419 research outputs found

    Optimal control of impulsive switched systems with minimum subsystem durations

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    This paper presents a new computational approach for solving optimal control problems governed by impulsive switched systems. Such systems consist of multiple subsystems operating in succession, with possible instantaneous state jumps occurring when the system switches from one subsystem to another. The control variables are the subsystem durations and a set of system parameters influencing the state jumps. In contrast with most other papers on the control of impulsive switched systems, we do not require every potential subsystem to be active during the time horizon (it may be optimal to delete certain subsystems, especially when the optimal number of switches is unknown). However, any active subsystem must be active for a minimum non-negligible duration of time. This restriction leads to a disjoint feasible region for the subsystem durations. The problem of choosing the subsystem durations and the system parameters to minimize a given cost function is a non-standard optimal control problem that cannot be solved using conventional techniques. By combining a time-scaling transformation and an exact penalty method, we develop a computational algorithm for solving this problem. We then demonstrate the effectiveness of this algorithm by considering a numerical example on the optimization of shrimp harvesting operations

    Barriers to implementation of a computerized decision support system for depression: an observational report on lessons learned in "real world" clinical settings

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    <p>Abstract</p> <p>Background</p> <p>Despite wide promotion, clinical practice guidelines have had limited effect in changing physician behavior. Effective implementation strategies to date have included: multifaceted interventions involving audit and feedback, local consensus processes, marketing; reminder systems, either manual or computerized; and interactive educational meetings. In addition, there is now growing evidence that contextual factors affecting implementation must be addressed such as organizational support (leadership procedures and resources) for the change and strategies to implement and maintain new systems.</p> <p>Methods</p> <p>To examine the feasibility and effectiveness of implementation of a computerized decision support system for depression (CDSS-D) in routine public mental health care in Texas, fifteen study clinicians (thirteen physicians and two advanced nurse practitioners) participated across five sites, accruing over 300 outpatient visits on 168 patients.</p> <p>Results</p> <p>Issues regarding computer literacy and hardware/software requirements were identified as initial barriers. Clinicians also reported concerns about negative impact on workflow and the potential need for duplication during the transition from paper to electronic systems of medical record keeping.</p> <p>Conclusion</p> <p>The following narrative report based on observations obtained during the initial testing and use of a CDSS-D in clinical settings further emphasizes the importance of taking into account organizational factors when planning implementation of evidence-based guidelines or decision support within a system.</p

    Design of Group IIA Secreted/Synovial Phospholipase A2 Inhibitors: An Oxadiazolone Derivative Suppresses Chondrocyte Prostaglandin E2 Secretion

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    Group IIA secreted/synovial phospholipase A2 (GIIAPLA2) is an enzyme involved in the synthesis of eicosanoids such as prostaglandin E2 (PGE2), the main eicosanoid contributing to pain and inflammation in rheumatic diseases. We designed, by molecular modeling, 7 novel analogs of 3-{4-[5(indol-1-yl)pentoxy]benzyl}-4H-1,2,4-oxadiazol-5-one, denoted C1, an inhibitor of the GIIAPLA2 enzyme. We report the results of molecular dynamics studies of the complexes between these derivatives and GIIAPLA2, along with their chemical synthesis and results from PLA2 inhibition tests. Modeling predicted some derivatives to display greater GIIAPLA2 affinities than did C1, and such predictions were confirmed by in vitro PLA2 enzymatic tests. Compound C8, endowed with the most favorable energy balance, was shown experimentally to be the strongest GIIAPLA2 inhibitor. Moreover, it displayed an anti-inflammatory activity on rabbit articular chondrocytes, as shown by its capacity to inhibit IL-1β-stimulated PGE2 secretion in these cells. Interestingly, it did not modify the COX-1 to COX-2 ratio. C8 is therefore a potential candidate for anti-inflammatory therapy in joints

    Enzyme classification with peptide programs: a comparative study

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    <p>Abstract</p> <p>Background</p> <p>Efficient and accurate prediction of protein function from sequence is one of the standing problems in Biology. The generalised use of sequence alignments for inferring function promotes the propagation of errors, and there are limits to its applicability. Several machine learning methods have been applied to predict protein function, but they lose much of the information encoded by protein sequences because they need to transform them to obtain data of fixed length.</p> <p>Results</p> <p>We have developed a machine learning methodology, called peptide programs (PPs), to deal directly with protein sequences and compared its performance with that of Support Vector Machines (SVMs) and BLAST in detailed enzyme classification tasks. Overall, the PPs and SVMs had a similar performance in terms of Matthews Correlation Coefficient, but the PPs had generally a higher precision. BLAST performed globally better than both methodologies, but the PPs had better results than BLAST and SVMs for the smaller datasets.</p> <p>Conclusion</p> <p>The higher precision of the PPs in comparison to the SVMs suggests that dealing with sequences is advantageous for detailed protein classification, as precision is essential to avoid annotation errors. The fact that the PPs performed better than BLAST for the smaller datasets demonstrates the potential of the methodology, but the drop in performance observed for the larger datasets indicates that further development is required.</p> <p>Possible strategies to address this issue include partitioning the datasets into smaller subsets and training individual PPs for each subset, or training several PPs for each dataset and combining them using a bagging strategy.</p

    Lateral Gene Transfer (LGT) between Archaea and Escherichia coli is a contributor to the emergence of novel infectious disease

