小波变换与生物医学信号处理

作为数字信号处理领域的一个重要分支,生物医学信号处理理论与技术的研究一直受到国内外科技工作者的高度重视。小波变换是近年来发展起来的一种新的信号分析工具。本文结合生物医学信号与小波变换的特点,探讨了小波变换在生物医学信号处理领域的应用前景。     

Effects of potent bombesin antagonist on exocrine pancreatic secretion in rats.

Recent synthesis of specific, potent bombesin receptor antagonists allows examination of the role of bombesin-like peptides in physiological processes in vivo. We characterized effects of [D-Phe6]bombesin(6-13)-methyl-ester (BME) on pancreatic enzyme secretion stimulated by the C-terminal decapeptide of gastrin releasing peptide (GRP-10), food intake, and diversion of bile-pancreatic juice in rats. In isolated pancreatic acini, BME had no agonistic effects on amylase secretion but competitively inhibited responses to GRP-10, yielding a pA2 value of 8.89 +/- 0.19. In conscious rats with gastric, jugular vein, bile-pancreatic, and duodenal cannulas, basal enzyme secretion (bile-pancreatic juice recirculated) was not affected by the antagonist. Maximal amylase response to GRP-10 (0.5 nmol/kg/h) was inhibited dose dependently by BME, reaching 97% inhibition at a dose of 400 nmol/kg/h. The dose response curve of amylase secretion stimulated by GRP-10 was shifted to the right by 40 nmol/kg/h BME, but maximal amylase response was unaltered, suggesting competitive inhibition in vivo. Liquid food intake and bile-pancreatic juice diversion caused substantial increases in amylase secretion; neither response was altered during administration of 400 pmol/kg/h BME. These results demonstrate that BME is a potent, competitive antagonist of pancreatic responses to bombesin-like peptides in vitro and in vivo. Lack of effect of BME on basal pancreatic secretion or responses to liquid food intake or diversion of bile-pancreatic juice in rats suggests that endogenous bombesin-like peptides do not act either directly or indirectly to mediate these responses.     

Basement membrane proteins as a substrate for efficient Trypanosoma brucei differentiation in vitro

The ability to reproduce the developmental events of trypanosomes that occur in their mammalian host in vitro offers significant potential to assist in understanding of the underlying biology of the process. For example, the transition from bloodstream slender to bloodstream stumpy forms is a quorum-sensing response to the parasite-derived peptidase digestion products of environmental proteins. As an abundant physiological substrate in vivo, we studied the ability of a basement membrane matrix enriched gel (BME) in the culture medium to support differentiation of pleomorphic Trypanosoma brucei to stumpy forms. BME comprises extracellular matrix proteins, which are among the most abundant proteins found in connective tissues in mammals and known substrates of parasite-released peptidases. We previously showed that two of these released peptidases are involved in generating a signal that promotes slender-to-stumpy differentiation. Here, we tested the ability of basement membrane extract to enhance parasite differentiation through its provision of suitable substrates to generate the quorum sensing signal, namely oligopeptides. Our results show that when grown in the presence of BME, T. brucei pleomorphic cells arrest at the G0/1 phase of the cell cycle and express the differentiation marker PAD1, the response being restricted to differentiation-competent parasites. Further, the stumpy forms generated in BME medium are able to efficiently proceed onto the next life cycle stage in vitro, procyclic forms, when incubated with cis-aconitate, further validating the in vitro BME differentiation system. Hence, BME provides a suitable in vitro substrate able to accurately recapitulate physiological parasite differentiation without the use of experimental animals.     

National Center for Biomedical Ontology: advancing biomedicine through structured organization of scientific knowledge

The National Center for Biomedical Ontology is a consortium that comprises leading informaticians, biologists, clinicians, and ontologists, funded by the National Institutes of Health (NIH) Roadmap, to develop innovative technology and methods that allow scientists to record, manage, and disseminate biomedical information and knowledge in machine-processable form. The goals of the Center are (1) to help unify the divergent and isolated efforts in ontology development by promoting high quality open-source, standards-based tools to create, manage, and use ontologies, (2) to create new software tools so that scientists can use ontologies to annotate and analyze biomedical data, (3) to provide a national resource for the ongoing evaluation, integration, and evolution of biomedical ontologies and associated tools and theories in the context of driving biomedical projects (DBPs), and (4) to disseminate the tools and resources of the Center and to identify, evaluate, and communicate best practices of ontology development to the biomedical community. Through the research activities within the Center, collaborations with the DBPs, and interactions with the biomedical community, our goal is to help scientists to work more effectively in the e-science paradigm, enhancing experiment design, experiment execution, data analysis, information synthesis, hypothesis generation and testing, and understand human disease.     

