980 resultados para Software-Defined Networking, OpenFlow, rete programmabile
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BACKGROUND: Today, recognition and classification of sequence motifs and protein folds is a mature field, thanks to the availability of numerous comprehensive and easy to use software packages and web-based services. Recognition of structural motifs, by comparison, is less well developed and much less frequently used, possibly due to a lack of easily accessible and easy to use software. RESULTS: In this paper, we describe an extension of DeepView/Swiss-PdbViewer through which structural motifs may be defined and searched for in large protein structure databases, and we show that common structural motifs involved in stabilizing protein folds are present in evolutionarily and structurally unrelated proteins, also in deeply buried locations which are not obviously related to protein function. CONCLUSIONS: The possibility to define custom motifs and search for their occurrence in other proteins permits the identification of recurrent arrangements of residues that could have structural implications. The possibility to do so without having to maintain a complex software/hardware installation on site brings this technology to experts and non-experts alike.
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A precise and simple computational model to generate well-behaved two-dimensional turbulent flows is presented. The whole approach rests on the use of stochastic differential equations and is general enough to reproduce a variety of energy spectra and spatiotemporal correlation functions. Analytical expressions for both the continuous and the discrete versions, together with simulation algorithms, are derived. Results for two relevant spectra, covering distinct ranges of wave numbers, are given.
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Introduction: Therapeutic drug monitoring (TDM) aims at optimizing treatment by individualizing dosage regimen based on measurement of blood concentrations. Maintaining concentrations within a target range requires pharmacokinetic and clinical capabilities. Bayesian calculation represents a gold standard in TDM approach but requires computing assistance. In the last decades computer programs have been developed to assist clinicians in this assignment. The aim of this benchmarking was to assess and compare computer tools designed to support TDM clinical activities.¦Method: Literature and Internet search was performed to identify software. All programs were tested on common personal computer. Each program was scored against a standardized grid covering pharmacokinetic relevance, user-friendliness, computing aspects, interfacing, and storage. A weighting factor was applied to each criterion of the grid to consider its relative importance. To assess the robustness of the software, six representative clinical vignettes were also processed through all of them.¦Results: 12 software tools were identified, tested and ranked. It represents a comprehensive review of the available software's characteristics. Numbers of drugs handled vary widely and 8 programs offer the ability to the user to add its own drug model. 10 computer programs are able to compute Bayesian dosage adaptation based on a blood concentration (a posteriori adjustment) while 9 are also able to suggest a priori dosage regimen (prior to any blood concentration measurement), based on individual patient covariates, such as age, gender, weight. Among those applying Bayesian analysis, one uses the non-parametric approach. The top 2 software emerging from this benchmark are MwPharm and TCIWorks. Other programs evaluated have also a good potential but are less sophisticated (e.g. in terms of storage or report generation) or less user-friendly.¦Conclusion: Whereas 2 integrated programs are at the top of the ranked listed, such complex tools would possibly not fit all institutions, and each software tool must be regarded with respect to individual needs of hospitals or clinicians. Interest in computing tool to support therapeutic monitoring is still growing. Although developers put efforts into it the last years, there is still room for improvement, especially in terms of institutional information system interfacing, user-friendliness, capacity of data storage and report generation.
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Objectives: Therapeutic drug monitoring (TDM) aims at optimizing treatment by individualizing dosage regimen based on blood concentrations measurement. Maintaining concentrations within a target range requires pharmacokinetic (PK) and clinical capabilities. Bayesian calculation represents a gold standard in TDM approach but requires computing assistance. The aim of this benchmarking was to assess and compare computer tools designed to support TDM clinical activities.¦Methods: Literature and Internet were searched to identify software. Each program was scored against a standardized grid covering pharmacokinetic relevance, user-friendliness, computing aspects, interfacing, and storage. A weighting factor was applied to each criterion of the grid to consider its relative importance. To assess the robustness of the software, six representative clinical vignettes were also processed through all of them.¦Results: 12 software tools were identified, tested and ranked. It represents a comprehensive review of the available software characteristics. Numbers of drugs handled vary from 2 to more than 180, and integration of different population types is available for some programs. Nevertheless, 8 programs offer the ability to add new drug models based on population PK data. 10 computer tools incorporate Bayesian computation to predict dosage regimen (individual parameters are calculated based on population PK models). All of them are able to compute Bayesian a posteriori dosage adaptation based on a blood concentration while 9 are also able to suggest a priori dosage regimen, only based on individual patient covariates. Among those applying Bayesian analysis, MM-USC*PACK uses a non-parametric approach. The top 2 programs emerging from this benchmark are MwPharm and TCIWorks. Others programs evaluated have also a good potential but are less sophisticated or less user-friendly.¦Conclusions: Whereas 2 software packages are ranked at the top of the list, such complex tools would possibly not fit all institutions, and each program must be regarded with respect to individual needs of hospitals or clinicians. Programs should be easy and fast for routine activities, including for non-experienced users. Although interest in TDM tools is growing and efforts were put into it in the last years, there is still room for improvement, especially in terms of institutional information system interfacing, user-friendliness, capability of data storage and automated report generation.