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    BACKGROUND: Lateral gene transfer is the major mechanism for acquisition of new virulence genes in pathogens. Recent whole genome analyses have suggested massive gene transfer between widely divergent organisms. PRESENTATION OF THE HYPOTHESIS: Archeal-like genes acting as virulence genes are present in several pathogens and genomes contain a number of archaeal-like genes of unknown function. Archaea, by virtue of their very different evolutionary history and different environment, provide a pool of potential virulence genes to bacterial pathogens. TESTING THE HYPOTHESIS: We can test this hypothesis by 1)identifying genes likely to have been transferred (directly or indirectly) to E. coli O157:H7 from archaea; 2)investigating the distribution of similar genes in pathogens and non-pathogens and 3)performing rigorous phylogenetic analyses on putative transfers. IMPLICATIONS OF THE HYPOTHESIS: Although this hypothesis focuses on archaea and E. coli, it will serve as a model having broad applicability to a number of pathogenic systems. Since no archaea are known vertebrate pathogens, archaeal-like transferred genes that are associated with virulence in bacteria represent a clear model for the emergence of virulence genes

    SCF Ensures Meiotic Chromosome Segregation Through a Resolution of Meiotic Recombination Intermediates

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    The SCF (Skp1-Cul1-F-box) complex contributes to a variety of cellular events including meiotic cell cycle control, but its function during meiosis is not understood well. Here we describe a novel function of SCF/Skp1 in meiotic recombination and subsequent chromosome segregation. The skp1 temperature-sensitive mutant exhibited abnormal distribution of spindle microtubules in meiosis II, which turned out to originate from abnormal bending of the spindle in meiosis I. Bent spindles were reported in mitosis of this mutant, but it remained unknown how SCF could affect spindle morphology. We found that the meiotic bent spindle in skp1 cells was due to a hypertension generated by chromosome entanglement. The spindle bending was suppressed by inhibiting double strand break (DSB) formation, indicating that the entanglement was generated by the meiotic recombination machinery. Consistently, Rhp51/Rad51-Rad22/Rad52 foci persisted until meiosis I in skp1 cells, proving accumulation of recombination intermediates. Intriguingly bent spindles were also observed in the mutant of Fbh1, an F-box protein containing the DNA helicase domain, which is involved in meiotic recombination. Genetic evidence suggested its cooperation with SCF/Skp1. Thus, SCF/Skp1 together with Fbh1 is likely to function in the resolution of meiotic recombination intermediates, thereby ensuring proper chromosome segregation

    SLC11A1 (NRAMP1) Polymorphisms and Tuberculosis Susceptibility: Updated Systematic Review and Meta-Analysis

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    Background: Natural resistance associated macrophage protein 1 (NRAMP1), encoded by the SLC11A1 gene, has been described to regulate macrophage activation and be associated with infectious and autoimmune diseases. The relation between SLC11A1 polymorphisms and tuberculosis susceptibility has been studied in different populations. Methods: We systematically reviewed published studies on SLC11A1 polymorphisms and tuberculosis susceptibility until September 15, 2010 and quantitatively summarized associations of the most widely studied polymorphisms using metaanalysis. Results: In total, 36 eligible articles were included in this review. In Meta-analysis, significant associations were observed between tuberculosis risk and widely studied SLC11A1 polymorphisms with summarized odds ratio of 1.35 (95%CI, 1.17– 1.54), 1.25 (95 % CI, 1.04–1.50), 1.23 (95 % CI, 1.04–1.44), 1.31 (95%CI, 1.08–1.59) for 39 UTR, D543N, INT4, and 59 (GT)n, respectively. Heterogeneity between studies was not pronounced, and the associations did not remarkably vary in the stratified analysis with respect to study population and study base. Conclusions: The association between SLC11A1 polymorphisms and tuberculosis susceptibility observed in our analyses supports the hypothesis that NRAMP1 might play an important role in the host defense to the development of tuberculosis

    A Global Characterization and Identification of Multifunctional Enzymes

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    Multi-functional enzymes are enzymes that perform multiple physiological functions. Characterization and identification of multi-functional enzymes are critical for communication and cooperation between different functions and pathways within a complex cellular system or between cells. In present study, we collected literature-reported 6,799 multi-functional enzymes and systematically characterized them in structural, functional, and evolutionary aspects. It was found that four physiochemical properties, that is, charge, polarizability, hydrophobicity, and solvent accessibility, are important for characterization of multi-functional enzymes. Accordingly, a combinational model of support vector machine and random forest model was constructed, based on which 6,956 potential novel multi-functional enzymes were successfully identified from the ENZYME database. Moreover, it was observed that multi-functional enzymes are non-evenly distributed in species, and that Bacteria have relatively more multi-functional enzymes than Archaebacteria and Eukaryota. Comparative analysis indicated that the multi-functional enzymes experienced a fluctuation of gene gain and loss during the evolution from S. cerevisiae to H. sapiens. Further pathway analyses indicated that a majority of multi-functional enzymes were well preserved in catalyzing several essential cellular processes, for example, metabolisms of carbohydrates, nucleotides, and amino acids. What’s more, a database of known multi-functional enzymes and a server for novel multi-functional enzyme prediction were also constructed for free access at http://bioinf.xmu.edu.cn/databases/MFEs/index.htm
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