Calcium‐phosphate and parathyroid intradialytic profiles: A potential aid for tailoring the dialysate calcium content of patients on different hemodialysis schedules

Severe hyperparathyroidism is a challenge on hemodialysis. The definition of dialysate calcium (Ca) is a pending issue with renewed importance in cases of individualized dialysis schedules and of portable home dialysis machines with low‐flow dialysate. Direct measurement of calcium mass transfer is complex and is imprecisely reflected by differences in start‐to‐end of dialysis Ca levels. The study was performed in a dialysis unit dedicated to home hemodialysis and to critical patients with wide use of daily and tailored schedules. The Ca‐phosphate (P)‐parathyroid hormone (PTH) profile includes creatinine, urea, total and ionized Ca, albumin, sodium, potassium, P, PTH levels at start, mid, and end of dialysis. “Severe” secondary hyperparathyroidism was defined as PTH > 300 pg/mL for ≥3 months. Four schedules were tested: conventional dialysis (polysulfone dialyzer 1.8–2.1 m²), with dialysate Ca 1.5 or 1.75 mmol/L, NxStage (Ca 1.5 mmol/L), and NxStage plus intradialytic Ca infusion. Dosages of vitamin D, calcium, phosphate binders, and Ca mimetic agents were adjusted monthly. Eighty Ca‐P‐PTH profiles were collected in 12 patients. Serum phosphate was efficiently reduced by all techniques. No differences in start‐to‐end PTH and Ca levels on dialysis were observed in patients with PTH levels < 300 pg/mL. Conversely, Ca levels in “severe” secondary hyperparathyroid patients significantly increased and PTH decreased during dialysis on all schedules except on Nxstage (P < 0.05). Our data support the need for tailored dialysate Ca content, even on “low‐flow” daily home dialysis, in “severe” secondary hyperparathyroid patients in order to increase the therapeutic potentials of the new dialysis techniques.     

In‐vitro preparation of nanocrystalline calcium phosphates as bone substitution materials in surgery

A continuous preparation method for nanoscopic calcium phosphate ceramics is presented. The influence of processing parameters (temperature, time) on the properties of calcium phosphates was studied. Crystallinity, structure, and morphology are important for an application as biodegradable implant material in bone contact. The samples were studied in detail using X‐ray powder diffraction, infrared spectroscopy, atomic absorption spectroscopy, photometry, scanning electron microscopy, and transmission electron microscopy. All calcium phosphate precipitates are non‐stoichiometric, calcium‐deficient hydroxyapatites.     

The effects of nocturnal compared with conventional hemodialysis on mineral metabolism: A randomized‐controlled trial

Hyperphosphatemia is common among patients receiving dialysis and is associated with increased mortality. Nocturnal hemodialysis (NHD) is a long, slow dialytic modality that may improve hyperphosphatemia and disorders of mineral metabolism. We performed a randomized‐controlled trial of NHD compared with conventional hemodialysis (CvHD); in this paper, we report detailed results of mineral metabolism outcomes. Prevalent patients were randomized to receive NHD 5 to 6 nights per week for 6to 10 hours per night or to continue CvHD thrice weekly for 6 months. Oral phosphate binders and vitamin D analogs were adjusted to maintain phosphate, calcium and parathyroid hormone (PTH) levels within recommended targets. Compared with CvHD patients, patients in the NHD group had a significant decrease in serum phosphate over the course of the study (0.49 mmol/L, 95% confidence interval 0.24–0.74; P=0.002) despite a significant reduction in the use of phosphate binders. Sixty‐one percent of patients in the NHD group compared with 20% in the CvHD group had a decline in intact PTH (P=0.003). Nocturnal hemodialysis lowers serum phosphate, calcium‐phosphate product and requirement for phosphate binders. The effects of NHD on PTH are variable. The impact of these changes on long‐term cardiovascular and bone‐related outcomes requires further investigation.     

Effect of serum FGF‐23, MGP and fetuin‐A on calcium‐phosphate metabolism in maintenance hemodialysis patients

