[Study on anti-hyperlipidemia mechanism of high frequency herb pairs by molecular docking method].

Traditional Chinese medicine (TCM) has definitely clinical effect in treating hyperlipidemia, but the action mechanism still need to be explored. Based on consulting Chinese Pharmacopoeia (2010), all the lipid-lowering Chinese patent medicines were analyzed by associated rules data mining method to explore high frequency herb pairs. The top three couplet medicines with high support degree were Puerariae Lobatae Radix-Crataegi Fructus, Salviae Miltiorrhizae Radix et Rhizoma-Crataegi Fructus, and Polygoni Multiflori Radix-Crataegi Fructus. The 20 main ingredients were selected from the herb pairs and docked with 3 key hyperlipidemia targets, namely 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMG-CoA reductase), peroxisome proliferator activated receptor-α (PPAR-α ) and niemann-pick C1 like 1 (NPC1L1) to further discuss the molecular mechanism of the high frequency herb pairs, by using the docking program, LibDock. To construct evaluation rules for the ingredients of herb pairs, the root-mean-square deviation (RMSD) value between computed and initial complexes was first calculated to validate the fitness of LibDock models. Then, the key residues were also confirmed by analyzing the interactions of those 3 proteins and corresponding marketed drugs. The docking results showed that hyperin, puerarin, salvianolic acid A and polydatin can interact with two targets, and the other five compounds may be potent for at least one of the three targets. In this study, the multi-target effect of high frequency herb pairs for lipid-lowering was discussed on the molecular level, which can help further researching new multi-target anti-hyperlipidemia drug.

[Construction of automatic elucidation platform for mechanism of traditional Chinese medicine].

Aim at the two problems in the field of traditional Chinese medicine (TCM) mechanism elucidation, one is the lack of detailed biological processes information, next is the low efficient in constructing network models, we constructed an auxiliary elucidation system for the TCM mechanism and realize the automatic establishment of biological network model. This study used the Entity Grammar Systems (EGS) as the theoretical framework, integrated the data of formulae, herbs, chemical components, targets of component, biological reactions, signaling pathways and disease related proteins, established the formal models, wrote the reasoning engine, constructed the auxiliary elucidation system for the TCM mechanism elucidation. The platform provides an automatic modeling method for biological network model of TCM mechanism. It would be benefit to perform the in-depth research on TCM theory of natures and combination and provides the scientific references for R&D of TCM.

[Study on prescription combination and design method based on dichotomy and greedy algorithm].

The prescription combinations of traditional Chinese medicine (TCM) focuses on the taste and channel tropism, the Qi movement, as well as the compatibility according to multiple combination principles and medicinal property and flavor combination of several traditional Chinese medicines. With the in-depth study on the prescription compatibility, researchers have realized that the medicinal property theory is the core of TCM combinations. However, there is no definite method for combinations based on medicinal properties. In this paper, the authors put forward an method for designing prescription combinations based on bipartite graph and the greedy algorithm. With the medicinal property combinations of Siweilurong Pills for example, the authors proved this method could provide ideas for quickly choosing herbal medicines for prescription combinations, and discussed the prospect of this method in substituting previous and endangered herbal medicines and banned medicinal materials.

[Formula method of medicated diet based on medicinal property combination patterns].

To propose a formula method of medicated diet based on medicinal property combination patterns in this paper under the context of lack of innovation in medicated diets. By analyzing the property combination patterns of traditional Chinese medicine and commonly used foods recorded in the pharmacopoeia, medicated diet formulae were optimized by using the greedy algorithm, with the property combination patterns of classical formulae based on the syndrome differentiation and treatment. In this paper, the Baihu Rensheng decoction, which is a classical formula for treating lung and stomach heat-derived diabetes, was taken for example in the formula design. As a result, totally 18 medicated diet formulae were developed and proved to be rational in the analysis on traditional Chinese medicines and nutriology. This method expands the way of thinking for personalized diet therapies and provides theoretical basis the industrial development and clinical application of medicated diets.

[Optimization method of MOS sensor array for identification of traditional Chinese medicine based on electronic nose].

Optimization of sensor array is a significant topic in the application of electronic nose (EN). Stepwise discriminant analysis and cluster analysis combining with screening of typical index were employed to optimize the original array in the classification of 100 samples from 10 kinds of traditional Chinese medicine based on alpha-FOX3000 EN. And the identification ability was evaluated by three algorithm including principle component analysis, Fisher discriminant analysis and random forest. The results showed that the identification ability of EN was improved since not only the effective information was maintained but also the redundant one was eliminated by the optimized array. The optimized method was eventually established, it was accurate and efficient. And the optimized array was built up, that is, S1, S2, S5, S6, S8, S12.

