yi Y Wang Yun Y

Evidence-based complementary and alternative medicine : eCAM 20131218

Because of the complexity of the components in Traditional Chinese Medicine formula (TCM formula), it is still a challenge to identify its effective components, to elucidate the mechanism of the components, and to discover the relationship between components and therapy objectives. In this paper, a method called directed TCM grammar systems (dTGS) for effective component identification was proposed using entity grammar systems (EGS) as the theoretical framework. The component-disease relationshi ...[more]

PMID: 24454516

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Project description:Fuzheng-Huayu formula (FZHY), a Chinese herbal mixture prescription, has been proven effective in treating liver fibrosis and cirrhosis in both clinical trials and animal experiments. In this study we assessed the metabolic mechanisms of traditional Chinese medicine (TCM) syndrome-based FZHY treatment in liver cirrhosis (LC). A total of 113 participants, including 50 healthy controls and 63 LC patients, were recruited. According to the diagnosis and differentiation of the TCM syndromes, the LC patients were classified into 5 TCM syndrome groups including the liver stagnation syndrome (LSS), spleen deficiency and damp overabundance syndrome (SDDOS), damp-heat accumulation syndrome (DHAS), liver-kidney Yin deficiency syndrome (LKYDS), and blood stagnation syndrome (BSS), and administered FZHY for 6 months. FZHY treatment significantly decreased serum levels of hyaluronic acid (HA), a biochemical marker for LC, as well as TCM syndrome scores (the TCM syndrome scores were decreased in all the groups with significant decreases in the LSS and LKYDS groups). Furthermore, FZHY treatment gradually shifted the metabolic profiles of LC patients from a pathologic state to a healthy state, especially in LC patients with LSS and LKYDS. Twenty-two differently altered metabolites (DAMs) were identified, including carbohydrates, amino acids, fatty acids, etc with 9 DAMs in LSS patients, 9 in LKYDS patients, and 4 in other patients. The metabolic pathways involved in the conversion of amino acids and the body's detoxification process were regulated first, followed by the pathways involved in the body's energy supply process. In conclusion, the evaluation of the effect of TCM syndrome-based FZHY treatment show that FZHY has a better effect on LKYDS and LSS than on the other TCM syndromes, and the metabolic mechanisms might be involved in the increased detoxification function in LKYDS and the improvement of energy supply in LSS, which provides important evidence for the clinical application of TCM syndrome-based treatment.

Project description:Purpose: This study proposes an S-TextBLCNN model for the efficacy of traditional Chinese medicine (TCM) formula classification. This model uses deep learning to analyze the relationship between herb efficacy and formula efficacy, which is helpful in further exploring the internal rules of formula combination. Methods: First, for the TCM herbs extracted from Chinese Pharmacopoeia, natural language processing (NLP) is used to learn and realize the quantitative expression of different TCM herbs. Three features of herb name, herb properties, and herb efficacy are selected to encode herbs and to construct formula-vector and herb-vector. Then, based on 2,664 formulae for stroke collected in TCM literature and 19 formula efficacy categories extracted from Yifang Jijie, an improved deep learning model TextBLCNN consists of a bidirectional long short-term memory (Bi-LSTM) neural network and a convolutional neural network (CNN) is proposed. Based on 19 formula efficacy categories, binary classifiers are established to classify the TCM formulae. Finally, aiming at the imbalance problem of formula data, the over-sampling method SMOTE is used to solve it and the S-TextBLCNN model is proposed. Results: The formula-vector composed of herb efficacy has the best effect on the classification model, so it can be inferred that there is a strong relationship between herb efficacy and formula efficacy. The TextBLCNN model has an accuracy of 0.858 and an F1-score of 0.762, both higher than the logistic regression (acc = 0.561, F1-score = 0.567), SVM (acc = 0.703, F1-score = 0.591), LSTM (acc = 0.723, F1-score = 0.621), and TextCNN (acc = 0.745, F1-score = 0.644) models. In addition, the over-sampling method SMOTE is used in our model to tackle data imbalance, and the F1-score is greatly improved by an average of 47.1% in 19 models. Conclusion: The combination of formula feature representation and the S-TextBLCNN model improve the accuracy in formula efficacy classification. It provides a new research idea for the study of TCM formula compatibility.

Dataset Information

DTGS: Method for Effective Components Identification from Traditional Chinese Medicine Formula and Mechanism Analysis.

Publications

dTGS: Method for Effective Components Identification from Traditional Chinese Medicine Formula and Mechanism Analysis.

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