This study was aimed to explore the role of serum fibroblast growth factor (FGF)‐23, matrix Gla protein (MGP) and fetuin‐A in the calcium‐phosphate metabolism and their predicting value in coronary artery calcification in maintenance hemodialysis (MHD) patients. This study included 64 patients who receive hemodialysis in our hospital. The serum FGF‐23, MGP and fetuin‐A were analyzed by enzyme‐linked immunosorbent assay (ELlSA). Coronary artery calcification score (CACS) was evaluated by coronary artery computed tomography scan. The 64 patients (30 males, 34 females, 60.6 ± 11.3 years of age) received an average dialysis vintage of 6.88 ± 2.94 years. We divided the CACS into three levels, and 13 (20.31%), 16 (25%), and 35 (54.69%) exhibited a CACS of 0–100, 100–400, and >400, respectively. Dialysis vintage, serum FGF‐23, fetuin‐A, phosphorus and high‐density lipoprotein‐C levels were identified as independent variables of CACS by stepwise multiple regression analysis. The area under receiver operating characteristic curve indicated that serum FGF‐23 and fetuin‐A were useful for identifying CAC in MHD patients. The cut‐off value corresponding to the highest Youden's index was serum FGF‐23 ≥ 256 pg/mL and fetuin‐A ≤ 85 μg/mL, which was defined as the optimal predictors of CAC. Different combinations of serum FGF‐23 and fetuin‐A in parallel or in series effectively boosted the identification of CAC. The incidence of CAC is high in MHD patients. Serum FGF‐23 and fetuin‐A levels are closely correlated with CAC.     

Numerical integration of a pressure‐dependent,non‐linear kinematic hardening constitutive model for large strain cyclic plasticity of metals

A Gurson‐based constitutive model is presented, which includes non‐linear mixed isotropic–kinematic hardening and creep, and allows the analysis of problems involving arbitrarily large plastic strains. This model was developed with the main objective of allowing, on the basis of a single set of material parameters, the numerical simulation of all the main features of cold metal forming processes, which usually imply severe loading–unloading cycles with very large plastic strains, difficult to be correctly reproduced numerically. A suitable integration scheme of the rate equations is described and implemented into a finite element code. The results obtained are compared with some reference experimental ones; an application of the model for the simulation of wire drawing processes is also presented. Copyright © 2011 John Wiley & Sons, Ltd.     

Efficient numerical implementation of pressure,time, and temperature superposition for elasto‐visco‐plastic material model by using a symbolic approach

This article is concerned with the finite element implementation of an elasto‐visco‐plastic constitutive model using a symbolic approach. The model combines the Knauss–Emri (KE) pressure, temperature, and time superposition principle in the implicit finite element scheme. The equation development and code generation was performed using the symbolic tool AceGen. The same symbolic system was applied to derive analytical sensitivities of the numerical model with respect to the material and shape parameters. To enable efficient numerical implementation of the KE model the convolution integrals were transformed into their respective incremental forms, so that radical improvements of code efficiency and computer storage requirements were achieved. The numerical examples derived for polyethylene terephthalate (PET) polymers demonstrate that symbolic systems can be applied to develop complex constitutive models capable of simulating material responses that are in good agreement with experimental measurements over a wide range of strain rates, temperatures, and loading conditions. Copyright © 2010 John Wiley & Sons, Ltd.     

Structural reliability analysis and uncertainties‐based collaborative design and optimization of turbine blades using surrogate model

In power and energy systems, both the aerodynamic performance and the structure reliability of turbine equipment are affected by utilized blades. In general, the design process of blade is high dimensional and nonlinear. Different coupled disciplines are also involved during this process. Moreover, unavoidable uncertainties are transported and accumulated between these coupled disciplines, which may cause turbine equipment to be unsafe. In this study, a saddlepoint approximation reliability analysis method is introduced and combined with collaborative optimization method to address the above challenge. During the above reliability analysis and design optimization process, surrogate models are utilized to alleviate the computational burden for uncertainties‐based multidisciplinary design and optimization problems. Smooth response surfaces of the performance of turbine blades are constructed instead of expensively time‐consuming simulations. A turbine blade design problem is solved here to validate the effectiveness and show the utilization of the given approach.     

Geometry and topology optimization of sheet metal profiles by using a branch‐and‐bound framework

In this paper well established procedures from partial differential equation (PDE)‐constrained and discrete optimization are combined in a new way to find an optimal design of a multi‐chambered profile. Given a starting profile design, a load case and corresponding design constraints (e.g. sheet thickness, chamber sizes), the aim is to find an optimal subdivision into a predefined number of chambers with optimal shape subject to structural stiffness. In the presented optimization scheme a branch‐and‐bound tree is generated with one additional chamber in each level. Before adding the next chamber, the geometry of the profile is optimized. Then a relaxation of a topology optimization problem is solved. Based on this relaxation, a best fitting feasible topology subject to manufacturability conditions is determined using a new mixed integer method employing shortest paths. To improve the running time, the finite element simulations for the geometry optimization and topology relaxation are performed with different levels of accuracy. Finally, numerical experiments are presented including different starting geometries, load scenarios and mesh sizes.     

