A Core Drug Discovery Framework from Large-Scale Literature for Cold Pathogenic Disease Treatment in Traditional Chinese Medicine.

Cold pathogenic disease is a widespread disease in traditional Chinese medicine, which includes influenza and respiratory infection associated with high incidence and mortality. Discovering effective core drugs in Chinese medicine prescriptions for treating the disease and reducing patients' symptoms has attracted great interest. In this paper, we explore the core drugs for curing various syndromes of cold pathogenic disease from large-scale literature. We propose a core drug discovery framework incorporating word embedding and community detection algorithms, which contains three parts: disease corpus construction, drug network generation, and core drug discovery. First, disease corpus is established by collecting and preprocessing large-scale literature about the Chinese medicine treatment of cold pathogenic disease from China National Knowledge Infrastructure. Second, we adopt the Chinese word embedding model SSP2VEC for mining the drug implication implied in the literature; then, a drug network is established by the semantic similarity among drugs. Third, the community detection method COPRA based on label propagation is adopted to reveal drug communities and identify core drugs in the drug network. We compute the community size, closeness centrality, and degree distributions of the drug network to analyse the patterns of core drugs. We acquire 4681 literature from China national knowledge infrastructure. Twelve significant drug communities are discovered, in which the top-10 drugs in every drug community are recognized as core drugs with high accuracy, and four classical prescriptions for treating different syndromes of cold pathogenic disease are discovered. The proposed framework can identify effective core drugs for curing cold pathogenic disease, and the research can help doctors to verify the compatibility laws of Chinese medicine prescriptions.

The effects of tacrolimus plus phototherapy in the treatment of vitiligo: a meta-analysis.

The objective of this meta-analysis was performed to compare the effects of tacrolimus plus phototherapy in the treatment of patients with vitiligo. Relevant studies were identified by searching PubMed, Embase, and Web of Science databases. The main outcomes of interest included excellent response (≥ 75% repigmentation), good response (50-75% repigmentation), moderate response (25%-50% repigmentation), and poor response (< 25% repigmentation). Risk ratio (RR) with 95% confidence intervals (95% CIs) was used to calculate the data. Eleven studies were included in this study. Compared with phototherapy alone, combination treatment of tacrolimus and phototherapy significantly improved excellent response rate (RR = 1.40, 95% CI 1.16, 1.69; P < 0.001) and reduced the poor response rate (RR = 0.37, 95% CI 0.22, 0.61; P = 0.001). However, the good response rate (RR = 1.00, 95% CI 0.59, 1.69, P = 1.000) and moderate response rate (RR = 0.91, 95% CI 0.60, 1.38; P = 0.653) were not significantly different between the two treatments. Subgroup analysis suggested that combination treatment had a higher excellent response rate than phototherapy alone for lesions located in the face and proximal limbs. Both NB-UVB and EL, when added to tacrolimus, resulted in a significantly higher excellent response rate than they were used alone. Meta-regression analysis showed that age was a predictive factor that influenced the effect of combination treatment on an excellent response, in which children had a high excellent response to the treatment. Other demographic and clinical variables, including gender, disease duration, family history, and type of vitiligo, did not have any impact on the treatment effect. Combination treatment with tacrolimus and phototherapy was more effective than phototherapy monotherapy for patients with vitiligo, especially in the lesions located in the face and proximal limbs. More large-scale, well-performed trials are needed to verify our findings.

A Semantic Analysis and Community Detection-Based Artificial Intelligence Model for Core Herb Discovery from the Literature: Taking Chronic Glomerulonephritis Treatment as a Case Study.

The Traditional Chinese Medicine (TCM) formula is the main treatment method of TCM. A formula often contains multiple herbs where core herbs play a critical therapeutic effect for treating diseases. It is of great significance to find out the core herbs in formulae for providing evidences and references for the clinical application of Chinese herbs and formulae. In this paper, we propose a core herb discovery model CHDSC based on semantic analysis and community detection to discover the core herbs for treating a certain disease from large-scale literature, which includes three stages: corpus construction, herb network establishment, and core herb discovery. In CHDSC, two artificial intelligence modules are used, where the Chinese word embedding algorithm ESSP2VEC is designed to analyse the semantics of herbs in Chinese literature based on the stroke, structure, and pinyin features of Chinese characters, and the label propagation-based algorithm LILPA is adopted to detect herb communities and core herbs in the herbal semantic network constructed from large-scale literature. To validate the proposed model, we choose chronic glomerulonephritis (CGN) as an example, search 1126 articles about how to treat CGN in TCM from the China National Knowledge Infrastructure (CNKI), and apply CHDSC to analyse the collected literature. Experimental results reveal that CHDSC discovers three major herb communities and eighteen core herbs for treating different CGN syndromes with high accuracy. The community size, degree, and closeness centrality distributions of the herb network are analysed to mine the laws of core herbs. As a result, we can observe that core herbs mainly exist in the communities with more than 25 herbs. The degree and closeness centrality of core herb nodes concentrate on the range of [15, 40] and [0.25, 0.45], respectively. Thus, semantic analysis and community detection are helpful for mining effective core herbs for treating a certain disease from large-scale literature.

Anti-degranulation response of herbal formula in RBL-2H3 cells.

Allergic diseases not only bring serious economic burden to the patients, but also consume a lot of substantial resources of social medical systems. Thus, the prevention and treatment of allergic diseases are imperative. In this study, the anti-degranulation activity of herbal formula was evaluated using the rat basophil leukemia cells (RBL-2H3) as in vitro model. The morphological and biophysical properties of RBL-2H3 cells before and after treatment with herbal formula were also determined. Notably, the herbal formula exhibits clearly inhibited degranulation by RBL-2H3 cells in a concentration-dependent manner without cytotoxic effect. Therefore, this herbal formula can be used as an alternative and promising therapeutic agent to ameliorate allergic diseases.

AMPK activation is involved in hypoglycemic and hypolipidemic activities of mogroside-rich extract from Siraitia grosvenorii (Swingle) fruits on high-fat diet/streptozotocin-induced diabetic mice.

Previous studies suggested the anti-diabetic effect of mogrosides in type 1 diabetes. To evaluate the potential effect of mogrosides in type 2 diabetes, we herein investigated the hypoglycemic and hypolipidemic effects and the underlying mechanism of mogroside-rich extract (MGE) using a high-fat diet in combination with streptozotocin (STZ)-induced diabetic model. MGE feeding for 5 weeks did not result in any obvious impact on the body weight and energy intake, but caused a moderate decrease of organ index in diabetic mice. MGE-supplemented diabetic mice showed a notable reduction of fasting blood glucose (FBG), glycated serum protein (GSP), serum insulin, homeostasis model assessment-insulin resistance (HOMA-IR), and serum atherogenic lipid profiles in a dose-dependent manner, whereas significant increases in the anti-atherogenic lipid profile, insulin sensitivity, glucose and insulin tolerance capacity with high dose (300 mg kg-1) MGE were observed (P < 0.01). Besides, hepatocyte polymorphism, lipid accumulation and steatosis were ameliorated and restored to near normal at the high dose. Furthermore, hepatic 5'AMP-activated protein kinase (AMPK) signaling was dose-dependently activated. Accordingly, the mRNA levels of hepatic gluconeogenic and lipogenic genes were downregulated and fat oxidation-associated genes were upregulated. These findings suggest that the hypoglycemic and hypolipidemic activities of MGE are probably attributed to the attenuation of insulin resistance and activation of hepatic AMPK signaling.