637 research outputs found
PPLook: an automated data mining tool for protein-protein interaction
<p>Abstract</p> <p>Background</p> <p>Extracting and visualizing of protein-protein interaction (PPI) from text literatures are a meaningful topic in protein science. It assists the identification of interactions among proteins. There is a lack of tools to extract PPI, visualize and classify the results.</p> <p>Results</p> <p>We developed a PPI search system, termed PPLook, which automatically extracts and visualizes protein-protein interaction (PPI) from text. Given a query protein name, PPLook can search a dataset for other proteins interacting with it by using a keywords dictionary pattern-matching algorithm, and display the topological parameters, such as the number of nodes, edges, and connected components. The visualization component of PPLook enables us to view the interaction relationship among the proteins in a three-dimensional space based on the OpenGL graphics interface technology. PPLook can also provide the functions of selecting protein semantic class, counting the number of semantic class proteins which interact with query protein, counting the literature number of articles appearing the interaction relationship about the query protein. Moreover, PPLook provides heterogeneous search and a user-friendly graphical interface.</p> <p>Conclusions</p> <p>PPLook is an effective tool for biologists and biosystem developers who need to access PPI information from the literature. PPLook is freely available for non-commercial users at <url>http://meta.usc.edu/softs/PPLook</url>.</p
Preparation of Fe-Pt thin-sheet magnets using exfoliation behavior
In this research, Fe-Pt thin sheets thicker than 10 microns with Fe contents ranging from 50 to 60 at.% were prepared. Isotropic Fe-Pt thin sheets could be obtained by taking advantage of the exfoliation behavior after depositing Fe-Pt films on Si substrates using a laser ablation technique. A post-annealing process was used to obtain the L10 phase, and the (BH)max value of Fe-Pt thin sheets showed approximately 70 kJ/m3. Moreover, the test of a cantilever containing the obtained Fe-Pt thin sheet showed good mechanical characteristics
The degree of acute descending control of spinal nociception in an area of primary hyperalgesia is dependent on the peripheral domain of afferent input
Descending controls of spinal nociceptive processing play a critical role in the development of inflammatory hyperalgesia. Acute peripheral nociceptor sensitization drives spinal sensitization and activates spino–supraspinal–spinal loops leading to descending inhibitory and facilitatory controls of spinal neuronal activity that further modify the extent and degree of the pain state. The afferent inputs from hairy and glabrous skin are distinct with respect to both the profile of primary afferent classes and the degree of their peripheral sensitization. It is not known whether these differences in afferent input differentially engage descending control systems to different extents or in different ways. Injection of complete Freund's adjuvant resulted in inflammation and swelling of hairy hind foot skin in rats, a transient thermal hyperalgesia lasting 72 h). In hairy skin, transient hyperalgesia was associated with sensitization of withdrawal reflexes to thermal activation of either A- or C-nociceptors. The transience of the hyperalgesia was attributable to a rapidly engaged descending inhibitory noradrenergic mechanism, which affected withdrawal responses to both A- and C-nociceptor activation and this could be reversed by intrathecal administration of yohimbine (α-2-adrenoceptor antagonist). In glabrous skin, yohimbine had no effect on an equivalent thermal inflammatory hyperalgesia. We conclude that acute inflammation and peripheral nociceptor sensitization in hind foot hairy skin, but not glabrous skin, rapidly activates a descending inhibitory noradrenergic system. This may result from differences in the engagement of descending control systems following sensitization of different primary afferent classes that innervate glabrous and hairy skin
Text Mining the History of Medicine
Historical text archives constitute a rich and diverse source of information, which is becoming increasingly readily accessible, due to large-scale digitisation efforts. However, it can be difficult for researchers to explore and search such large volumes of data in an efficient manner. Text mining (TM) methods can help, through their ability to recognise various types of semantic information automatically, e.g., instances of concepts (places, medical conditions, drugs, etc.), synonyms/variant forms of concepts, and relationships holding between concepts (which drugs are used to treat which medical conditions, etc.). TM analysis allows search systems to incorporate functionality such as automatic suggestions of synonyms of user-entered query terms, exploration of different concepts mentioned within search results or isolation of documents in which concepts are related in specific ways. However, applying TM methods