77 resultados para Computing Classification Systems
Resumo:
Functional and non-functional concerns require different programming effort, different techniques and different methodologies when attempting to program efficient parallel/distributed applications. In this work we present a "programmer oriented" methodology based on formal tools that permits reasoning about parallel/distributed program development and refinement. The proposed methodology is semi-formal in that it does not require the exploitation of highly formal tools and techniques, while providing a palatable and effective support to programmers developing parallel/distributed applications, in particular when handling non-functional concerns.
Resumo:
An alternative models framework was used to test three confirmatory factor analytic models for the Short Leyton Obsessional Inventory-Children's Version (Short LOI-CV) in a general population sample of 517 young adolescent twins (11-16 years). A one-factor model as implicit in current classification systems of Obsessive-Compulsive Disorder (OCD), a two-factor obsessions and compulsions model, and a multidimensional model corresponding to the three proposed subscales of the Short LOI-CV (labelled Obsessions/Incompleteness, Numbers/Luck and Cleanliness) were considered. The three-factor model was the only model to provide an adequate explanation of the data. Twin analyses suggested significant quantitative sex differences in heritability for both the Obsessions/Incompleteness and Numbers/Luck dimensions with these being significantly heritable in males only (heritability of 60% and 65% respectively). The correlation between the additive genetic effects for these two dimensions in males was 0.95 suggesting they largely share the same genetic risk factors.
Resumo:
Today, the classification systems for myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML) already incorporate cytogenetic and molecular genetic aberrations in an attempt to better reflect disease biology. However, in many MDS/AML patients no genetic aberrations have been identified yet, and even within some cytogenetically well-defined subclasses there is considerable clinical heterogeneity. Recent advances in genomics technologies such as gene expression profiling (GEP) provide powerful tools to further characterize myeloid malignancies at the molecular level, with the goal to refine the MDS/AML classification system, incorporating as yet unknown molecular genetic and epigenetic pathomechanisms, which are likely reflected by aberrant gene expression patterns. In this study, we provide a comprehensive review on how GEP has contributed to a refined molecular taxonomy of MDS and AML with regard to diagnosis, prediction of clinical outcome, discovery of novel subclasses and identification of novel therapeutic targets and novel drugs. As many challenges remain ahead, we discuss the pitfalls of this technology and its potential including future integrative studies with other genomics technologies, which will continue to improve our understanding of malignant transformation in myeloid malignancies and thereby contribute to individualized risk-adapted treatment strategies for MDS and AML patients. Leukemia (2011) 25, 909-920; doi:10.1038/leu.2011.48; published online 29 March 2011
Resumo:
Increasingly infrastructure providers are supplying the cloud marketplace with storage and on-demand compute resources to host cloud applications. From an application user's point of view, it is desirable to identify the most appropriate set of available resources on which to execute an application. Resource choice can be complex and may involve comparing available hardware specifications, operating systems, value-added services, such as network configuration or data replication, and operating costs, such as hosting cost and data throughput. Providers' cost models often change and new commodity cost models, such as spot pricing, have been introduced to offer significant savings. In this paper, a software abstraction layer is used to discover infrastructure resources for a particular application, across multiple providers, by using a two-phase constraints-based approach. In the first phase, a set of possible infrastructure resources are identified for a given application. In the second phase, a heuristic is used to select the most appropriate resources from the initial set. For some applications a cost-based heuristic is most appropriate; for others a performance-based heuristic may be used. A financial services application and a high performance computing application are used to illustrate the execution of the proposed resource discovery mechanism. The experimental result shows the proposed model could dynamically select an appropriate set of resouces that match the application's requirements.