[Relationships between properties and functional targets of Chinese herbs].

Functional targets are the objects that Chinese herbal medicines act directly upon. If the relationships between the properties of Chinese herbs and their functional targets were analyzed clearly, it would benefit the overall understanding of the holistic mechanisms of Chinese herbal treatments. In this paper, data regarding the properties of Chinese herbs and their functional targets were collected from the 2005 edition of The People's Republic of China Pharmacopoeia. After analyzing and assessing the data, the relationships were defined between the four qi, meridian entry and medicinal functional targets and between the four qi, five flavors and mode of function. Then the relationships between a single herbal medicine and a prescription were analyzed, and the results conformed with the traditional knowledge of Chinese herbal nature and efficacy. This demonstrated that the holistic mechanisms of the properties of Chinese herbs adhere to the findings, which may be beneficial for the development and compatibility of Chinese herbal medicines.

[Standardization of the terms for Chinese herbal functions based on functional targeting].

Functional analysis concisely summarizes and concentrates on the therapeutic characteristics and features of Chinese herbal medicine. Standardization of the terms for Chinese herbal functions not only plays a key role in modern research and development of Chinese herbal medicine, but also has far-reaching clinical applications. In this paper, a new method for standardizing the terms for Chinese herbal function was proposed. Firstly, functional targets were collected. Secondly, the pathological conditions and the mode of action of every functional target were determined by analyzing the references. Thirdly, the relationships between the pathological condition and the mode of action were determined based on Chinese medicine theory and data. This three-step approach allows for standardization of the terms for Chinese herbal functions. Promoting the standardization of Chinese medicine terms will benefit the overall clinical application of Chinese herbal medicine.

Citrus fruits as a treasure trove of active natural metabolites that potentially provide benefits for human health.

Citrus fruits, which are cultivated worldwide, have been recognized as some of the most high-consumption fruits in terms of energy, nutrients and health supplements. What is more, a number of these fruits have been used as traditional medicinal herbs to cure diseases in several Asian countries. Numerous studies have focused on Citrus secondary metabolites as well as bioactivities and have been intended to develop new chemotherapeutic or complementary medicine in recent decades. Citrus-derived secondary metabolites, including flavonoids, alkaloids, limonoids, coumarins, carotenoids, phenolic acids and essential oils, are of vital importance to human health due to their active properties. These characteristics include anti-oxidative, anti-inflammatory, anti-cancer, as well as cardiovascular protective effects, neuroprotective effects, etc. This review summarizes the global distribution and taxonomy, numerous secondary metabolites and bioactivities of Citrus fruits to provide a reference for further study. Flavonoids as characteristic bioactive metabolites in Citrus fruits are mainly introduced.

Is it possible to rapidly and noninvasively identify different plants from Asteraceae using electronic nose with multiple mathematical algorithms?

Many plants originating from the Asteraceae family are applied as herbal medicines and also beverage ingredients in Asian areas, particularly in China. However, they may be confused due to their similar odor, especially when ground into powder, losing their typical macroscopic characteristics. In this paper, 11 different multiple mathematical algorithms, which are commonly used in data processing, were utilized and compared to analyze the electronic nose (E-nose) response signals of different plants from Asteraceae family. Results demonstrate that three-dimensional plot scatter figure of principal component analysis with less extracted components could offer the identification results more visually; simultaneously, all nine kinds of artificial neural network could give classification accuracies at 100%. This paper presents a rapid, accurate, and effective method to distinguish Asteraceae plants based on their response signals in E-nose. It also gives insights to further studies, such as to find unique sensors that are more sensitive and exclusive to volatile components in Chinese herbal medicines and to improve the identification ability of E-nose. Screening sensors made by other novel materials would be also an interesting way to improve identification capability of E-nose.

Identification of chinese herbal medicines from zingiberaceae family using feature extraction and cascade classifier based on response signals from e-nose.

Identification of Chinese herbal medicines (CHMs) by human experience is often inaccurate because individual ability and external factors may influence the outcome. However, it might be promising to employ an electronic nose (E-nose) to identify them. This paper presents a rapid and reliable method for identification of ten different species of CHMs from Zingiberaceae family based on their response signals from E-nose. Ten Zingiberaceae CHMs were measured and their maximum response values were analyzed by principal component analysis (PCA). Result shows that E Zhu (Curcuma phaeocaulis Val.) and Yi Zhi (Alpinia oxyphylla Miq.) could not be distinguished completely by PCA. Two solutions were proposed: (i) using BestFirst+CfsSubsetEval (BC) method to extract more discriminative features to select sensors with higher contribution rate and remove the redundant signals; (ii) employing a novel cascade classifier with two stages to enhance the distinguishing-positive rate (DPR). Based on these strategies, six features were extracted and used in different stages of the cascade classifier with higher DPRs.