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The Office of Special Investigations at Iowa Department of Transportation (DOT) collects FWD data on regular basis to evaluate pavement structural conditions. The primary objective of this study was to develop a fully-automated software system for rapid processing of the FWD data along with a user manual. The software system automatically reads the FWD raw data collected by the JILS-20 type FWD machine that Iowa DOT owns, processes and analyzes the collected data with the rapid prediction algorithms developed during the phase I study. This system smoothly integrates the FWD data analysis algorithms and the computer program being used to collect the pavement deflection data. This system can be used to assess pavement condition, estimate remaining pavement life, and eventually help assess pavement rehabilitation strategies by the Iowa DOT pavement management team. This report describes the developed software in detail and can also be used as a user-manual for conducting simulation studies and detailed analyses. *********************** Large File ***********************
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Los agentes de software en la era de las redes globales son una herramienta vital para superar el fenómeno llamado "sobrecarga de información". El grado de madurez alcanzado en esta tecnología permite que hoy se puedan ver aplicaciones concretas funcionado en organizaciones, como así también en el escritorio del usuario hogareño. El objetivo de este trabajo es presentar una revisión bibliográfica sobre la tecnología de agentes de software, con orientación a los modelos que permiten gerenciar la sobrecarga de información.
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In recent years, protein-ligand docking has become a powerful tool for drug development. Although several approaches suitable for high throughput screening are available, there is a need for methods able to identify binding modes with high accuracy. This accuracy is essential to reliably compute the binding free energy of the ligand. Such methods are needed when the binding mode of lead compounds is not determined experimentally but is needed for structure-based lead optimization. We present here a new docking software, called EADock, that aims at this goal. It uses an hybrid evolutionary algorithm with two fitness functions, in combination with a sophisticated management of the diversity. EADock is interfaced with the CHARMM package for energy calculations and coordinate handling. A validation was carried out on 37 crystallized protein-ligand complexes featuring 11 different proteins. The search space was defined as a sphere of 15 A around the center of mass of the ligand position in the crystal structure, and on the contrary to other benchmarks, our algorithm was fed with optimized ligand positions up to 10 A root mean square deviation (RMSD) from the crystal structure, excluding the latter. This validation illustrates the efficiency of our sampling strategy, as correct binding modes, defined by a RMSD to the crystal structure lower than 2 A, were identified and ranked first for 68% of the complexes. The success rate increases to 78% when considering the five best ranked clusters, and 92% when all clusters present in the last generation are taken into account. Most failures could be explained by the presence of crystal contacts in the experimental structure. Finally, the ability of EADock to accurately predict binding modes on a real application was illustrated by the successful docking of the RGD cyclic pentapeptide on the alphaVbeta3 integrin, starting far away from the binding pocket.
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Apresenta um método para avaliação e seleção de softwares de automação de bibliotecas. Consiste na atribuição de critérios e cálculos estatísticos em uma lista elaborada para a seleção e avaliação deste tipo de software. Este método pretender servir como instrumento de apoio à tomada de decisão no processo de escolha do software mais adequado às necessidades de cada instituição. Este trabalho foi motivado por uma demanda do Instituto Brasileiro de Informação em Ciência e Tecnologia (IBICT) para automatizar a sua biblioteca.