BIOSMILE: A semantic role labeling system for biomedical verbs using a maximum-entropy model with automatically generated template features

Background  

Bioinformatics tools for automatic processing of biomedical literature are invaluable for both the design and interpretation of large-scale experiments. Many information extraction (IE) systems that incorporate natural language processing (NLP) techniques have thus been developed for use in the biomedical field. A key IE task in this field is the extraction of biomedical relations, such as protein-protein and gene-disease interactions. However, most biomedical relation extraction systems usually ignore adverbial and prepositional phrases and words identifying location, manner, timing, and condition, which are essential for describing biomedical relations. Semantic role labeling (SRL) is a natural language processing technique that identifies the semantic roles of these words or phrases in sentences and expresses them as predicate-argument structures. We construct a biomedical SRL system called BIOSMILE that uses a maximum entropy (ME) machine-learning model to extract biomedical relations. BIOSMILE is trained on BioProp, our semi-automatic, annotated biomedical proposition bank. Currently, we are focusing on 30 biomedical verbs that are frequently used or considered important for describing molecular events.     

Merging microfluidics with microarray-based bioassays

Microarray technologies provide powerful tools for biomedical researchers and medicine, since arrays can be configured to monitor the presence of molecular signatures in a highly parallel fashion and can be configured to search either for nucleic acids (DNA microarrays) or proteins (antibody-based microarrays) as well as different types of cells. Microfluidics on the other hand, provides the ability to analyze small volumes (micro-, nano- or even pico-liters) of sample and minimize costly reagent consumption as well as automate sample preparation and reduce sample processing time. The marriage of microarray technologies with the emerging field of microfluidics provides a number of advantages such as, reduction in reagent cost, reductions in hybridization assay times, high-throughput sample processing, and integration and automation capabilities of the front-end sample processing steps. However, this potential marriage is also fraught with some challenges as well, such as developing low-cost manufacturing methods of the fluidic chips, providing good interfaces to the macro-world, minimizing non-specific analyte/wall interactions due to the high surface-to-volume ratio associated with microfluidics, the development of materials that accommodate the optical readout phases of the assay and complete integration of peripheral components (optical and electrical) to the microfluidic to produce autonomous systems appropriate for point-of-care testing. In this review, we provide an overview and recent advances on the coupling of DNA, protein and cell microarrays to microfluidics and discuss potential improvements required for the implementation of these technologies into biomedical and clinical applications.     

A web service for biomedical term look-up

Recent years have seen a huge increase in the amount of biomedical information that is available in electronic format. Consequently, for biomedical researchers wishing to relate their experimental results to relevant data lurking somewhere within this expanding universe of on-line information, the ability to access and navigate biomedical information sources in an efficient manner has become increasingly important. Natural language and text processing techniques can facilitate this task by making the information contained in textual resources such as MEDLINE more readily accessible and amenable to computational processing. Names of biological entities such as genes and proteins provide critical links between different biomedical information sources and researchers' experimental data. Therefore, automatic identification and classification of these terms in text is an essential capability of any natural language processing system aimed at managing the wealth of biomedical information that is available electronically. To support term recognition in the biomedical domain, we have developed Termino, a large-scale terminological resource for text processing applications, which has two main components: first, a database into which very large numbers of terms can be loaded from resources such as UMLS, and stored together with various kinds of relevant information; second, a finite state recognizer, for fast and efficient identification and mark-up of terms within text. Since many biomedical applications require this functionality, we have made Termino available to the community as a web service, which allows for its integration into larger applications as a remotely located component, accessed through a standardized interface over the web.     

