A Prototype of a Decision Support System for River Basin Water Quality Management in Central and Eastern Europe

This Working Paper documents the implementation of a prototype of a Decision Support System (DSS) for regional water quality management applied to a case study of the Nitra River in Slovakia. With the goals of flexibility and simplicity in mind, two different approaches and tools have been implemented and tested. First, the object-oriented development tool ORVAN was used for fast prototyping of the mathematical programming model and for scenario analysis. Second, a problem-specific generator was implemented to generate various single criterion and multiple criteria optimization problems useful in examining the water quality problem. The resulting mixed-integer optimization problems were solved by the MOMIP package. Provided in the paper are the following: a complete formulation of the mathematical model, a detailed discussion of the data used, documentation of the developed software, an overview of interesting results, and recommendations for future work. Since only preliminary data were available at the time of performing the reported research, results are given merely as illustration of the methodology and software and should not he considered policy recommendations. For the latter task a verified data set and water quality model will be required

Rotational Symmetry of Classical Orbits, Arbitrary Quantization of Angular Momentum and the Role of Gauge Field in Two-Dimensional Space

We study the quantum-classical correspondence in terms of coherent wave functions of a charged particle in two-dimensional central-scalar-potentials as well as the gauge field of a magnetic flux in the sense that the probability clouds of wave functions are well localized on classical orbits. For both closed and open classical orbits, the non-integer angular-momentum quantization with the level-space of angular momentum being greater or less than $\hbar$ is determined uniquely by the same rotational symmetry of classical orbits and probability clouds of coherent wave functions, which is not necessarily $2\pi$-periodic. The gauge potential of a magnetic flux impenetrable to the particle cannot change the quantization rule but is able to shift the spectrum of canonical angular momentum by a flux-dependent value, which results in a common topological phase for all wave functions in the given model. The quantum mechanical model of anyon proposed by Wilczek (Phys. Rev. Lette. 48, 1144) becomes a special case of the arbitrary-quantization.Comment: 6 pages, 5 figure

Treatment of patients with chronic thrombo embolic pulmonary hypertension: focus on riociguat

Chronic thromboembolic pulmonary hypertension (CTEPH) is a disease of the pulmonary vascular bed that is characterized by elevations in the mean pulmonary artery pressure in the setting of perfusion defects on ventilation-perfusion scan, and subsequently confirmed by pulmonary angiography. CTEPH, or World Health Organization (WHO) group 4 pulmonary hypertension, is a result of unresolved thromboembolic obstruction in the pulmonary arteries. Pulmonary endarterectomy (PEA) is the treatment of choice for CTEPH as it is a potentially curative therapy. However, up to one-third of patients are not candidates for the surgery, either due to distal and inaccessible nature of the lesions or comorbid conditions. Due to remodeling that occurs in nonobstructed pulmonary vessels, a portion of patients who have undergone PEA have residual CTEPH after the procedure, attributable to high shear stress prior to PEA. This phenomenon has led to the understanding of a so-called two-compartment model of CTEPH, opening the door to pharmacologic treatment strategies. In 2013, riociguat, a soluble guanylate cyclase stimulator, was approved in the US and Europe for the treatment of inoperable or persistent/recurrent CTEPH. This article reviews the current management of CTEPH with a focus on riociguat

Evaluation of T1 relaxation time in prostate cancer and benign prostate tissue using a Modified Look-Locker inversion recovery sequence

Purpose of this study was to evaluate the diagnostic performance of T1 relaxation time (T1) for differentiating prostate cancer (PCa) from benign tissue as well as high- from low-grade PCa. Twenty-three patients with suspicion for PCa were included in this prospective study. 3 T MRI including a Modified Look-Locker inversion recovery sequence was acquired. Subsequent targeted and systematic prostate biopsy served as a reference standard. T1 and apparent diffusion coefficient (ADC) value in PCa and reference regions without malignancy as well as high- and low-grade PCa were compared using the Mann-Whitney U test. The performance of T1, ADC value, and a combination of both to differentiate PCa and reference regions was assessed by receiver operating characteristic (ROC) analysis. T1 and ADC value were lower in PCa compared to reference regions in the peripheral and transition zone (p < 0.001). ROC analysis revealed high AUCs for T1 (0.92; 95%-CI, 0.87-0.98) and ADC value (0.97; 95%-CI, 0.94 to 1.0) when differentiating PCa and reference regions. A combination of T1 and ADC value yielded an even higher AUC. The difference was statistically significant comparing it to the AUC for ADC value alone (p = 0.02). No significant differences were found between high- and low-grade PCa for T1 (p = 0.31) and ADC value (p = 0.8). T1 relaxation time differs significantly between PCa and benign prostate tissue with lower T1 in PCa. It could represent an imaging biomarker for PCa

