Large Scale Application of Neural Network Based Semantic Role Labeling for Automated Relation Extraction from Biomedical Texts

To reduce the increasing amount of time spent on literature search in the life sciences, several methods for automated knowledge extraction have been developed. Co-occurrence based approaches can deal with large text corpora like MEDLINE in an acceptable time but are not able to extract any specific type of semantic relation. Semantic relation extraction methods based on syntax trees, on the other hand, are computationally expensive and the interpretation of the generated trees is difficult. Several natural language processing (NLP) approaches for the biomedical domain exist focusing specifically on the detection of a limited set of relation types. For systems biology, generic approaches for the detection of a multitude of relation types which in addition are able to process large text corpora are needed but the number of systems meeting both requirements is very limited. We introduce the use of SENNA (“Semantic Extraction using a Neural Network Architecture”), a fast and accurate neural network based Semantic Role Labeling (SRL) program, for the large scale extraction of semantic relations from the biomedical literature. A comparison of processing times of SENNA and other SRL systems or syntactical parsers used in the biomedical domain revealed that SENNA is the fastest Proposition Bank (PropBank) conforming SRL program currently available. 89 million biomedical sentences were tagged with SENNA on a 100 node cluster within three days. The accuracy of the presented relation extraction approach was evaluated on two test sets of annotated sentences resulting in precision/recall values of 0.71/0.43. We show that the accuracy as well as processing speed of the proposed semantic relation extraction approach is sufficient for its large scale application on biomedical text. The proposed approach is highly generalizable regarding the supported relation types and appears to be especially suited for general-purpose, broad-scale text mining systems. The presented approach bridges the gap between fast, cooccurrence-based approaches lacking semantic relations and highly specialized and computationally demanding NLP approaches.     

Representation of cancer in the medical literature--a bibliometric analysis

Background

There exists a lack of knowledge regarding the quantity and quality of scientific yield in relation to individual cancer types. We aimed to measure the proportion, quality and relevance of oncology-related articles, and to relate this output to their associated disease burden. By incorporating the impact factor(IF) and Eigenfactor™(EF) into our analysis we also assessed the relationship between these indices and the output under study.

Methods

All publications in 2007 were retrieved for the 26 most common cancers. The top 20 journals ranked by IF and EF in general medicine and oncology, and the presence of each malignancy within these titles was analysed. Journals publishing most prolifically on each cancer were identified and their impact assessed.

Principal Findings

63260 (PubMed) and 126845 (WoS) entries were generated, respectively. 26 neoplasms accounted for 25% of total output from the top medical publications. 5 cancers dominated the first quartile of output in the top oncology journals; breast, prostate, lung, and intestinal cancer, and leukaemia. Journals associated with these cancers were associated with much higher IFs and EFs than those journals associated with the other cancer types under study, although these measures were not equivalent across all sub-specialties. In addition, yield on each cancer was related to its disease burden as measured by its incidence and prevalence.

Conclusions

Oncology enjoys disproportionate representation in the more prestigious medical journals. 5 cancers dominate yield, although this attention is justified given their associated disease burden. The commonly used IF and the recently introduced EF do not correlate in the assessment of the preeminent oncology journals, nor at the level of individual malignancies; there is a need to delineate between proxy measures of quality and the relevance of output when assessing its merit. These results raise significant questions regarding the best method of assessment of research and scientific output in the field of oncology.     

Genetic Analysis of Central Carbon Metabolism Unveils an Amino Acid Substitution That Alters Maize NAD-Dependent Isocitrate Dehydrogenase Activity

Background

Central carbon metabolism (CCM) is a fundamental component of life. The participating genes and enzymes are thought to be structurally and functionally conserved across and within species. Association mapping utilizes a rich history of mutation and recombination to achieve high resolution mapping. Therefore, applying association mapping in maize (Zea mays ssp. mays), the most diverse model crop species, to study the genetics of CCM is a particularly attractive system.

Methodology/Principal Findings

We used a maize diversity panel to test the CCM functional conservation. We found heritable variation in enzyme activity for every enzyme tested. One of these enzymes was the NAD-dependent isocitrate dehydrogenase (IDH, E.C. 1.1.1.41), in which we identified a novel amino-acid substitution in a phylogenetically conserved site. Using candidate gene association mapping, we identified that this non-synonymous polymorphism was associated with IDH activity variation. The proposed mechanism for the IDH activity variation includes additional components regulating protein level. With the comparison of sequences from maize and teosinte (Zea mays ssp. Parviglumis), the maize wild ancestor, we found that some CCM genes had also been targeted for selection during maize domestication.

Conclusions/Significance

Our results demonstrate the efficacy of association mapping for dissecting natural variation in primary metabolic pathways. The considerable genetic diversity observed in maize CCM genes underlies heritable phenotypic variation in enzyme activities and can be useful to identify putative functional sites.     