Rapid Identification of Asteraceae Plants with Improved RBF-ANN Classification Models Based on MOS Sensor E-Nose.

Plants from Asteraceae family are widely used as herbal medicines and food ingredients, especially in Asian area. Therefore, authentication and quality control of these different Asteraceae plants are important for ensuring consumers' safety and efficacy. In recent decades, electronic nose (E-nose) has been studied as an alternative approach. In this paper, we aim to develop a novel discriminative model by improving radial basis function artificial neural network (RBF-ANN) classification model. Feature selection algorithms, including principal component analysis (PCA) and BestFirst + CfsSubsetEval (BC), were applied in the improvement of RBF-ANN models. Results illustrate that in the improved RBF-ANN models with lower dimension data classification accuracies (100%) remained the same as in the original model with higher-dimension data. It is the first time to introduce feature selection methods to get valuable information on how to attribute more relevant MOS sensors; namely, in this case, S1, S3, S4, S6, and S7 show better capability to distinguish these Asteraceae plants. This paper also gives insights to further research in this area, for instance, sensor array optimization and performance improvement of classification model.

GeneSearch™ BLN Assay could replace frozen section and touch imprint cytology for intra-operative assessment of breast sentinel lymph nodes.

BACKGROUND: Breast cancer sentinel lymph node (SLN) biopsy has become a common procedure. The GeneSearch™ Breast Lymph Node Assay is a real-time reverse-transcriptase polymerase chain reaction assay for detecting nodal metastases larger than 0.2 mm. The trial is a prospective multi-center clinical trial conducted to validate the assay in China. METHODS: Four hundred and seventy-nine consecutive prospective patients were enrolled from six centers. SLNs were sectioned along the short axis into multiple blocks. Odd blocks were tested by the assay intra-operatively, and even blocks were assessed by post-operative histology. Six 4- to 6-µm-thick sections were taken every 150 µm per block. In addition, intra-operative histological assessments were performed on the even blocks of 214 patients by frozen section (FS) and all blocks of 156 patients by touch imprint cytology (TIC). RESULTS: A total of 1046 SLNs were excised. Overall performance of the assay compared to post-operative histology was accuracy of 91.4 %, sensitivity of 87.5 %, and specificity of 92.9 %. There were no significant differences in assay performance of each center. After a learning curve of about 10 cases, the assay could be performed in a median time of about 35 min. The sensitivity of the assay was similar to the FS (84.9 %, P = 0.885) and was significantly higher than the TIC (70.0 %, P = 0.007) while the specificity of all were comparable. CONCLUSION: The GeneSearch™ Breast Lymph Node Assay is an accurate and rapid intra-operative assay for breast SLNs and it can replace FS and TIC for application.

Visualizing excipient composition and homogeneity of Compound Liquorice Tablets by near-infrared chemical imaging.

This study demonstrated that near-infrared chemical imaging (NIR-CI) was a promising technology for visualizing the spatial distribution and homogeneity of Compound Liquorice Tablets. The starch distribution (indirectly, plant extraction) could be spatially determined using basic analysis of correlation between analytes (BACRA) method. The correlation coefficients between starch spectrum and spectrum of each sample were greater than 0.95. Depending on the accurate determination of starch distribution, a method to determine homogeneous distribution was proposed by histogram graph. The result demonstrated that starch distribution in sample 3 was relatively heterogeneous according to four statistical parameters. Furthermore, the agglomerates domain in each tablet was detected using score image layers of principal component analysis (PCA) method. Finally, a novel method named Standard Deviation of Macropixel Texture (SDMT) was introduced to detect agglomerates and heterogeneity based on binary image. Every binary image was divided into different sizes length of macropixel and the number of zero values in each macropixel was counted to calculate standard deviation. Additionally, a curve fitting graph was plotted on the relationship between standard deviation and the size length of macropixel. The result demonstrated the inter-tablet heterogeneity of both starch and total compounds distribution, simultaneously, the similarity of starch distribution and the inconsistency of total compounds distribution among intra-tablet were signified according to the value of slope and intercept parameters in the curve.