Resumo:
Background: The authors consider whether differences in stage at diagnosis could explain the variation in lung cancer survival between six developed countries in 2004-2007. Methods: Routinely collected population-based data were obtained on all adults (15-99 years) diagnosed with lung cancer in 2004-2007 and registered in regional and national cancer registries in Australia, Canada, Denmark, Norway, Sweden and the UK. Stage data for 57 352 patients were consolidated from various classification systems. Flexible parametric hazard models on the log cumulative scale were used to estimate net survival at 1 year and the excess hazard up to 18 months after diagnosis. Results: Age-standardised 1-year net survival from non-small cell lung cancer ranged from 30% (UK) to 46% (Sweden). Patients in the UK and Denmark had lower survival than elsewhere, partly because of a more adverse stage distribution. However, there were also wide international differences in stage-specific survival. Net survival from TNM stage I non-small cell lung cancer was 16% lower in the UK than in Sweden, and for TNM stage IV disease survival was 10% lower. Similar patterns were found for small cell lung cancer. Conclusions: There are comparability issues when using population-based data but, even given these constraints, this study shows that, while differences in stage at diagnosis explain some of the international variation in overall lung cancer survival, wide disparities in stage-specific survival exist, suggesting that other factors are also important such as differences in treatment. Stage should be included in international cancer survival studies and the comparability of population-based data should be improved.
Resumo:
Abstract - This study investigates the effect of solid dispersions prepared from of polyethylene glycol (PEG) 3350 and 6000 Da alone or combined with the non-ionic surfactant Tween 80 on the solubility and dissolution rate of a poorly soluble drug eprosartan mesylate (ESM) in attempt to improve its bioavailability following its oral administration.
INTRODUCTION
ESM is a potent anti-hypertension [1]. It has low water solubility and is classified as a Class II drug as per the Biopharmaceutical Classification Systems (BCS) leading to low and variable oral bioavailability (approximately 13%). [2]. Thus, improving ESM solubility and/or dissolution rate would eventually improve the drug bioavailability. Solid dispersion is widely used technique to improve the water solubility of poorly water-soluble drugs employing various biocompatible polymers. In this study, we aimed to enhance the solubility and dissolution of EMS employing solid dispersion (SD) formulated from two grades of poly ethylene glycol (PEG) polymers (i.e. PEG 3350 & PEG 6000 Da) either individually or in combination with Tween 80.
MATERIALS AND METHODS
ESM SDs were prepared by solvent evaporation method using either PEG 3350 or PEG 6000 at various (drug: polymer, w/w) ratios 1:1, 1:2, 1:3, 1:4, 1:5 alone or combined with Tween 80 added at fixed percentage of 0.1 of drug by weight?. Physical mixtures (PMs) of drug and carriers were also prepared at same ratios. Drug solid dispersions and physical mixtures were characterized in terms of drug content, drug dissolution using dissolution apparatus USP II and assayed using HPLC method. Drug dissolution enhancement ratio (ER %) from SD in comparison to the plain drug was calculated. Drug-polymer interactions were evaluated using Differential Scanning Calorimetry (DSC) and FT-IR.
RESULTS AND DISCUSSION
The in vitro solubility and dissolution studies showed SDs prepared using both polymers produced a remarkable improvement (p<0.05) in comparison to the plain drug which reached around 32% (Fig. 1). The dissolution enhancement ratio was polymer type and concentration-dependent. Adding Tween 80 to the SD did not show further dissolution enhancement but reduced the required amount of the polymer to get the same dissolution enhancement. The DSC and FT-IR studies indicated that using SD resulted in transformation of drug from crystalline to amorphous form.
CONCLUSIONS
This study indicated that SDs prepared by using both polymers i.e. PEG 3350 and PEG 6000 improved the in-vitro solubility and dissolution of ESM remarkably which may result in improving the drug bioavailability in vivo.
Acknowledgments
This work is a part of MSc thesis of O.M. Ali at the Faculty of Pharmacy, Aleppo University, Syria.
REFERENCES
[1] Ruilope L, Jager B: Eprosartan for the treatment of hypertension. Expert Opin Pharmacother 2003; 4(1):107-14
[2] Tenero D, Martin D, Wilson B, Jushchyshyn J, Boike S, Lundberg, D, et al. Pharmacokinetics of intravenously and orally administered Eprosartan in healthy males: absolute bioavailability and effect of food. Biopharm Drug Dispos 1998; 19(6): 351- 6.