U-Compare bio-event meta-service: compatible BioNLP event extraction services

AbstractBackgroundBio-molecular event extraction from literature is recognized as an important task of bio text mining and, as such, many relevant systems have been developed and made available during the last decade. While such systems provide useful services individually, there is a need for a meta-service to enable comparison and ensemble of such services, offering optimal solutions for various purposes.ResultsWe have integrated nine event extraction systems in the U-Compare framework, making them inter-compatible and interoperable with other U-Compare components. The U-Compare event meta-service provides various meta-level features for comparison and ensemble of multiple event extraction systems. Experimental results show that the performance improvements achieved by the ensemble are significant. ConclusionsWhile individual event extraction systems themselves provide useful features for bio text mining, the U-Compare meta-service is expected to improve the accessibility to the individual systems, and to enable meta-level uses over multiple event extraction systems such as comparison and ensemble.This research was partially supported by KAKENHI 18002007 [YK, MM, JDK, SP, TO, JT]; JST PRESTO and KAKENHI 21500130 [YK]; the Academy of Finland and computational resources were provided by CSC -- IT Center for Science Ltd [JB, FG]; the Research Foundation Flanders (FWO) [SVL]; UK Biotechnology and Biological Sciences, Research Council (BBSRC project BB/G013160/1 Automated Biological Event Extraction from the Literature for Drug Discovery) and JISC, National Centre for Text Mining [SA]; the Spanish grant BIO2010-17527 [MN, APM]; NIH Grant U54 DA021519 [AO, DRR]Peer Reviewe

Влияние высокожировой и высокоуглеводной диеты на клетки крови крыс

Aim. To study the effects of a high-fat, high-carbohydrate diet on erythrocytes and platelets of rats.Materials and methods. Male Wistar rats (n = 23) were used for the study. The rats were divided into a control group and an experimental group. The rats from the control group were fed with standard rat chow. The rats from the experimental group had received a high-fat and high-carbohydrate diet for 12 weeks. In the rats, body weight and blood pressure (BP) were measured, an oral glucose tolerance test was carried out, and hematological and lipid metabolism parameters were analyzed. The conductance of erythrocyte KCa-channels was measured by the potentiometric method, and platelet aggregation was determined by the turbidimetric method.Results. Feeding the rats with a high-fat, high-carbohydrate diet for 12 weeks resulted in obesity, BP elevation, hyperglycemia, impaired glucose tolerance, and dyslipidemia with pronounced triglyceridemia. In the experimental group, a rise in the number of leukocytes, mainly due to granulocytes, and an increase in the number of platelets and their collagen-induced aggregation were observed. The red blood cell count in the rats of the experimental group did not significantly differ from that of the control group. In the experimental group, multidirectional changes in the membrane potential were observed in response to the stimulation of the KCa-channels in the erythrocyte membrane with the Ca2+ ionophore A23187 or artificial redox systems.Conclusion. The obtained data indicate that a high-fat, high-carbohydrate diet leads to metabolic and hemorheological disorders that are typical of metabolic syndrome.Цель – изучить воздействие высокожировой и высокоуглеводной диеты на эритроциты и тромбоциты крови крыс.Материалы и методы. Исследование выполнено на 23 самцах крыс линии Вистар, которые были разделены на контрольную и опытную группу. Крысы контрольной группы находились на стандартной диете. Крысы опытной группы в течение 12 нед получали высокожировую и высокоуглеводную диету. Животным измеряли массу тела, артериальное давление (АД), выполняли глюкозотолерантный тест, определяли гематологические показатели и параметры липидного обмена. Потенциометрическим методом изучали проводимость КСа-каналов мембраны эритроцитов, турбидиметрическим – агрегационную способность тромбоцитов.Результаты. Содержание животных на высокожировой и высокоуглеводной диете приводило к ожирению, повышению АД, гипергликемии, снижению толерантности к глюкозе, дислипидемии с выраженной триглицеридемией. У животных опытной группы происходило увеличение количества лейкоцитов, главным образом, за счет гранулоцитов, повышение числа тромбоцитов и их коллаген-индуцированной агрегации. Количественные показатели клеток красной крови крыс опытной группы не отличались от контрольной группы. В ответ на стимуляцию КСа-каналов мембраны эритроцитов животных экспериментальной группы с помощью Са2+-ионофора А23187 или редокс-системы наблюдались разнонаправленные изменения мембранного потенциала.Заключение. Полученные результаты свидетельствуют, что высокожировая и высокоуглеводная диета приводит к метаболическим и гемореологическим нарушениям, характерным для метаболического синдрома

Influence of obesity on the tone of bronchial smooth muscles in rats

Background. Overweight and obesity are key factors for the occurrence of many morphofunctional disorders in organs and tissues, including bronchopulmonary system.The aim. To study the influence of metabolic disorders that occur against the background of obesity on the state of the airways tone in rats.Materials and methods. Obesity in male Wistar rats was induced using a high-fat and high-carbohydrate diet. In animals, body weight and fat mass were measured, and the heart-lung complex was extracted. In blood serum, the levels of glucose, insulin, leptin, triglycerides, and cholesterol were assessed. Bronchoalveolar lavage fluid was obtained by an open method, in which the concentration of protein, interleukin (IL) 6 and IL-10 was determined. The contractile activity of the isolated bronchial smooth muscle segments was studied using mechanographic method. The effect of acetylcholine (10–7–10–4 M), indomethacin (10–5 M), and forskolin (10–7–10–5 M) on the changes in the tone of airway smooth muscles was assessed.Results. High-fat and high-carbohydrate diet caused an increase in body weight, visceral obesity, hyperglycemia, insulin resistance, leptinemia, dyslipidemia in rats of the experimental group. In the bronchoalveolar lavage fluid of experimental animals, an increase in the content of protein and IL-6 was found, which positively correlated with the level of leptin and the fat mass. In obese rats, the contractile responses of bronchial smooth muscle segments increased in response to the effect of the cholinergic agent acetylcholine. The bronchoconstrictor effect of acetylcholine was reduced by the cyclooxygenase inhibitor indomethacin. In turn, the adenylate cyclase activator forskolin caused relaxation of the airway segments smooth muscles in rats of both groups, which was more pronounced in the experimental group.Conclusion. The obtained results indicate that the change in the reactivity of the respiratory tract can be the cause of  bronchospastic conditions in obesity and of the inflammatory reaction in the respiratory system induced by obesity

