3 resultados para computation- and data-intensive applications

em Université de Lausanne, Switzerland


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Pharmacogenomics is a field with origins in the study of monogenic variations in drug metabolism in the 1950s. Perhaps because of these historical underpinnings, there has been an intensive investigation of 'hepatic pharmacogenes' such as CYP450s and liver drug metabolism using pharmacogenomics approaches over the past five decades. Surprisingly, kidney pathophysiology, attendant diseases and treatment outcomes have been vastly under-studied and under-theorized despite their central importance in maintenance of health, susceptibility to disease and rational personalized therapeutics. Indeed, chronic kidney disease (CKD) represents an increasing public health burden worldwide, both in developed and developing countries. Patients with CKD suffer from high cardiovascular morbidity and mortality, which is mainly attributable to cardiovascular events before reaching end-stage renal disease. In this paper, we focus our analyses on renal function before end-stage renal disease, as seen through the lens of pharmacogenomics and human genomic variation. We herein synthesize the recent evidence linking selected Very Important Pharmacogenes (VIP) to renal function, blood pressure and salt-sensitivity in humans, and ways in which these insights might inform rational personalized therapeutics. Notably, we highlight and present the rationale for three applications that we consider as important and actionable therapeutic and preventive focus areas in renal pharmacogenomics: 1) ACE inhibitors, as a confirmed application, 2) VDR agonists, as a promising application, and 3) moderate dietary salt intake, as a suggested novel application. Additionally, we emphasize the putative contributions of gene-environment interactions, discuss the implications of these findings to treat and prevent hypertension and CKD. Finally, we conclude with a strategic agenda and vision required to accelerate advances in this under-studied field of renal pharmacogenomics with vast significance for global public health.

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Summary : 1. Measuring health literacy in Switzerland: a review of six surveys: 1.1 Comparison of questionnaires - 1.2 Measures of health literacy in Switzerland - 1.3 Discussion of Swiss data on HL - 1.4 Description of the six surveys: 1.4.1 Current health trends and health literacy in the Swiss population (gfs-UNIVOX), 1.4.2 Nutrition, physical exercise and body weight : opinions and perceptions of the Swiss population (USI), 1.4.3 Health Literacy in Switzerland (ISPMZ), 1.4.4 Swiss Health Survey (SHS), 1.4.5 Survey of Health, Ageing and Retirement in Europe (SHARE), 1.4.6 Adult literacy and life skills survey (ALL). - 2 . Economic costs of low health literacy in Switzerland: a rough calculation. Appendix: Screenshots cost model

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In this paper, we present an efficient numerical scheme for the recently introduced geodesic active fields (GAF) framework for geometric image registration. This framework considers the registration task as a weighted minimal surface problem. Hence, the data-term and the regularization-term are combined through multiplication in a single, parametrization invariant and geometric cost functional. The multiplicative coupling provides an intrinsic, spatially varying and data-dependent tuning of the regularization strength, and the parametrization invariance allows working with images of nonflat geometry, generally defined on any smoothly parametrizable manifold. The resulting energy-minimizing flow, however, has poor numerical properties. Here, we provide an efficient numerical scheme that uses a splitting approach; data and regularity terms are optimized over two distinct deformation fields that are constrained to be equal via an augmented Lagrangian approach. Our approach is more flexible than standard Gaussian regularization, since one can interpolate freely between isotropic Gaussian and anisotropic TV-like smoothing. In this paper, we compare the geodesic active fields method with the popular Demons method and three more recent state-of-the-art algorithms: NL-optical flow, MRF image registration, and landmark-enhanced large displacement optical flow. Thus, we can show the advantages of the proposed FastGAF method. It compares favorably against Demons, both in terms of registration speed and quality. Over the range of example applications, it also consistently produces results not far from more dedicated state-of-the-art methods, illustrating the flexibility of the proposed framework.