Challenges for automatically extracting molecular interactions from full-text articles

Background  

The increasing availability of full-text biomedical articles will allow more biomedical knowledge to be extracted automatically with greater reliability. However, most Information Retrieval (IR) and Extraction (IE) tools currently process only abstracts. The lack of corpora has limited the development of tools that are capable of exploiting the knowledge in full-text articles. As a result, there has been little investigation into the advantages of full-text document structure, and the challenges developers will face in processing full-text articles.     

Effect of Arginine-deficient Media on the Herpes-Type Virus Associated with Cultured Burkitt Tumor Cells

After incubation at 37 C for 2 or more days, Basal Medium Eagle (BME) supplemented with 25% fetal calf serum (FCS) was not able to support adequate growth of EB3 and other lines of Burkitt tumor cells. The medium did, however, increase, by a factor of about 10, the number of cells synthesizing herpes-type virus with which the cultures were persistently infected. Not every lot of FCS produced these effects, nor were these effects seen when BME and FCS were incubated separately for 7 days before the medium was completed. At 37 C, appropriate lots of FCS interacted with several of the amino acids present in BME; this interaction resulted in an inhibition of cellular growth, whereas interaction with arginine yielded the virus-enhancing effect. Arginine-free BME, supplemented with 25% FCS and used without prior incubation, prevented cellular replication and promoted viral infection to a similar extent as did preincubated complete medium. Replenishment of arginine reduced, but did not regularly abolish, the virus-enhancing activity of preincubated media. RPMI-1629 medium was less affected by preincubation with FCS because it contained twice the amount of arginine that BME contained. The FCS factors which act upon arginine and other amino acids are not dialyzable and are partially resistant to heating at 56 or 60 C for 30 to 60 min. Calf and horse sera appear to be devoid of these activities. The nature of these interactions, as well as the mechanism by which arginine deficiency enhanced the viral infection, remains to be ascertained.     

Engineering the Virtual Enterprise: An Architecture-Driven Modeling Approach

The managerial and organization practices required by an increasingly dynamic competitive manufacturing, business, and industrial environment include the formation of “virtual enterprises.” A major concern in the management of virtual enterprises is the integration and coordination of business processes contributed by partner enterprises. The traditional methods of process modeling currently used for the design of business processes do not fully support the needs of the virtual enterprise. The design of these virtual enterprises imposes requirements that make it more complex than conventional intraorganizational business process design. This paper first describes an architecture that assists in the design of the virtual enterprise. Then it discusses business process reengineering (BPR) as a methodology for modeling and designing virtual organizations. While BPR presents many useful tools, the approach itself and the modeling tools commonly used for redesign have fundamental shortcomings when dealing with the virtual enterprise. However, several innovative modeling approaches provide promise for this problem. The paper discusses some of these innovative modeling approaches, such as object-oriented modeling of business processes, agent modeling of organizational players, and the use of ontological modeling to capture and manipulate knowledge about the players and processes. The paper concludes with a conceptual modeling methodology that combines these approaches under the enterprise architecture for the design of virtual enterprises.     

Mechanism of growth inhibitory effect of Blumea balsamifera extract in hepatocellular carcinoma

Blumea balsamifera is known to improve physiological disorders such as rheumatism and hypertension, but its anticancer activity has not been well elucidated. In this study, we found that Blumea balsamifera MeOH extract (BME) induced growth-inhibitory activity in rat and human hepatocellular carcinoma cells without cytotoxicity in rat hepatocytes which were used as a normal cell model. BME induced cell cycle arrest at the G1 phase via decreases in the expression of cyclin-E and phosphorylation of retinoblastoma protein. Furthermore, BME reduced the level of a proliferation-inducing ligand, that stimulates tumor cell growth. These findings suggest that BME has possible therapeutic potential in hepatoma cancer patients and that depletion of cellular APRIL is an important mechanism in the growth-inhibitory effect of BME.     

The BioLexicon: a large-scale terminological resource for biomedical text mining

Background

Due to the rapidly expanding body of biomedical literature, biologists require increasingly sophisticated and efficient systems to help them to search for relevant information. Such systems should account for the multiple written variants used to represent biomedical concepts, and allow the user to search for specific pieces of knowledge (or events) involving these concepts, e.g., protein-protein interactions. Such functionality requires access to detailed information about words used in the biomedical literature. Existing databases and ontologies often have a specific focus and are oriented towards human use. Consequently, biological knowledge is dispersed amongst many resources, which often do not attempt to account for the large and frequently changing set of variants that appear in the literature. Additionally, such resources typically do not provide information about how terms relate to each other in texts to describe events.

