Processing SPARQL queries with regular expressions in RDF databases

Background: As the Resource Description Framework (RDF) data model is widely used for modeling and sharing a lot of online bioinformatics resources such as Uniprot (dev.isb-sib.ch/projects/uniprot-rdf) or Bio2RDF (bio2rdf.org), SPARQL - a W3C recommendation query for RDF databases - has become an important query language for querying the bioinformatics knowledge bases. Moreover, due to the diversity of users' requests for extracting information from the RDF data as well as the lack of users' knowledge about the exact value of each fact in the RDF databases, it is desirable to use the SPARQL query with regular expression patterns for querying the RDF data. To the best of our knowledge, there is currently no work that efficiently supports regular expression processing in SPARQL over RDF databases. Most of the existing techniques for processing regular expressions are designed for querying a text corpus, or only for supporting the matching over the paths in an RDF graph. Results: In this paper, we propose a novel framework for supporting regular expression processing in SPARQL query. Our contributions can be summarized as follows. 1) We propose an efficient framework for processing SPARQL queries with regular expression patterns in RDF databases. 2) We propose a cost model in order to adapt the proposed framework in the existing query optimizers. 3) We build a prototype for the proposed framework in C++ and conduct extensive experiments demonstrating the efficiency and effectiveness of our technique. Conclusions: Experiments with a full-blown RDF engine show that our framework outperforms the existing ones by up to two orders of magnitude in processing SPARQL queries with regular expression patterns.X113sciescopu

Personality Factors Predicting Smartphone Addiction Predisposition: Behavioral Inhibition and Activation Systems, Impulsivity, and Self-control

The purpose of this study was to identify personality factor-associated predictors of smartphone addiction predisposition (SAP). Participants were 2,573 men and 2,281 women (n = 4,854) aged 20-49 years (Mean +/- SD: 33.47 +/- 7.52); participants completed the following questionnaires: the Korean Smartphone Addiction Proneness Scale (K-SAPS) for adults, the Behavioral Inhibition System/Behavioral Activation System questionnaire (BIS/BAS), the Dickman Dysfunctional Impulsivity Instrument (DDII), and the Brief Self-Control Scale (BSCS). In addition, participants reported their demographic information and smartphone usage pattern (weekday or weekend average usage hours and main use). We analyzed the data in three steps: (1) identifying predictors with logistic regression, (2) deriving causal relationships between SAP and its predictors using a Bayesian belief network (BN), and (3) computing optimal cut-off points for the identified predictors using the Youden index. Identified predictors of SAP were as follows: gender (female), weekend average usage hours, and scores on BAS-Drive, BAS-Reward Responsiveness, DDII, and BSCS. Female gender and scores on BAS-Drive and BSCS directly increased SAP. BAS-Reward Responsiveness and DDII indirectly increased SAP. We found that SAP was defined with maximal sensitivity as follows: weekend average usage hours > 4.45, BAS-Drive > 10.0, BAS-Reward Responsiveness > 13.8, DDII > 4.5, and BSCS > 37.4. This study raises the possibility that personality factors contribute to SAP. And, we calculated cut-off points for key predictors. These findings may assist clinicians screening for SAP using cut-off points, and further the understanding of SA risk factors.111413Ysciescopu

Sofosbuvir-based therapy for patients with chronic hepatitis C: Early experience of its efficacy and safety in Korea

Background/AimsThe previous standard treatment for chronic hepatitis C (CHC) patients, comprising a combination of pegylated interferon (IFN) and ribavirin, was associated with suboptimal efficacy and severe adverse reactions. A new era of direct-acting antivirals is now dawning in Korea. Early experience of applying sofosbuvir-based therapy to CHC patients in Korea is reported herein.MethodsData on efficacy and safety were collected for CHC patients treated with a combination of sofosbuvir plus ribavirin or sofosbuvir/ledipasvir with or without ribavirin.ResultsThis retrospective study included 25 consecutive patients who received sofosbuvir-based therapy (19 with genotype 1b and 6 with genotype 2) at Seoul National University Hospital from May 2014 to April 2015. A virologic response was achieved at week 4 by 85.7% and 80% of the patients with genotypes 1b and 2, respectively. The HCV-RNA level decreased more slowly in IFN-experienced than in treatment-naïve patients with genotype 1b. However, the sustained virologic response at week 12 (SVR12) rate did not differ among these patients, and was as high as 100%. The presence of cirrhosis significantly increased the risk of a virologic response failure at week 4 (OR, 11.0; P=0.011) among patients with HCV genotype 1b. Only five patients (20%) experienced minor adverse events, including grade 1 fatigue and headache. The hemoglobin level decreased slightly after sofosbuvir-based therapy, but there was no case of premature discontinuation of this therapy.ConclusionsIn a real clinical practice, sofosbuvir-based therapy for CHC patients in Korea achieved optimal antiviral efficacy with insignificant adverse events. Long-term follow-up data are warranted to ensure the sustained antiviral efficacy and long-term safety of sofosbuvir-based IFN-free therapy