Removal of vancomycin administered during dialysis by a high‐flux dialyzer

Introduction: Hemodialysis patients frequently receive vancomycin for treatment of gram‐positive bacterial infections. This drug is most conveniently administered in outpatient dialysis units during the hemodialysis treatment. However, there is a paucity of data on the removal of vancomycin by high‐flux polyamide dialyzers. Methods: This is a prospective crossover study in which seven uninfected chronic hemodialysis patients at three dialysis units received vancomycin 1 gram intravenously over one hour immediately after the dialysis treatment (Phase 1), and vancomycin 1.5 grams during the last hour of dialysis treatment using a polyarylethersulfone, polyvinylpyrrolidone, polyamide high‐flux (Polyflux 24R) dialyzer (Phase 2). There was a three‐week washout period between phases. Serial serum vancomycin concentrations were used to determine the removal of vancomycin when administered during dialysis. Findings: Dialysis removed 35 ± 15% (range 18‐56%) of the vancomycin dose when administered during the last hour of dialysis. The calculated area under the curve (AUC) of vancomycin levels for 0‐44.5 hours from the start of infusion were similar between the two phases (AUC_{Phase 1} 884 ± 124 mg‐hr/L, mean ± SD; AUC_{Phase 2} 856 ± 208 mg‐hr/L; P=0.72). Serum vancomycin concentrations immediately prior to the next dialysis treatment following vancomycin administration were also similar between the two phases (13.1 ± 2.7 mg/L in Phase 1 and 12.3 ± 3.3 mg/L in Phase 2; P=0.55). Discussion: When using a polyarylethersulfone, polyvinylpyrrolidone, and polyamide high‐flux HD membrane with a 24R Polyflux dialyzer, vancomycin can be administered during the last hour of dialysis if the dose that is prescribed for intra‐dialysis dosing is empirically increased to account for intra‐dialytic drug removal.     

Performance Assessment of a Numerical Simulation Tool for Wooden Boards with Knots by Means of Full‐Field Deformation Measurements

In wooden boards, knots and the resulting fibre deviations in their vicinities are mainly responsible for qualitative downgrading of timber elements. Thus, the development of reliable numerical simulation tools for the determination of effective strength and stiffness properties of timber elements and, in a next step, for the development and evaluation of grading criteria is highly desirable. Due to the complexity of such tools, a comprehensive validation is required. Within this work, the suitability of full‐field deformation measurements for four‐point bending tests on wooden boards with knots is evaluated first. Next, the test series is used to validate a previously developed three‐dimensional numerical simulation tool, which combines a geometrical model for the grain course and a micromechanical model for a density and moisture dependent characterisation of the clear‐wood material. The digital image correlation technique proved to be capable to reproduce the strain fields in the vicinity of knots under bending load. Moreover, a very good correlation between numerical and experimental results was obtained.     

A note on the Bayesian analysis of experiments with correlated multiple responses using a matrix‐logarithmic covariance model

In the literature, analysis of multiple responses from experiments with replicates has modeled the covariance matrix directly as linear models of the transformed variances and correlations, ie, covariance modeling. This article considers models based on the matrix‐logarithm of the covariance matrix. This so‐called log‐covariance modeling is illustrated with data from actual experiments and compared with the traditional covariance modeling.     

Super‐resolution of the undersampled and subpixel shifted image sequence by a neural network

Numerous approaches to super‐resolution (SR) of sequentially observed images (image sequence) of low resolution (LR) have been presented in the past two decades. However, neural network methods are almost ignored for solving SR problems. This is because the SR problem traditionally has been regarded as the optimization of an ill‐posed large set of linear equations. A designed neural network based on this has a large number of neurons, thereby requiring a long learning time. Also, the deduced cost function is overly complex. These defects limit applications of a neural network to an SR problem. We think that the underlying meaning of the SR problem should refer to super‐resolving an imaging system by image sequence observation, instead of merely improving the image sequence itself. SR can be regarded as a pattern mapping from LR to SR images. The parameters of the pattern mapping can be learned from the imaging process of the image sequence. This article presents a neural network for SR based on learning from the imaging process of the image sequence. In order to speed up the convergence, we employ vector mapping to train the neural network. A mapping vector is composed of some neighbor subpixels. Such a well‐trained neural network has powerful generalization ability so that it can be used directly to estimate the SR image of the other image sequences without learning again. Our simulations show the effectiveness of the proposed neural network. © 2004 Wiley Periodicals, Inc. Int J Imaging Syst Technol 14, 8–15, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ima.20001