Results

This article provides an overview of the design, construction and evaluation of a large-scale lexical and conceptual resource for the biomedical domain, the BioLexicon. The resource can be exploited by text mining tools at several levels, e.g., part-of-speech tagging, recognition of biomedical entities, and the extraction of events in which they are involved. As such, the BioLexicon must account for real usage of words in biomedical texts. In particular, the BioLexicon gathers together different types of terms from several existing data resources into a single, unified repository, and augments them with new term variants automatically extracted from biomedical literature. Extraction of events is facilitated through the inclusion of biologically pertinent verbs (around which events are typically organized) together with information about typical patterns of grammatical and semantic behaviour, which are acquired from domain-specific texts. In order to foster interoperability, the BioLexicon is modelled using the Lexical Markup Framework, an ISO standard.

Conclusions

The BioLexicon contains over 2.2 M lexical entries and over 1.8 M terminological variants, as well as over 3.3 M semantic relations, including over 2 M synonymy relations. Its exploitation can benefit both application developers and users. We demonstrate some such benefits by describing integration of the resource into a number of different tools, and evaluating improvements in performance that this can bring.     

Improved reproducibility in preparing precision-cut liver tissue slices

More than 35 years ago double Nobel laureate Linus Carl Pauling published a powerful model of the molecular mechanism of general anesthesia, generally referred to as the hydrate-microcrystal (aqueous-phase) theory. This hypothesis, based on the molecular behavior of water molecules, did not receive serious attention during Pauling’s life time, when scientific tools for examining complex systems such as the brain were still in their infancy. The situation has since drastically changed, and, now, in the twenty first century, many scientific tools are available for examining different types of complex systems. The discovery of aquaporin-4, a subtype of water channel abundantly expressed in glial systems, further highlighted the concept that the dynamics of water molecules in the cerebral cortex play an important role in important physiological brain functions including consciousness and information processing.     

Improving Health in Ucayali,Peru: A Multisector and Multilevel Analysis

We review the key determinants of health in Ucayali, Peru, identified by researchers, and, according to these, propose a set of tools to improve health in this area. Women and indigenous peoples are recognized as two vulnerable groups in the region that face greater health risks, and these are the main focus of the development of tools for health improvement. Also, the growing economic integration in the region facilitates the spread of infectious disease, thus requiring several levels of intervention. The tools discussed to improve health in Ucayali cross several scales and sectors. They include improved natural resource management, education and empowerment of women, integration of traditional and biomedical care, improved health information management, and community mobilization for health. Overall, our conclusions reinforce the limitations of the biomedical approach, which focuses on the treatment of specific pathologies in improving health. Health-system development requires the cooperation of many sectors and many actors across several spatial scales.     

Open source model for generating RR intervals in atrial fibrillation and beyond

Background  

Realistic modeling of cardiac inter-beat (RR) intervals is highly desirable for basic research in cardiac electrophysiology, clinical management of heart diseases, and developing signal processing tools for ECG analysis.     

Interactions Between Shoot Age Structure, Nutrient Availability and Physiological Integration in the Giant Bamboo Phyllostachys pubescens

Abstract: The age structure of adult shoots, the nutrient availability of the habitat, and their interaction, are important factors influencing the productivity of bamboo groves. In a field fertilization experiment over two years we examined the impact of physiological integration on the emergence, growth, and survival of new shoots of Phyllostachys pubescens, a giant woody bamboo. Impacts of physiological integration were compared using uniform and patchy fertilization treatments. The number of new shoots emerging per plot significantly increased with the application of fertilizer (NPK), but the increase was constrained by the age structure of adult shoots. In a year with a high proportion of shoots with new (first-year) leaves many more new shoots emerged than in a year with a low proportion of new leaves. Mean survivorship of the new shoots was constant at 20 % for all treatments in both years of study. Surprisingly, fertilization did not increase DBH or height of the new shoots, suggesting that shoot size was fixed early in ontogeny. The pattern of fertilizer application, either uniform or patchy, did not affect the total number of new shoots produced. In the case of patchy application, more new shoots developed in unfertilized patches in comparison to uniformly unfertilized plots, probably because these parts of the clone received resources via the rhizomes from the adult shoots in adjacent fertilized patches. The production of new shoots in fertilized patches, in turn, was lower than that in uniformly fertilized plots as a result of this physiological integration. The results are discussed in the general context of the impact of integration on clonal plant performance in dense stands.     

