In vitro studies of cells grown on the superconductor PrOxFeAs

The recent discovery of arsenic-based high temperature superconductors has reignited interest in the study of superconductor: biological interfaces. However, the new superconductor materials involve the chemistry of arsenic and their toxicity remains unclear [Hand, E., 2008. Nature 452 (24), 922]. In this study the possible adverse effects of this new family of superconductors on cells have been examined. Cell culture studies in conjunction with microscopy and viability assays were employed to examine the influence of arsenic-based superconductor PrO_xFeAs (x = 0.75) material in vitro. Imaging data revealed that cells were well adhered and spread on the surface of the superconductor. Furthermore, cytotoxicity studies showed that cells were unaffected during the time-course of the experiments, providing support for the biocompatibility aspects of PrO_xFeAs-based superconductor material.

Ordovician nautiloid fossils of Xainza region, Tibet

The Taerma bridge-Zhakang in the Xainza area is the second spot of Ordovician in northern Tibet based on the discovery of some reliable fossils. The strata contain a large amount of fossils of many taxa, which developed well enough to attain reliable support for era and distinctive boundary. It is the best spot for the fossil study of the Ordovician in the northern Tibet up to now and provides important clues to the classification and correlation of the Ordovician and to the paleogeography distribution as well as to the tectonic evolution of the northern Tibet. 29 species of Nautiloid fossils, which belong to 3 orders, 8 families and 15 genera, have been identified. Among them,3 genera and 9 species are new. Here only one new genus Eneoceras gen. nov. and six new species are described in detail as example. Other two new genera Taremaocera's and Variabioceras will be described in other papers.Genus Eneoceras gen.nov.Diagnosis:The new genus Eneoceras gen. nov. is characterized by the features as “Conch orthoconic, medium in size. The surface is decorated with annulus which array in a distance as the septa. Conch enlarging slowly. Compressed laterally. Circular in cross section. Siphuncle small, situated central from ventral in position. Spetal neck subcyrtochoanitic. Slightly expanded in connecting rings. Siphuncle appears as a string of beads with thin parietal deposits in it. Medium in spetal density. Thin epithecal and hypothecal deposits developed in cameras

Earliest Wuchiapingian (Lopingian, Late Permian) brachiopods in southern Hunan, South China : implications for the Pre-Lopingian crisis and onset of Lopingian recovery / radiation

The uppermost 5-15 m of the Douling Formation in the southern Hunan area. South China, yields a diverse fauna comprised of ammonoids, bivalves, and brachiopods. The brachiopods reported in this paper consist of 51 species in 34 genera and are dominated by the Lopingian (Late Permian) species associated with a few species persisting from the underlying Maokouan (Late Guadalupian). This fauna is of earliest Wuchiapingian in age as precisely constrained by the associated conodont Clarkina postbitteri postbitteri and the Guadalupian-type ammonoid fauna of the Roadoceras-Doulingoceras Zone in the brachiopod horizon. The discovery of the Lopingian species-dominated brachiopod fauna in the earliest Wuchiapingian in southern Hunan suggests a much less pronounced effect of the pre-Lopingian crisis (end-Guadalupian mass extinction) than the end-Changhsingian mass extinction in terms of brachiopods, a contemporaneous onset of the Lopingian recovery/radiation during the pre-Lopingian crisis period, and taxonomic selectivity of the pre-Lopingian crisis in terms of different fossil groups. New taxa are Echinauris doulingensis n. sp., Pararigbyella quadrilobata n. gen. and n. sp. and P. doulingensis n. gen. and n. sp.

Fast mining of non-derivable episode rules in complex sequences

Researchers have been endeavoring to discover concise sets of episode rules instead of complete sets in sequences. Existing approaches, however, are not able to process complex sequences and can not guarantee the accuracy of resulting sets due to the violation of anti-monotonicity of the frequency metric. In some real applications, episode rules need to be extracted from complex sequences in which multiple items may appear in a time slot. This paper investigates the discovery of concise episode rules in complex sequences. We define a concise representation called non-derivable episode rules and formularize the mining problem. Adopting a novel anti-monotonic frequency metric, we then develop a fast approach to discover non-derivable episode rules in complex sequences. Experimental results demonstrate that the utility of the proposed approach substantially reduces the number of rules and achieves fast processing.

