The uraemic hypertensive patient. a therapeutic challenge-right you are (if you think so)

High blood pressure (BP) is a leading cause of chronic kidney disease (CKD) and at the same time represents its most frequent complication. High BP is an independent risk factor for advanced CKD; on the other hand, at least 40% of patients with normal glomerular filtration rate (GFR) and virtually all patients with GFR <30 mL/min are hypertensive. CKD and microalbuminuria are powerful risk factors for cardiovascular morbidity and mortality. Consequently, in uraemic hypertension, it is of utmost importance to carefully manage both high BP and microalbuminuria, in order to slow down the progression of kidney damage and to reduce the incidence of cardiovascular events. The first purpose of the medical treatment in hypertensive patients is to normalize BP, regardless of the drug used. Nevertheless, some drugs have an 'additional' nephroprotective effect at the same BP target achieved. In this regard, first-line drugs are definitely renin-angiotensin-aldosterone inhibitors, mainly for their proved efficacy in reducing hypertension-related kidney damage and proteinuria. Anyway, a combined approach (two or more drugs) is usually needed to achieve the optimal BP target and reduce the worsening of CKD

Preconditioners based on the Alternating-Direction-Implicit algorithm for the 2D steady-state diffusion equation with orthotropic heterogeneous coefficients

In this paper, we combine the Alternating Direction Implicit (ADI) algorithm with the concept of preconditioning and apply it to linear systems discretized from the 2D steady-state diffusion equations with orthotropic heterogeneous coefficients by the finite element method assuming tensor product basis functions. Specifically, we adopt the compound iteration idea and use ADI iterations as the preconditioner for the outside Krylov subspace method that is used to solve the preconditioned linear system. An efficient algorithm to perform each ADI iteration is crucial to the efficiency of the overall iterative scheme. We exploit the Kronecker product structure in the matrices, inherited from the tensor product basis functions, to achieve high efficiency in each ADI iteration. Meanwhile, in order to reduce the number of Krylov subspace iterations, we incorporate partially the coefficient information into the preconditioner by exploiting the local support property of the finite element basis functions. Numerical results demonstrated the efficiency and quality of the proposed preconditioner. © 2014 Elsevier B.V. All rights reserved

Identification alone versus intraoperative neuromonitoring of the recurrent laryngeal nerve during thyroid surgery: experience of 2034 consecutive patients

Background: The aim of this study was to evaluate the ability of intraoperative neuromonitoring in reducing the postoperative recurrent laryngeal nerve palsy rate by a comparison between patients submitted to thyroidectomy with intraoperative neuromonitoring and with routine identification alone. Methods: Between June 2007 and December 2012, 2034 consecutive patients underwent thyroidectomy by a single surgical team. We compared patients who have had neuromonitoring and patients who have undergone surgery with nerve visualization alone. Patients in which neuromonitoring was not utilized (Group A) were 993, patients in which was utilized (group B) were 1041. Results: In group A 28 recurrent laryngeal nerve injuries were observed (2.82%), 21 (2.11%) transient and 7 (0.7%) permanent. In group B 23 recurrent laryngeal nerve injuries were observed (2.21%), in 17 cases (1.63%) transient and in 6 (0.58%) permanent. Differences were not statistically significative. Conclusions: Visual nerve identification remains the gold standard of recurrent laryngeal nerve management in thyroid surgery. Neuromonitoring helps to identify the nerve, in particular in difficult cases, but it did not decrease nerve injuries compared with visualization alone. Future studies are warranted to evaluate the benefit of intraoperative neuromonitoring in thyroidectomy, especially in conditions in which the recurrent nerve is at high risk of injury. Keywords: Neuromonitoring, Recurrent laryngeal nerve, Thyroidectom

Validation of a bioanalytical method for the determination of synthetic and natural cannabinoids (New psychoactive substances) in oral fluid samples by means of hplc-ms/ms

New psychoactive substances (NPS) represent an important focus nowadays and are continually produced with minimal structural modifications in order to circumvent the law and increase the difficulty of identifying them. Moreover, since there are a high number of different compounds, it is arduous to develop analytical screening and/or confirmation methods that allow the identification and quantification of these compounds. The aim of this work is to develop and validate a bioanalytical method for detecting new synthetic drugs in biological samples, specifically oral fluid, using high-performance liquid chromatography coupled with mass spectrometry (HPLC-MS/MS) with minimal sample pretreatment. Oral fluid samples were simply centrifuged and denaturized with different rapid procedures before injection into the LC-MS/MS system. Calibration curves covered a linear concentration range from LOQ to 100 ng/mL. Validation parameters such as linearity, precision, accuracy, selectivity, matrix effect and thermal stability were evaluated and showed satisfactory results, in accordance with US Food & Drug Administration guidelines. The inter-day analytical bias and imprecision at two levels of quality control (QC) were within ±15% for most compounds. This method was able to identify and calculate the concentration of 10 NPS validated in this biological sample, even in the presence of matrix effect