Production of reliability proven physiological data for use in automated monitoring and diagnostic systems

In recent years manufacturers of intensive care monitoring systems have introduced complex digital processing architectures that theoretically have enormous processing power. This power should allow the realization of many useful processing methodologies that up to now have only been research tools, e.g. the generation of reliable alarms, the implementation of predictive monitoring strategies and reliable diagnostic and treatment guidance to the clinical staff. However, before any of these methodologies can be successfully initiated, each must have accurate and relaible derived physiological data available to them, e.g. beat-by-beat heart rate and blood pressure. From the very nature of monitoring physiological quantities there will be much misinformation or ‘noise’ superimposed on the raw signal obtained from the patient. The major source of noise (as far as electocardiogram (ECG) monitoring is concerned) is internal to the body and is electromyographic noise. This results from the contraction of skeletal muscles producing action potentials of similar magnitude and frequency to that of the ECG. Fortunately, nursing staff are very good at ‘filtering out’ any misinformation before recording any data (on a ward chart for instance). However, in completely automated systems, if this noise is not detected and eliminated or compensated for at an early stage in the processing chain, misinformation will result with potentially serious consequences. The recognition and elimination of such noise cannot be readily achieved using standard filtering techniques without serious degradation of information. This paper discusses the potential of modern digital system architectures developed for ECG monitoring. It analyses the noise that occurs on this physiological variable and demonstrates a novel method of eliminating such noise.     

A comparison among different techniques for human ERG signals processing and classification

Feature detection in biomedical signals is crucial for deepening our knowledge about the involved physiological processes. To achieve this aim, many analytic approaches can be applied but only few are able to deal with signals whose time dependent features provide useful clinical information. Among the biomedical signals, the electroretinogram (ERG), that records the retinal response to a light flash, can improve our comprehension of the complex photoreceptoral activities.The present study is focused on the analysis of the early response of the photoreceptoral human system, known as a-wave ERG-component. This wave reflects the functional integrity of the photoreceptors, rods and cones, whose activation dynamics are not yet completely understood. Moreover, since in incipient photoreceptoral pathologies eventual anomalies in a-wave are not always detectable with a “naked eye” analysis of the traces, the possibility to discriminate pathologic from healthy traces, by means of appropriate analytical techniques, could help in clinical diagnosis.In the present paper, we discuss and compare the efficiency of various techniques of signal processing, such as Fourier analysis (FA), Principal Component Analysis (PCA), Wavelet Analysis (WA) in recognising pathological traces from the healthy ones. The investigated retinal pathologies are Achromatopsia, a cone disease and Congenital Stationary Night Blindness, affecting the photoreceptoral signal transmission. Our findings prove that both PCA and FA of conventional ERGs, don't add clinical information useful for the diagnosis of ocular pathologies, whereas the use of a more sophisticated analysis, based on the wavelet transform, provides a powerful tool for routine clinical examinations of patients.     

Semantic Web Applications and Tools for the Life Sciences: SWAT4LS 2010

As Semantic Web technologies mature and new releases of key elements, such as SPARQL 1.1 and OWL 2.0, become available, the Life Sciences continue to push the boundaries of these technologies with ever more sophisticated tools and applications. Unsurprisingly, therefore, interest in the SWAT4LS (Semantic Web Applications and Tools for the Life Sciences) activities have remained high, as was evident during the third international SWAT4LS workshop held in Berlin in December 2010. Contributors to this workshop were invited to submit extended versions of their papers, the best of which are now made available in the special supplement of BMC Bioinformatics. The papers reflect the wide range of work in this area, covering the storage and querying of Life Sciences data in RDF triple stores, tools for the development of biomedical ontologies and the semantics-based integration of Life Sciences as well as clinicial data.