TCMGeneDIT: a database for associated traditional Chinese medicine, gene and disease information using text mining

<p>Abstract</p> <p>Background</p> <p>Traditional Chinese Medicine (TCM), a complementary and alternative medical system in Western countries, has been used to treat various diseases over thousands of years in East Asian countries. In recent years, many herbal medicines were found to exhibit a variety of effects through regulating a wide range of gene expressions or protein activities. As available TCM data continue to accumulate rapidly, an urgent need for exploring these resources systematically is imperative, so as to effectively utilize the large volume of literature.</p> <p>Methods</p> <p>TCM, gene, disease, biological pathway and protein-protein interaction information were collected from public databases. For association discovery, the TCM names, gene names, disease names, TCM ingredients and effects were used to annotate the literature corpus obtained from PubMed. The concept to mine entity associations was based on hypothesis testing and collocation analysis. The annotated corpus was processed with natural language processing tools and rule-based approaches were applied to the sentences for extracting the relations between TCM effecters and effects.</p> <p>Results</p> <p>We developed a database, TCMGeneDIT, to provide association information about TCMs, genes, diseases, TCM effects and TCM ingredients mined from vast amount of biomedical literature. Integrated protein-protein interaction and biological pathways information are also available for exploring the regulations of genes associated with TCM curative effects. In addition, the transitive relationships among genes, TCMs and diseases could be inferred through the shared intermediates. Furthermore, TCMGeneDIT is useful in understanding the possible therapeutic mechanisms of TCMs via gene regulations and deducing synergistic or antagonistic contributions of the prescription components to the overall therapeutic effects. The database is now available at <url>http://tcm.lifescience.ntu.edu.tw/</url>.</p> <p>Conclusion</p> <p>TCMGeneDIT is a unique database that offers diverse association information on TCMs. This database integrates TCMs with biomedical studies that would facilitate clinical research and elucidate the possible therapeutic mechanisms of TCMs and gene regulations.</p

Extracting causal relations on HIV drug resistance from literature

<p>Abstract</p> <p>Background</p> <p>In HIV treatment it is critical to have up-to-date resistance data of applicable drugs since HIV has a very high rate of mutation. These data are made available through scientific publications and must be extracted manually by experts in order to be used by virologists and medical doctors. Therefore there is an urgent need for a tool that partially automates this process and is able to retrieve relations between drugs and virus mutations from literature.</p> <p>Results</p> <p>In this work we present a novel method to extract and combine relationships between HIV drugs and mutations in viral genomes. Our extraction method is based on natural language processing (NLP) which produces grammatical relations and applies a set of rules to these relations. We applied our method to a relevant set of PubMed abstracts and obtained 2,434 extracted relations with an estimated performance of 84% for F-score. We then combined the extracted relations using logistic regression to generate resistance values for each <drug, mutation> pair. The results of this relation combination show more than 85% agreement with the Stanford HIVDB for the ten most frequently occurring mutations. The system is used in 5 hospitals from the Virolab project <url>http://www.virolab.org</url> to preselect the most relevant novel resistance data from literature and present those to virologists and medical doctors for further evaluation.</p> <p>Conclusions</p> <p>The proposed relation extraction and combination method has a good performance on extracting HIV drug resistance data. It can be used in large-scale relation extraction experiments. The developed methods can also be applied to extract other type of relations such as gene-protein, gene-disease, and disease-mutation.</p

The GABA transporter 1 (SLC6A1): a novel candidate gene for anxiety disorders

Recent evidence suggests that the GABA transporter 1 (GAT-1; SLC6A1) plays a role in the pathophysiology and treatment of anxiety disorders. In order to understand the impact of genetic variation within SLC6A1 on pathological anxiety, we performed a case–control association study with anxiety disorder patients with and without syndromal panic attacks. Using the method of sequential addition of cases, we found that polymorphisms in the 5′ flanking region of SLC6A1 are highly associated with anxiety disorders when considering the severity of syndromal panic attacks as phenotype covariate. Analysing the effect size of the association, we observed a constant increase in the odds ratio for disease susceptibility with an increase in panic severity (OR ~ 2.5 in severely affected patients). Nominally significant association effects were observed considering the entire patient sample. These data indicate a high load of genetic variance within SLC6A1 on pathological anxiety and highlight GAT-1 as a promising target for treatment of anxiety disorders with panic symptoms