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Over the past decade a series of trials of the EORTC Brain Tumor Group (BTG) has substantially influenced and shaped the standard-of-care of primary brain tumors. All these trials were coupled with biological research that has allowed for better understanding of the biology of these tumors. In glioblastoma, EORTC trial 26981/22981 conducted jointly with the National Cancer Institute of Canada Clinical Trials Group showed superiority of concomitant radiochemotherapy with temozolomide over radiotherapy alone. It also identified the first predictive marker for benefit from alkylating agent chemotherapy in glioblastoma, the methylation of the O6-methyl-guanyl-methly-transferase (MGMT) gene promoter. In another large randomized trial, EORTC 26951, adjuvant chemotherapy in anaplastic oligodendroglial tumors was investigated. Despite an improvement in progression-free survival this did not translate into a survival benefit. The third example of a landmark trial is the EORTC 22845 trial. This trial led by the EORTC Radiation Oncology Group forms the basis for an expectative approach to patients with low-grade glioma, as early radiotherapy indeed prolongs time to tumor progression but with no benefit in overall survival. This trial is the key reference in deciding at what time in their disease adult patients with low-grade glioma should be irradiated. Future initiatives will continue to focus on the conduct of controlled trials, rational academic drug development as well as systematic evaluation of tumor tissue including biomarker development for personalized therapy. Important lessons learned in neurooncology are to dare to ask real questions rather than merely rapidly testing new compounds, and the value of well designed trials, including the presence of controls, central pathology review, strict radiology protocols and biobanking. Structurally, the EORTC BTG has evolved into a multidisciplinary group with strong transatlantic alliances. It has contributed to the maturation of neurooncology within the oncological sciences.
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The growth rate of acoustic tumors, although slow, varies widely. There may be a continuous spectrum or distinct groups of tumor growth rates. Clinical, audiologic, and conventional histologic tests have failed to shed any light on this problem. Modern immunohistochemical methods may stand a better chance. The Ki-67 monoclonal antibody stains proliferating cells and is used in this study to investigate the growth fraction of 13 skull base schwannomas. The acoustic tumors can be divided into two different growth groups, one with a rate five times the other. The literature is reviewed to see if this differentiation is borne out by the radiologic studies. Distinct growth rates have been reported: one very slow, taking 50 years to reach 1 cm in diameter, a second rate with a diameter increase of 0.2 cm/year, and a third rate five times the second, with a 1.0 cm increase in diameter per year. A fourth group growing at 2.5 cm/year is postulated, but these tumors cannot be followed for long radiologically, since symptoms demand surgical intervention. The clinical implications of these separate growth rates are discussed.
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A novel melanoma-associated differentiation Ag whose surface expression can be enhanced or induced by IFN-gamma was identified by mAb Me14/D12. Testing of numerous tumor cell lines and tumor tissue sections showed that Me14/D12-defined Ag was present not only on melanoma but also on other tumor lines of neuroectodermal origin such as gliomas and neuroblastomas and on some lymphoblastic B cell lines, on monocytes and macrophages. Immunoprecipitation by mAb Me14/D12 of lysates from [35S]methionine-labeled melanoma cells analyzed by SDS-PAGE revealed two polypeptide chains of 33 and 38 KDa, both under reducing and nonreducing conditions. Cross-linking experiments indicated that the two chains were present at the cell surface as a dimeric structure. Two-dimensional gel electrophoresis showed that the two chains of 33 and 38 KDa had isoelectric points of 6.2 and 5.7, respectively. Treatment of the melanoma cells with tunicamycin, an inhibitor of N-linked glycosylation, resulted in a reduction of the Mr from 33 to 24 KDa and from 38 to 26 KDa. Peptide maps obtained after Staphylococcus aureus V8 protease digestion showed no shared peptides between the two chains. Although biochemical data indicate that Me14/D12 molecules do not correspond to any known MHC class II Ag, their dimeric structure, tissue distribution, and regulation of IFN-gamma suggest that they could represent a new member of the MHC class II family.
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This paper examines statistical analysis of social reciprocity at group, dyadic, and individual levels. Given that testing statistical hypotheses regarding social reciprocity can be also of interest, a statistical procedure based on Monte Carlo sampling has been developed and implemented in R in order to allow social researchers to describe groups and make statistical decisions.