Detecting modification of biomedical events using a deep parsing approach

<p>Abstract</p> <p>Background</p> <p>This work describes a system for identifying event mentions in bio-molecular research abstracts that are either speculative (e.g. <it>analysis of IkappaBalpha phosphorylation</it>, where it is not specified whether phosphorylation did or did not occur) or negated (e.g. <it>inhibition of IkappaBalpha phosphorylation</it>, where phosphorylation did <it>not </it>occur). The data comes from a standard dataset created for the BioNLP 2009 Shared Task. The system uses a machine-learning approach, where the features used for classification are a combination of shallow features derived from the words of the sentences and more complex features based on the semantic outputs produced by a deep parser.</p> <p>Method</p> <p>To detect event modification, we use a Maximum Entropy learner with features extracted from the data relative to the trigger words of the events. The shallow features are bag-of-words features based on a small sliding context window of 3-4 tokens on either side of the trigger word. The deep parser features are derived from parses produced by the English Resource Grammar and the <it>RASP </it>parser. The outputs of these parsers are converted into the Minimal Recursion Semantics formalism, and from this, we extract features motivated by linguistics and the data itself. All of these features are combined to create training or test data for the machine learning algorithm.</p> <p>Results</p> <p>Over the test data, our methods produce approximately a 4% absolute increase in F-score for detection of event modification compared to a baseline based only on the shallow bag-of-words features.</p> <p>Conclusions</p> <p>Our results indicate that grammar-based techniques can enhance the accuracy of methods for detecting event modification.</p

Using Unsupervised Patterns to Extract Gene Regulation Relationships for Network Construction

BACKGROUND: The gene expression is usually described in the literature as a transcription factor X that regulates the target gene Y. Previously, some studies discovered gene regulations by using information from the biomedical literature and most of them require effort of human annotators to build the training dataset. Moreover, the large amount of textual knowledge recorded in the biomedical literature grows very rapidly, and the creation of manual patterns from literatures becomes more difficult. There is an increasing need to automate the process of establishing patterns. METHODOLOGY/PRINCIPAL FINDINGS: In this article, we describe an unsupervised pattern generation method called AutoPat. It is a gene expression mining system that can generate unsupervised patterns automatically from a given set of seed patterns. The high scalability and low maintenance cost of the unsupervised patterns could help our system to extract gene expression from PubMed abstracts more precisely and effectively. CONCLUSIONS/SIGNIFICANCE: Experiments on several regulators show reasonable precision and recall rates which validate AutoPat's practical applicability. The conducted regulation networks could also be built precisely and effectively. The system in this study is available at http://ikmbio.csie.ncku.edu.tw/AutoPat/

Overview of the ID, EPI and REL tasks of BioNLP Shared Task 2011

We present the preparation, resources, results and analysis of three tasks of the BioNLP Shared Task 2011: the main tasks on Infectious Diseases (ID) and Epigenetics and Post-translational Modifications (EPI), and the supporting task on Entity Relations (REL). The two main tasks represent extensions of the event extraction model introduced in the BioNLP Shared Task 2009 (ST'09) to two new areas of biomedical scientific literature, each motivated by the needs of specific biocuration tasks. The ID task concerns the molecular mechanisms of infection, virulence and resistance, focusing in particular on the functions of a class of signaling systems that are ubiquitous in bacteria. The EPI task is dedicated to the extraction of statements regarding chemical modifications of DNA and proteins, with particular emphasis on changes relating to the epigenetic control of gene expression. By contrast to these two application-oriented main tasks, the REL task seeks to support extraction in general by separating challenges relating to part-of relations into a subproblem that can be addressed by independent systems. Seven groups participated in each of the two main tasks and four groups in the supporting task. The participating systems indicated advances in the capability of event extraction methods and demonstrated generalization in many aspects: from abstracts to full texts, from previously considered subdomains to new ones, and from the ST'09 extraction targets to other entities and events. The highest performance achieved in the supporting task REL, 58% F-score, is broadly comparable with levels reported for other relation extraction tasks. For the ID task, the highest-performing system achieved 56% F-score, comparable to the state-of-the-art performance at the established ST'09 task. In the EPI task, the best result was 53% F-score for the full set of extraction targets and 69% F-score for a reduced set of core extraction targets, approaching a level of performance sufficient for user-facing applications. In this study, we extend on previously reported results and perform further analyses of the outputs of the participating systems. We place specific emphasis on aspects of system performance relating to real-world applicability, considering alternate evaluation metrics and performing additional manual analysis of system outputs. We further demonstrate that the strengths of extraction systems can be combined to improve on the performance achieved by any system in isolation. The manually annotated corpora, supporting resources, and evaluation tools for all tasks are available from http://www.bionlp-st.org and the tasks continue as open challenges for all interested parties