Modeling and Re-Engineering of \u3cem\u3eAzotobacter vinelandii\u3c/em\u3e Alginate Lyase to Enhance Its Catalytic Efficiency for Accelerating Biofilm Degradation

Alginate is known to prevent elimination of Pseudomonas aeruginosa biofilms. Alginate lyase (AlgL) might therefore facilitate treatment of Pseudomonas aeruginosa-infected cystic fibrosis patients. However, the catalytic activity of wild-type AlgL is not sufficiently high. Therefore, molecular modeling and site-directed mutagenesis of AlgL might assist in enzyme engineering for therapeutic development. AlgL, isolated from Azotobacter vinelandii, catalyzes depolymerization of alginate via a β-elimination reaction. AlgL was modeled based on the crystal structure template of Sphingomonas AlgL species A1-III. Based on this computational analysis, AlgL was subjected to site-directed mutagenesis to improve its catalytic activity. The kcat/Km of the K194E mutant showed a nearly 5-fold increase against the acetylated alginate substrate, as compared to the wild-type. Double and triple mutants (K194E/K245D, K245D/K319A, K194E/K245D/E312D, and K194E/K245D/K319A) were also prepared. The most potent mutant was observed to be K194E/K245D/K319A, which has a 10-fold improved kcat value (against acetylated alginate) compared to the wild-type enzyme. The antibiofilm effect of both AlgL forms was identified in combination with piperacillin/tazobactam (PT) and the disruption effect was significantly higher in mutant AlgL combined with PT than wild-type AlgL. However, for both the wild-type and K194E/K245D/K319A mutant, the use of the AlgL enzyme alone did not show significant antibiofilm effect

Organic light emitting board for dynamic interactive display

Interactive displays involve the interfacing of a stimuli-responsive sensor with a visual human-readable response. Here, we describe a polymeric electroluminescence-based stimuli-responsive display method that simultaneously detects external stimuli and visualizes the stimulant object. This organic light-emitting board is capable of both sensing and direct visualization of a variety of conductive information. Simultaneous sensing and visualization of the conductive substance is achieved when the conductive object is coupled with the light emissive material layer on application of alternating current. A variety of conductive materials can be detected regardless of their work functions, and thus information written by a conductive pen is clearly visualized, as is a human fingerprint with natural conductivity. Furthermore, we demonstrate that integration of the organic light-emitting board with a fluidic channel readily allows for dynamic monitoring of metallic liquid flow through the channel, which may be suitable for biological detection and imaging applications.

3D garment digitisation for virtual wardrobe using a commodity depth sensor

5-Aminovaleric acid (5AVA) is an important five-carbon platform chemical that can be used for the synthesis of polymers and other chemicals of industrial interest. Enzymatic conversion of L-lysine to 5AVA has been achieved by employing lysine 2-monooxygenase encoded by the davB gene and 5-aminovaleramidase encoded by the davA gene. Additionally, a recombinant Escherichia coli strain expressing the davB and davA genes has been developed for bioconversion of L-lysine to 5AVA. To use glucose and xylose derived from lignocellulosic biomass as substrates, rather than L-lysine as a substrate, we previously examined direct fermentative production of 5AVA from glucose by metabolically engineered E. coli strains. However, the yield and productivity of 5AVA achieved by recombinant E. coli strains remain very low. Thus, Corynebacterium glutamicum, a highly efficient L-lysine producing microorganism, should be useful in the development of direct fermentative production of 5AVA using L-lysine as a precursor for 5AVA. Here, we report the development of metabolically engineered C. glutamicum strains for enhanced fermentative production of 5AVA from glucose.Various expression vectors containing different promoters and origins of replication were examined for optimal expression of Pseudomonas putida davB and davA genes encoding lysine 2-monooxygenase and delta-aminovaleramidase, respectively. Among them, expression of the C. glutamicum codon-optimized davA gene fused with His-Tag at its N-Terminal and the davB gene as an operon under a strong synthetic H promoter (plasmid p36davAB3) in C. glutamicum enabled the most efficient production of 5AVA. Flask culture and fed-batch culture of this strain produced 6.9 and 19.7\ua0g/L (together with 11.9\ua0g/L glutaric acid as major byproduct) of 5AVA, respectively. Homology modeling suggested that endogenous gamma-aminobutyrate aminotransferase encoded by the gabT gene might be responsible for the conversion of 5AVA to glutaric acid in recombinant C. glutamicum. Fed-batch culture of a C. glutamicum gabT mutant-harboring p36davAB3 produced 33.1\ua0g/L 5AVA with much reduced (2.0\ua0g/L) production of glutaric acid.Corynebacterium glutamicum was successfully engineered to produce 5AVA from glucose by optimizing the expression of two key enzymes, lysine 2-monooxygenase and delta-aminovaleramidase. In addition, production of glutaric acid, a major byproduct, was significantly reduced by employing C. glutamicum gabT mutant as a host strain. The metabolically engineered C. glutamicum strains developed in this study should be useful for enhanced fermentative production of the novel C5 platform chemical 5AVA from renewable resources