An iterative approach of protein function prediction

Background: Current approaches of predicting protein functions from a protein-protein interaction (PPI) dataset are based on an assumption that the available functions of the proteins (a.k.a. annotated proteins) will determine the functions of the proteins whose functions are unknown yet at the moment (a.k.a. un-annotated proteins). Therefore, the protein function prediction is a mono-directed and one-off procedure, i.e. from annotated proteins to un-annotated proteins. However, the interactions between proteins are mutual rather than static and mono-directed, although functions of some proteins are unknown for some reasons at present. That means when we use the similarity-based approach to predict functions of un-annotated proteins, the un-annotated proteins, once their functions are predicted, will affect the similarities between proteins, which in turn will affect the prediction results. In other words, the function prediction is a dynamic and mutual procedure. This dynamic feature of protein interactions, however, was not considered in the existing prediction algorithms.

Results: In this paper, we propose a new prediction approach that predicts protein functions iteratively. This iterative approach incorporates the dynamic and mutual features of PPI interactions, as well as the local and global semantic influence of protein functions, into the prediction. To guarantee predicting functions iteratively, we propose a new protein similarity from protein functions. We adapt new evaluation metrics to evaluate the prediction quality of our algorithm and other similar algorithms. Experiments on real PPI datasets were conducted to evaluate the effectiveness of the proposed approach in predicting unknown protein functions.

Conclusions: The iterative approach is more likely to reflect the real biological nature between proteins when predicting functions. A proper definition of protein similarity from protein functions is the key to predicting functions iteratively. The evaluation results demonstrated that in most cases, the iterative approach outperformed non-iterative ones with higher prediction quality in terms of prediction precision, recall and F-value.

Mining condensed sets of frequent episodes with more accurate frequencies from complex sequences

Many previous approaches to frequent episode discovery only accept simple sequences. Although a recent approach has been able to nd frequent episodes from complex sequences, the discovered sets are neither condensed nor accurate. This paper investigates the discovery of condensed sets of frequent episodes from complex sequences. We adopt a novel anti-monotonic frequency measure based on non-redundant occurrences, and dene a condensed set, nDaCF (the set of non-derivable approximately closed frequent episodes) within a given maximal error bound of support. We then introduce a series of effective pruning strategies, and develop a method, nDaCF-Miner, for discovering nDaCF sets. Experimental results show that, when the error bound is somewhat high, the discovered nDaCF sets are two orders of magnitude smaller than complete sets, and nDaCF-miner is more efficient than previous mining approaches. In addition, the nDaCF sets are more accurate than the sets found by previous approaches.

Carbon dioxide corrosion inhibition : an overview of recent research on new inhibitor development

Since the introduction of inhibitors to the oil and gas industry in the 1940’s, corrosion inhibition has played a key role in carbon dioxide (CO2) corrosion control. Major inhibitor discoveries occurred from the late 1940's to the late 1960's, followed by the refinement of formulations and the development of improved application methods. Over the past two to three decades, although some new derivatives of existing inhibitors such as amide, amine and imidazoline have been reported, there have been few if any discoveries of new CO2 corrosion inhibitors. In recent years, the development of environmentally friendly inhibitors and the inhibition of localised corrosion have become driving forces behind new advances in corrosion inhibitor technology. Recently a rare earth metal organic compound, lanthanum 4-hydroxy cinnamate has been found to be an efficient corrosion inhibitor for mild steel in CO2 containing aqueous media. A resorcinarene acid has been found to provide effective localised corrosion inhibition by promoting a random distribution of insignificant anodic currents. The advent of advanced scanning probe techniques and an electrochemical integrated multi-electrode array have facilitated the discovery of corrosion inhibitors. This paper provides a brief overview of recent progress in this field.