Uncoupling charge movement from channel opening in voltage-gated potassium channels by ruthenium complexes

The Kv2.1 channel generates a delayed-rectifier current in neurons and is responsible for modulation of neuronal spike frequency and membrane repolarization in pancreatic β-cells and cardiomyocytes. As with other tetrameric voltage-activated K(+)-channels, it has been proposed that each of the four Kv2.1 voltage-sensing domains activates independently upon depolarization, leading to a final concerted transition that causes channel opening. The mechanism by which voltage-sensor activation is coupled to the gating of the pore is still not understood. Here we show that the carbon-monoxide releasing molecule 2 (CORM-2) is an allosteric inhibitor of the Kv2.1 channel and that its inhibitory properties derive from the CORM-2 ability to largely reduce the voltage dependence of the opening transition, uncoupling voltage-sensor activation from the concerted opening transition. We additionally demonstrate that CORM-2 modulates Shaker K(+)-channels in a similar manner. Our data suggest that the mechanism of inhibition by CORM-2 may be common to voltage-activated channels and that this compound should be a useful tool for understanding the mechanisms of electromechanical coupling.     

Synthesis and biological evaluation of five-membered heterocycles fused to cyclopenta[c]thiophene as new antitumor agents

A series of 10 derivatives 2-6 issued from the fusion of various five-membered heterocycles to cyclopenta[c]thiophene were evaluated for potential anticancer activity in the NCI's in vitro human disease-oriented tumor cell line screening panel that consisted of 60 human tumor cell lines arranged in nine subpanels, representing diverse histologies. Among these tested compounds, four were found to be cytotoxic allowing us to point out some structure-activity relationships. The oxazolidinone derivatives 2a-c displayed further in vivo antitumor activity in the hollow fiber assay and standard xenograft testing developed at the NCI.     

Detrimental contribution of the Toll-like receptor (TLR)3 to influenza A virus-induced acute pneumonia

Influenza A virus (IAV) is the etiological agent of a highly contagious acute respiratory disease that causes epidemics and considerable mortality annually. Recently, we demonstrated, using an in vitro approach, that the pattern recognition Toll-like receptor (TLR)3 plays a key role in the immune response of lung epithelial cells to IAV. In view of these data and the fact that the functional role of TLR3 in vivo is still debated, we designed an investigation to better understand the role of TLR3 in the mechanisms of IAV pathogenesis and host immune response using an experimental murine model. The time-course of several dynamic parameters, including animal survival, respiratory suffering, viral clearance, leukocyte recruitment into the airspaces and secretion of critical inflammatory mediators, was compared in infected wild-type and TLR3(-/-) mice. First, we found that the pulmonary expression of TLR3 is constitutive and markedly upregulated following influenza infection in control mice. Notably, when compared to wild-type mice, infected TLR3-/- animals displayed significantly reduced inflammatory mediators, including RANTES (regulated upon activation, normal T cell expressed and secreted), interleukin-6, and interleukin-12p40/p70 as well as a lower number of CD8+ T lymphocytes in the bronchoalveolar airspace. More important, despite a higher viral production in the lungs, mice deficient in TLR3 had an unexpected survival advantage. Hence, to our knowledge, our findings show for the first time that TLR3-IAV interaction critically contributes to the debilitating effects of a detrimental host inflammatory response.     

BDNF and DYRK1A Are Variable and Inversely Correlated in Lymphoblastoid Cell Lines from Down Syndrome Patients

Down syndrome or trisomy 21 is the most common genetic disorder leading to mental retardation. One feature is impaired short- and long-term spatial memory, which has been linked to altered brain-derived neurotrophic factor (BDNF) levels. Mouse models of Down syndrome have been used to assess neurotrophin levels, and reduced BDNF has been demonstrated in brains of adult transgenic mice overexpressing Dyrk1a, a candidate gene for Down syndrome phenotypes. Given the link between DYRK1A overexpression and BDNF reduction in mice, we sought to assess a similar association in humans with Down syndrome. To determine the effect of DYRK1A overexpression on BDNF in the genomic context of both complete trisomy 21 and partial trisomy 21, we used lymphoblastoid cell lines from patients with complete aneuploidy of human chromosome 21 (three copies of DYRK1A) and from patients with partial aneuploidy having either two or three copies of DYRK1A. Decreased BDNF levels were found in lymphoblastoid cell lines from individuals with complete aneuploidy as well as those with partial aneuploidies conferring three DYRK1A alleles. In contrast, lymphoblastoid cell lines from individuals with partial trisomy 21 having only two DYRK1A copies displayed increased BDNF levels. A negative correlation was also detected between BDNF and DYRK1A levels in lymphoblastoid cell lines with complete aneuploidy of human chromosome 21. This finding indicates an upward regulatory role of DYRK1A expression on BDNF levels in lymphoblastoid cell lines and emphasizes the role of genetic variants associated with psychiatric disorders.     

Rab35 GTPase and cancer: Linking membrane trafficking to tumorigenesis

Rab35 is a small GTPase that is involved in many cellular processes, including membrane trafficking, cell polarity, lipid homeostasis, immunity, phagocytosis and cytokinesis. Recent studies showed that activating mutations confer Rab35 with oncogenic properties. Conversely, downregulation of Rab35 inverts apico‐basal cell polarity and promotes cell migration. Here we review Rab35’s known functions in membrane trafficking and signaling, cell division and cell migration in cancer cells and discuss the importance of Rab35‐dependent membrane trafficking in cancer progression.