The P2X1 receptor and platelet function

Extracellular nucleotides are ubiquitous signalling molecules, acting via the P2 class of surface receptors. Platelets express three P2 receptor subtypes, ADP-dependent P2Y1 and P2Y12 G-protein-coupled receptors and the ATP-gated P2X1 non-selective cation channel. Platelet P2X1 receptors can generate significant increases in intracellular Ca2+, leading to shape change, movement of secretory granules and low levels of αIIbβ3 integrin activation. P2X1 can also synergise with several other receptors to amplify signalling and functional events in the platelet. In particular, activation of P2X1 receptors by ATP released from dense granules amplifies the aggregation responses to low levels of the major agonists, collagen and thrombin. In vivo studies using transgenic murine models show that P2X1 receptors amplify localised thrombosis following damage of small arteries and arterioles and also contribute to thromboembolism induced by intravenous co-injection of collagen and adrenaline. In vitro, under flow conditions, P2X1 receptors contribute more to aggregate formation on collagen-coated surfaces as the shear rate is increased, which may explain their greater contribution to localised thrombosis in arterioles compared to venules within in vivo models. Since shear increases substantially near sites of stenosis, anti-P2X1 therapy represents a potential means of reducing thrombotic events at atherosclerotic plaques

Antagonism between DNA and H3K27 Methylation at the Imprinted Rasgrf1 Locus

At the imprinted Rasgrf1 locus in mouse, a cis-acting sequence controls DNA methylation at a differentially methylated domain (DMD). While characterizing epigenetic marks over the DMD, we observed that DNA and H3K27 trimethylation are mutually exclusive, with DNA and H3K27 methylation limited to the paternal and maternal sequences, respectively. The mutual exclusion arises because one mark prevents placement of the other. We demonstrated this in five ways: using 5-azacytidine treatments and mutations at the endogenous locus that disrupt DNA methylation; using a transgenic model in which the maternal DMD inappropriately acquired DNA methylation; and by analyzing materials from cells and embryos lacking SUZ12 and YY1. SUZ12 is part of the PRC2 complex, which is needed for placing H3K27me3, and YY1 recruits PRC2 to sites of action. Results from each experimental system consistently demonstrated antagonism between H3K27me3 and DNA methylation. When DNA methylation was lost, H3K27me3 encroached into sites where it had not been before; inappropriate acquisition of DNA methylation excluded normal placement of H3K27me3, and loss of factors needed for H3K27 methylation enabled DNA methylation to appear where it had been excluded. These data reveal the previously unknown antagonism between H3K27 and DNA methylation and identify a means by which epigenetic states may change during disease and development

Female Institutional Directors on Boards and Firm Value

The aim of this research is to examine what impact female institutional directors on boards have on corporate performance. Previous research shows that institutional female directors cannot be considered as a homogeneous group since they represent investors who may or may not maintain business relations with the companies on whose corporate boards they sit. Thus, it is not only the effect of female institutional directors as a whole on firm value that has been analysed, but also the impact of pressure-resistant female directors, who represent institutional investors (investment, pension and mutual funds) that only invest in the company, and do not maintain a business relation with the firm. We hypothesize that there is a non-linear association, specifically quadratic, between institutional and pressure-resistant female directors on boards and corporate performance. Our results report that female institutional directors on boards enhance corporate performance, but when they reach a certain threshold on boards (11.72 %), firm value decreases. In line with female institutional directors, pressure-resistant female directors on boards also increase firm value, but only up to a certain figure (12.71 % on boards), above which they have a negative impact on firm performance. These findings are consistent with an inverted U-shaped relationship between female institutional directors and pressure-resistant female directors and firm performance