GENETIC ASPECTS OF BEEF PRODUCTION AMONG HOLSTEIN-FRIESIANS PEDIGREE SELECTED FOR MILK PRODUCTION

To explore the potential of cattle to produce both milk and beef, the genetic aspects of beef production among Holstein-Friesian bulls pedigree selected for milk were studied. The data included growth records of 504 bulls (DPT) by 120 sires (SPT) pedigree selected for progeny testing by American Breeders Service, 1964 to 1971. DPT bulls with proofs had an average predicted difference for milk (PMD) of +180 kilograms. The daughter average was 7,273 kg per lactation under varying herd conditions. Sires accounted for 10% of the variation in average daily gain (ADG), 10% in daily gain per 100 kg body weight (DG/100) and 16% in body weight, indicating substantial genetic variability in beef traits. Sire variance components for beef traits varied with age. There were wide ranges in estimated breeding value (EBV) and estimated transmitting ability (ETA) for beef traits among DPT and SPT bulls, respectively. Ranking EBV among DPT bulls and ETA among SPT bulls for beef traits and selecting the top 10% and 20%, respectively, showed high selection differentials, empirically reflecting the potential for genetic improvement from selection

Refined Isogeometric Analysis for a preconditioned conjugate gradient solver

Starting from a highly continuous Isogeometric Analysis (IGA) discretization, refined Isogeometric Analysis (rIGA) introduces C 0 hyperplanes that act as separators for the direct LU factorization solver. As a result, the total computational cost required to solve the corresponding system of equations using a direct LU factorization solver dramatically reduces (up to a factor of 55) (Garcia et al., 2017). At the same time, rIGA enriches the IGA spaces, thus improving the best approximation error. In this work, we extend the complexity analysis of rIGA to the case of iterative solvers. We build an iterative solver as follows: we first construct the Schur complements using a direct solver over small subdomains (macro-elements). We then assemble those Schur complements into a global skeleton system. Subsequently, we solve this system iteratively using Conjugate Gradients (CG) with an incomplete LU (ILU) preconditioner. For a 2D Poisson model problem with a structured mesh and a uniform polynomial degree of approximation, rIGA achieves moderate savings with respect to IGA in terms of the number of Floating Point Operations (FLOPs) and computational time (in seconds) required to solve the resulting system of linear equations. For instance, for a mesh with four million elements and polynomial degree p=3, the iterative solver is approximately 2.6 times faster (in time) when applied to the rIGA system than to the IGA one. These savings occur because the skeleton rIGA system contains fewer non-zero entries than the IGA one. The opposite situation occurs for 3D problems, and as a result, 3D rIGA discretizations provide no gains with respect to their IGA counterparts when considering iterative solvers

Modeling phase-transitions using a high-performance, isogeometric analysis framework

In this paper, we present a high-performance framework for solving partial differential equations using Isogeometric Analysis, called PetIGA, and show how it can be used to solve phase-field problems. We specifically chose the Cahn-Hilliard equation, and the phase-field crystal equation as test cases. These two models allow us to highlight some of the main advantages that we have access to while using PetIGA for scientific computing. © The Authors. Published by Elsevier B.V

Micropolar fluids using B-spline divergence conforming spaces

We discretized the two-dimensional linear momentum, microrotation, energy and mass conservation equations from micropolar fluids theory, with the finite element method, creating divergence conforming spaces based on B-spline basis functions to obtain pointwise divergence free solutions [8]. Weak boundary conditions were imposed using Nitsche's method for tangential conditions, while normal conditions were imposed strongly. Once the exact mass conservation was provided by the divergence free formulation, we focused on evaluating the differences between micropolar fluids and conventional fluids, to show the advantages of using the micropolar fluid model to capture the features of complex fluids. A square and an arc heat driven cavities were solved as test cases. A variation of the parameters of the model, along with the variation of Rayleigh number were performed for a better understanding of the system. The divergence free formulation was used to guarantee an accurate solution of the flow. This formulation was implemented using the framework PetIGA as a basis, using its parallel stuctures to achieve high scalability. The results of the square heat driven cavity test case are in good agreement with those reported earlier. © The Authors. Published by Elsevier B.V