to historical text can be challenging, according to differences and evolutions in vocabulary, terminology, language structure and style, compared to more modern text. In this article, we present our efforts to overcome the various challenges faced in the semantic analysis of published historical medical text dating back to the mid 19th century. Firstly, we used evidence from diverse historical medical documents from different periods to develop new resources that provide accounts of the multiple, evolving ways in which concepts, their variants and relationships amongst them may be expressed. These resources were employed to support the development of a modular processing pipeline of TM tools for the robust detection of semantic information in historical medical documents with varying characteristics. We applied the pipeline to two large-scale medical document archives covering wide temporal ranges as the basis for the development of a publicly accessible semantically-oriented search system. The novel resources are available for research purposes, while the processing pipeline and its modules may be used and configured within the Argo TM platform
Solid 4He and the Supersolid Phase: from Theoretical Speculation to the Discovery of a New State of Matter? A Review of the Past and Present Status of Research
The possibility of a supersolid state of matter, i.e., a crystalline solid
exhibiting superfluid properties, first appeared in theoretical studies about
forty years ago. After a long period of little interest due to the lack of
experimental evidence, it has attracted strong experimental and theoretical
attention in the last few years since Kim and Chan (Penn State, USA) reported
evidence for nonclassical rotational inertia effects, a typical signature of
superfluidity, in samples of solid 4He. Since this "first observation", other
experimental groups have observed such effects in the response to the rotation
of samples of crystalline helium, and it has become clear that the response of
the solid is extremely sensitive to growth conditions, annealing processes, and
3He impurities. A peak in the specific heat in the same range of temperatures
has been reported as well as anomalies in the elastic behaviour of solid 4He
with a strong resemblance to the phenomena revealed by torsional oscillator
experiments. Very recently, the observation of unusual mass transport in hcp
solid 4He has also been reported, suggesting superflow. From the theoretical
point of view, powerful simulation methods have been used to study solid 4He,
but the interpretation of the data is still rather difficult; dealing with the
question of supersolidity means that one has to face not only the problem of
the coexistence of quantum coherence phenomena and crystalline order, exploring
the realm of spontaneous symmetry breaking and quantum field theory, but also
the problem of the role of disorder, i.e., how defects, such as vacancies,
impurities, dislocations, and grain boundaries, participate in the phase
transition mechanism.Comment: Published on J. Phys. Soc. Jpn., Vol.77, No.11, p.11101
Practice advisory on the appropriate use of NSAIDs in primary care
Cyclo-oxygenase (COX)-2 selective and nonselective nonsteroidal anti-inflammatory drugs (NSAIDs) are important in managing acute and chronic pain secondary to inflammation. As a greater understanding of the risks of gastrointestinal (GI), cardiovascular (CV) and renal events with NSAIDs use has emerged, guidelines have evolved to reflect differences in risks among NSAIDs. Updated guidelines have yet to reflect new evidence from recent trials which showed similar CV event rates with celecoxib compared to naproxen and ibuprofen, and significantly better GI tolerability for celecoxib. This practice advisory paper aims to present consensus statements and associated guidance regarding appropriate NSAID use based on a review of current evidence by a multidisciplinary group of expert clinicians. This paper is especially intended to guide primary care practitioners within Asia in the appropriate use of NSAIDs in primary care. Following a literature review, group members used a modified Delphi consensus process to determine agreement with selected recommendations. Agreement with a statement by 75% of total voting members was defined a priori as consensus. For low GI risk patients, any nonselective NSAID plus proton pump inhibitor (PPI) or celecoxib alone is acceptable treatment when CV risk is low; for high CV risk patients, low-dose celecoxib or naproxen plus PPI is appropriate. For high GI risk patients, celecoxib plus PPI is acceptable for low CV risk patients; low-dose celecoxib plus PPI is appropriate for high CV risk patients, with the alternative to avoid NSAIDs and consider opioids instead. Appropriate NSAID prescription assumes that the patient has normal renal function at commencement, with ongoing monitoring recommended. In conclusion, appropriate NSAID use requires consideration of all risks
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
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