A truncated fragment of Src protein kinase generated by calpain-mediated cleavage is a mediator of neuronal death in excitotoxicity

Excitotoxicity resulting from overstimulation of glutamate receptors is a major cause of neuronal death in cerebral ischemic stroke. The overstimulated ionotropic glutamate receptors exert their neurotoxic effects in part by overactivation of calpains, which induce neuronal death by catalyzing limited proteolysis of specific cellular proteins. Here, we report that in cultured cortical neurons and in vivo in a rat model of focal ischemic stroke, the tyrosine kinase Src is cleaved by calpains at a site in the N-terminal unique domain. This generates a truncated Src fragment of ?52 kDa, which we localized predominantly to the cytosol. A cell membrane-permeable fusion peptide derived from the unique domain of Src prevents calpain from cleaving Src in neurons and protects against excitotoxic neuronal death. To explore the role of the truncated Src fragment in neuronal death, we expressed a recombinant truncated Src fragment in cultured neurons and examined how it affects neuronal survival. Expression of this fragment, which lacks the myristoylation motif and unique domain, was sufficient to induce neuronal death. Furthermore, inactivation of the prosurvival kinase Akt is a key step in its neurotoxic signaling pathway. Because Src maintains neuronal survival, our results implicate calpain cleavage as a molecular switch converting Src from a promoter of cell survival to a mediator of neuronal death in excitotoxicity. Besides unveiling a new pathological action of Src, our discovery of the neurotoxic action of the truncated Src fragment suggests new therapeutic strategies with the potential to minimize brain damage in ischemic stroke.

Quantitative experimental comparison of single-beam, sidescan, and multibeam benthic habitat maps

Map comparison is a relatively uncommon practice in acoustic seabed classification to date, contrary to the field of land remote sensing, where it has been developed extensively over recent decades. The aim here is to illustrate the benefits of map comparison in the underwater realm with a case study of three maps independently describing the seabed habitats of the Te Matuku Marine Reserve (Hauraki Gulf, New Zealand). The maps are obtained from a QTC View classification of a single-beam echosounder (SBES) dataset, manual segmentation of a sidescan sonar (SSS) mosaic, and automatic classification of a backscatter dataset from a multibeam echosounder (MBES). The maps are compared using pixel-to-pixel similarity measures derived from the literature in land remote sensing. All measures agree in presenting the MBES and SSS maps as the most similar, and the SBES and SSS maps as the least similar. The results are discussed with reference to the potential of MBES backscatter as an alternative to SSS mosaic for imagery segmentation and to the potential of joint SBES–SSS survey for improved habitat mapping. Other applications of map-similarity measures in acoustic classification of the seabed are suggested.

Software similarity and classification

This thesis analyses software programs in the context of their similarity to other software programs. Applications proposed and implemented include detecting malicious software and discovering security vulnerabilities.

Efficient mining of top-k breaker emerging subgraph patterns from graph datasets

This paper introduces a new type of discriminative subgraph pattern called breaker emerging subgraph pattern by introducing three constraints and two new concepts: base and breaker. A breaker emerging sub-graph pattern consists of three subpatterns: a con-strained emerging subgraph pattern, a set of bases and a set of breakers. An efficient approach is pro-posed for the discovery of top-k breaker emerging sub-graph patterns from graph datasets. Experimental re-sults show that the approach is capable of efficiently discovering top-k breaker emerging subgraph patterns from given datasets, is more efficient than two previ-ous methods for mining discriminative subgraph pat-terns. The discovered top-k breaker emerging sub-graph patterns are more informative, more discrim-inative, more accurate and more compact than the minimal distinguishing subgraph patterns. The top-k breaker emerging patterns are more useful for sub-structure analysis, such as molecular fragment analy-sis. © 2009, Australian Computer Society, Inc.

Validation of a multiplex reverse transcription and pre-amplification method using TaqMan(®) MicroRNA assays.

