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Picrasma quassioides (P. quassioides) has been widely used as a traditional Chinese medicine for clearing fever and detoxification. Previous phytochemical studies have identified a novel dihydrobenzofuran type neolignan, picrasmalignan A, isolated from the stems of P. quassioides. In the present study, the in vitro anti inflammatory effects and molecular mechanisms of picrasmalignan A have been investigated in cultured RAW 264.7 cells, a mouse macrophage like cell line. A Griess assay was used to demonstrate the inhibitory effect of picrasmalignan A on the overproduction of nitric oxide (NO). An enzyme linked immunosorbent assay was used to determine the levels of pro inflammatory cytokines, including tumor necrosis factorα (TNFα) and interleukin 6 (IL 6). The inhibitory effect on the enzymatic activity of cyclooxygenase 2 (COX 2) and inducible nitric oxide synthase (iNOS) was observed by colorimetric and fluorimetric assays, respectively. Western blotting was conducted to detect the expression of iNOS and COX 2. Results showed that picrasmalignan A suppressed lipopolysaccharide stimulated NO production and pro inflammatory cytokine secretion, including TNFα and IL 6, in a dose dependent manner. It also significantly inhibited the expression and enzymatic activity of iNOS and COX 2. These results may demonstrate the anti inflammatory mechanism of picrasmalignan A. [ABSTRACT FROM AUTHOR]

The concept of "network target" has ushered in a new era in the field of traditional Chinese medicine (TCM). As a new research approach, network pharmacology is based on the analysis of network models and systems biology. Taking advantage of advancements in systems biology, a high degree of integration data analysis strategy and interpretable visualization provides deeper insights into the underlying mechanisms of TCM theories, including the principles of herb combination, biological foundations of herb or herbal formulae action, and molecular basis of TCM syndromes. In this study, we review several recent developments in TCM network pharmacology research and discuss their potential for bridging the gap between traditional and modern medicine. We briefly summarize the two main functional applications of TCM network models: understanding/uncovering and predicting/discovering. In particular, we focus on how TCM network pharmacology research is conducted and highlight different computational tools, such as network-based and machine learning algorithms, and sources that have been proposed and applied to the different steps involved in the research process. To make network pharmacology research commonplace, some basic network definitions and analysis methods are presented. [ABSTRACT FROM AUTHOR]

Background: Alzheimer’s disease (AD) is the most common type of dementia in the elderly. It is estimated that the global prevalence of dementia will rise from 24.3 million in 2005 to 81.1 million in 2040. AD has a devastating impact on sufferers, caregivers, their communities and the healthcare system in general. “Di-tan decoction” (DTD) is a traditional Chinese medicine (TCM) formula frequently used to treat symptoms that are now defined as AD in clinical treatment. However, the existing evidence for recommending DTD in clinical practice derives from studies that were methodologically flawed. In this study, we aim to determine the efficacy and safety of DTD in AD patients based on a rigidly randomized controlled trial. It will provide critical information on sample size and treatment regimen for conducting a full-scale clinical trial of DTD later. Methods/Design: This study will be a double-blind, randomized, placebo-controlled, add-on trial. After a 2-week run-in period, eligible patients with mild to moderate AD will be recruited and given either DTD or placebo twice daily for 24 weeks with follow-up 6 weeks after the last treatment. An increase of four points or greater on the scores of Alzheimer’s Disease Assessment Scale-cognitive subscale (ADAD-cog) will be considered as a positive primary outcome. Total scores of the ADAD-cog, the Chinese version of Mini-Mental State Examination (C-MMSE), and the Chinese version of the Disability Assessment for Dementia (C-DAD) score will be used as secondary outcomes. Adverse events will also be reported. Discussion: This randomized trial will be the first rigorous empirical study on the efficacy of DTD for treating cognitive symptoms in AD patients. Its success will justify and warrant a large-scale clinical trial to further consolidate the evidence for DTD’s efficacy in treating AD. [ABSTRACT FROM AUTHOR]

Traditional Chinese medicine (TCM) is an important treatment for male infertility, and its application to therapy is dependent on differentiation of TCM syndromes. This study aims to investigate the changes in metabolites and metabolic pathways in infertile males with Kidney-Yang Deficiency syndrome (KYDS) via metabolomics approaches. Seminal plasma samples were collected from 18 infertile males with KYDS and 18 fertile males. Liquid chromatography and mass spectrometry were used to characterize metabolomics profiles. Principal component analysis (PCA), partial least squares-discriminate analysis (PLS-DA), and pathway analysis were used for pattern recognition and metabolite identification. PCA and PLS-DA results differentiated the two groups of patients. Forty-one discriminating metabolites (18 in positive mode and 23 in negative mode) were identified. Seven metabolites were related to five potential metabolic pathways associated with biosynthesis and metabolism of aromatic amino acids, tricarboxylic acid cycle, and sphingolipid metabolism. The changes in metabolic pathways may play an important role in the origin of KYDS-associated male infertility. Metabolomics analysis of seminal plasma may be used to differentiate TCM syndromes of infertile males, but further research must be conducted. [ABSTRACT FROM AUTHOR]

Background: In order to better understand the structural features of natural compounds from traditional Chinese medicines, the scaffold architectures of drug-like compounds in MACCS-II Drug Data Report (MDDR), non-drug-like compounds in Available Chemical Directory (ACD), and natural compounds in Traditional Chinese Medicine Compound Database (TCMCD) were explored and compared. Results: First, the different scaffolds were extracted from ACD, MDDR and TCMCD by using three scaffold representations, including Murcko frameworks, Scaffold Tree, and ring systems with different complexity and side chains. Then, by examining the accumulative frequency of the scaffolds in each dataset, we observed that the Level 1 scaffolds of the Scaffold Tree offer advantages over the other scaffold architectures to represent the scaffold diversity of the compound libraries. By comparing the similarity of the scaffold architectures presented in MDDR, ACD and TCMCD, structural overlaps were observed not only between MDDR and TCMCD but also between MDDR and ACD. Finally, Tree Maps were used to cluster the Level 1 scaffolds of the Scaffold Tree and visualize the scaffold space of the three datasets. Conclusion: The analysis of the scaffold architectures of MDDR, ACD and TCMCD shows that, on average, drug-like molecules in MDDR have the highest diversity while natural compounds in TCMCD have the highest complexity. According to the Tree Maps, it can be observed that the Level 1 scaffolds present in MDDR have higher diversity than those presented in TCMCD and ACD. However, some representative scaffolds in MDDR with high frequency show structural similarities to those in TCMCD and ACD, suggesting that some scaffolds in TCMCD and ACD may be potentially drug-like fragments for fragment-based and de novo drug design. [ABSTRACT FROM AUTHOR]