Modeling the Hydration Layer around Proteins: HyPred

AbstractProtein hydration plays an integral role in determining protein function and stability. We develop a simple method with atomic level precision for predicting the solvent density near the surface of a protein. A set of proximal radial distribution functions are defined and calculated for a series of different atom types in proteins using all-atom, explicit solvent molecular dynamic simulations for three globular proteins. A major improvement in predicting the hydration layer is found when the protein is held immobile during the simulations. The distribution functions are used to develop a model for predicting the hydration layer with sub-1-Ångstrom resolution without the need for additional simulations. The model and the distribution functions for a given protein are tested in their ability to reproduce the hydration layer from the simulations for that protein, as well as those for other proteins and for simulations in which the protein atoms are mobile. Predictions for the density of water in the hydration shells are then compared with high occupancy sites observed in crystal structures. The accuracy of both tests demonstrates that the solvation model provides a basis for quantitatively understanding protein solvation and thereby predicting the hydration layer without additional simulations

Quantitative biparametric analysis of hybrid 18F-FET PET/MR-neuroimaging for differentiation between treatment response and recurrent glioma

We investigated the diagnostic potential of simultaneous 18F-FET PET/MR-imaging for differentiation between recurrent glioma and post-treatment related effects (PTRE) using quantitative volumetric (3D-VOI) lesion analysis. In this retrospective study, a total of 42 patients including 32 patients with histologically proven glioma relapse and 10 patients with PTRE (histopathologic follow-up, n = 4, serial imaging follow-up, n = 6) were evaluated regarding recurrence. PET/MR-imaging was semi-automatically analysed based on FET tracer uptake using conservative SUV thresholding (isocontour 80%) with emphasis on the metabolically most active regions. Mean (relative) apparent diffusion coefficient (ADCmean, rADCmean), standardised-uptake-value (SUV) including target-to-background (TBR) ratio were determined. Glioma relapse presented higher ADCmean (MD ± SE, 284 ± 91, p = 0.003) and TBRmax (MD ± SE, 1.10 ± 0.45, p = 0.02) values than treatment-related changes. Both ADCmean (AUC ± SE = 0.82 ± 0.07, p-value < 0.001) and TBRmax (AUC ± SE = 0.81 ± 0.08, p-value < 0.001) achieved reliable diagnostic performance in differentiating glioma recurrence from PTRE. Bivariate analysis based on a combination of ADCmean and TBRmax demonstrated highest diagnostic accuracy (AUC ± SE = 0.90 ± 0.05, p-value < 0.001), improving clinical (false negative and false positive) classification. In conclusion, biparametric analysis using DWI and FET PET, both providing distinct information regarding the underlying pathophysiology, presented best diagnostic accuracy and clinical benefit in differentiating recurrent glioma from treatment-related changes

Nutrition and Metabolic Correlates of Obesity and Inflammation: Clinical Considerations

Since 1980, the global prevalence of obesity has doubled; in the United States, it has almost tripled. Billions of people are overweight and obese; the WHO reports that >65% of the world’s population die of diseases related to overweight rather than underweight. Obesity is a complex disease that can be studied from “metropolis to metabolite”—that is, beginning at the policy and the population level through epidemiology and intervention studies; to bench work including preclinical models, tissue, and cell culture studies; to biochemical assays; and to metabolomics. Metabolomics is the next research frontier because it provides a real-time snapshot of biochemical building blocks and products of cellular processes. This report comments on practical considerations when conducting metabolomics research. The pros and cons and important study design concerns are addressed to aid in increasing metabolomics research in the United States. The link between metabolism and inflammation is an understudied phenomenon that has great potential to transform our understanding of immunometabolism in obesity, diabetes, cancer, and other diseases; metabolomics promises to be an important tool in understanding the complex relations between factors contributing to such diseases