Since the discovery of microRNAs (miRNAs), different approaches have been developed to label, amplify and quantify miRNAs. The TaqMan(®) technology, provided by Applied Biosystems (ABIs), uses a stem-loop reverse transcription primer system to reverse transcribe the RNA and amplify the cDNA. This method is widely used to identify global differences between the expression of 100s of miRNAs across comparative samples. This technique also allows the quantification of the expression of targeted miRNAs to validate observations determined by whole-genome screening or to analyze few specific miRNAs on a large number of samples. Here, we describe the validation of a method published by ABIs on their web site allowing to reverse transcribe and pre-amplify multiple miRNAs and snoRNAs simultaneously. The validation of this protocol was performed on human muscle and plasma samples. Fast and cost efficient, this method achieves an easy and convenient way to screen a relatively large number of miRNAs in parallel.

Mimtags: the use of phage display technology to produce novel protein-specific probes

In recent times the use of protein-specific probes in the field of proteomics has undergone evolutionary changes leading to the discovery of new probing techniques. Protein-specific probes serve two main purposes: epitope mapping and detection assays. One such technique is the use of phage display in the random selection of peptide mimotopes (mimtags) that can tag epitopes of proteins, replacing the use of monoclonal antibodies in detection systems. In this study, phage display technology was used to screen a random peptide library with a biologically active purified human interleukin-4 receptor (IL-4R) and interleukin-13 (IL-13) to identify mimtag candidates that interacted with these proteins. Once identified, the mimtags were commercially synthesised, biotinylated and used for in vitro immunoassays. We have used phage display to identify M13 phage clones that demonstrated specific binding to IL-4R and IL-13 cytokine. A consensus in binding sequences was observed and phage clones characterised had identical peptide sequence motifs. Only one was synthesised for use in further immunoassays, demonstrating significant binding to either IL-4R or IL-13. We have successfully shown the use of phage display to identify and characterise mimtags that specifically bind to their target epitope. Thus, this new method of probing proteins can be used in the future as a novel tool for immunoassay and detection technique, which is cheaper and more rapidly produced and therefore a better alternative to the use of monoclonal antibodies.

Hierarchical dirichlet process for tracking complex topical structure evolution and its application to autism research literature

In this paper we describe a novel framework for the discovery of the topical content of a data corpus, and the tracking of its complex structural changes across the temporal dimension. In contrast to previous work our model does not impose a prior on the rate at which documents are added to the corpus nor does it adopt the Markovian assumption which overly restricts the type of changes that the model can capture. Our key technical contribution is a framework based on (i) discretization of time into epochs, (ii) epoch-wise topic discovery using a hierarchical Dirichlet process-based model, and (iii) a temporal similarity graph which allows for the modelling of complex topic changes: emergence and disappearance, evolution, splitting and merging. The power of the proposed framework is demonstrated on the medical literature corpus concerned with the autism spectrum disorder (ASD) - an increasingly important research subject of significant social and healthcare importance. In addition to the collected ASD literature corpus which we made freely available, our contributions also include two free online tools we built as aids to ASD researchers. These can be used for semantically meaningful navigation and searching, as well as knowledge discovery from this large and rapidly growing corpus of literature.

Stabilizing sparse cox model using statistic and semantic structures in electronic medical records

Stability in clinical prediction models is crucial for transferability between studies, yet has received little attention. The problem is paramount in high dimensional data, which invites sparse models with feature selection capability. We introduce an effective method to stabilize sparse Cox model of time-to-events using statistical and semantic structures inherent in Electronic Medical Records (EMR). Model estimation is stabilized using three feature graphs built from (i) Jaccard similarity among features (ii) aggregation of Jaccard similarity graph and a recently introduced semantic EMR graph (iii) Jaccard similarity among features transferred from a related cohort. Our experiments are conducted on two real world hospital datasets: a heart failure cohort and a diabetes cohort. On two stability measures – the Consistency index and signal-to-noise ratio (SNR) – the use of our proposed methods significantly increased feature stability when compared with the baselines.