Capillary electrophoresis contributions to the hydromorphone metabolism in man

CE-ESI multistage IT-MS (CE-MS(n), n < or = 4) and computer simulation of fragmentation are demonstrated to be effective tools to detect and identify phase I and phase II metabolites of hydromorphone (HMOR) in human urine. Using the same CE conditions as previously developed for the analysis of urinary oxycodone and its metabolites, HMOR and its phase I metabolites produced by N-demethylation, 6-keto-reduction and N-oxidation and phase II conjugates of HMOR and its metabolites formed with glucuronic acid, glucose, and sulfuric acid could be detected in urine samples of a patient that were collected during a pharmacotherapy episode with daily ingestion of 48 mg of HMOR chloride. The CE-MS(n) data obtained with the HMOR standard, synthesized hydromorphol and hydromorphone-N-oxide, and CYP3A4 in vitro produced norhydromorphone were employed to identify the metabolites. This approach led to the identification of previously unknown HMOR metabolites, including HMOR-3O-glucide and various N-oxides, structures for which no standard compounds or mass spectra library data were available. Furthermore, the separation of alpha- and beta-hydromorphol, the stereoisomers of 6-keto-reduced HMOR, was achieved by CE in the presence of the single isomer heptakis(2,3-diacetyl-6-sulfato)-beta-CD. The obtained data indicate that the urinary excretion of alpha-hydromorphol is larger than that of beta-hydromorphol.

POOR PERFORMANCE OF BOOTSTRAP CONFIDENCE INTERVALS FOR THE LOCATION OF A QUANTITATIVE TRAIT LOUCS

The aim of many genetic studies is to locate the genomic regions (called quantitative trait loci, QTLs) that contribute to variation in a quantitative trait (such as body weight). Confidence intervals for the locations of QTLs are particularly important for the design of further experiments to identify the gene or genes responsible for the effect. Likelihood support intervals are the most widely used method to obtain confidence intervals for QTL location, but the non-parametric bootstrap has also been recommended. Through extensive computer simulation, we show that bootstrap confidence intervals are poorly behaved and so should not be used in this context. The profile likelihood (or LOD curve) for QTL location has a tendency to peak at genetic markers, and so the distribution of the maximum likelihood estimate (MLE) of QTL location has the unusual feature of point masses at genetic markers; this contributes to the poor behavior of the bootstrap. Likelihood support intervals and approximate Bayes credible intervals, on the other hand, are shown to behave appropriately.

Optimized temperature and deadspace correction improve analysis of multiple breath washout measurements by ultrasonic flowmeter in infants

BACKGROUND: Assessment of lung volume (FRC) and ventilation inhomogeneities with ultrasonic flowmeter and multiple breath washout (MBW) has been used to provide important information about lung disease in infants. Sub-optimal adjustment of the mainstream molar mass (MM) signal for temperature and external deadspace may lead to analysis errors in infants with critically small tidal volume changes during breathing. METHODS: We measured expiratory temperature in human infants at 5 weeks of age and examined the influence of temperature and deadspace changes on FRC results with computer simulation modeling. A new analysis method with optimized temperature and deadspace settings was then derived, tested for robustness to analysis errors and compared with the previously used analysis methods. RESULTS: Temperature in the facemask was higher and variations of deadspace volumes larger than previously assumed. Both showed considerable impact upon FRC and LCI results with high variability when obtained with the previously used analysis model. Using the measured temperature we optimized model parameters and tested a newly derived analysis method, which was found to be more robust to variations in deadspace. Comparison between both analysis methods showed systematic differences and a wide scatter. CONCLUSION: Corrected deadspace and more realistic temperature assumptions improved the stability of the analysis of MM measurements obtained by ultrasonic flowmeter in infants. This new analysis method using the only currently available commercial ultrasonic flowmeter in infants may help to improve stability of the analysis and further facilitate assessment of lung volume and ventilation inhomogeneities in infants.

Hip damage occurs at the zone of femoroacetabular impingement

Although current concepts of anterior femoroacetabular impingement predict damage in the labrum and the cartilage, the actual joint damage has not been verified by computer simulation. We retrospectively compared the intraoperative locations of labral and cartilage damage of 40 hips during surgical dislocation for cam or pincer type femoroacetabular impingement (Group I) with the locations of femoroacetabular impingement in 15 additional hips using computer simulation (Group II). We found no difference between the mean locations of the chondrolabral damage of Group I and the computed impingement zone of Group II. The standard deviation was larger for measures of articular damage from Group I in comparison to the computed values of Group II. The most severe hip damage occurred at the zone of highest probability of femoroacetabular impact, typically in the anterosuperior quadrant of the acetabulum for both cam and pincer type femoroacetabular impingements. However, the extent of joint damage along the acetabular rim was larger intraoperatively than that observed on the images of the 3-D joint simulations. We concluded femoroacetabular impingement mechanism contributes to early osteoarthritis including labral lesions. LEVEL OF EVIDENCE: Level II, diagnostic study. See the Guidelines for Authors for a complete description of levels of evidence.

Properties of an injectable low modulus PMMA bone cement for osteoporotic bone

The use of polymethylmethacrylate (PMMA) cement to reinforce fragile or broken vertebral bodies (vertebroplasty) leads to extensive bone stiffening. Fractures in the adjacent vertebrae may be the consequence of this procedure. PMMA with a reduced Young's modulus may be more suitable. The goal of this study was to produce and characterize stiffness adapted PMMA bone cements. Porous PMMA bone cements were produced by combining PMMA with various volume fractions of an aqueous sodium hyaluronate solution. Porosity, Young's modulus, yield strength, polymerization temperature, setting time, viscosity, injectability, and monomer release of those porous cements were investigated. Samples presented pores with diameters in the range of 25-260 microm and porosity up to 56%. Young's modulus and yield strength decreased from 930 to 50 MPa and from 39 to 1.3 MPa between 0 and 56% porosity, respectively. The polymerization temperature decreased from 68 degrees C (0%, regular cement) to 41 degrees C for cement having 30% aqueous fraction. Setting time decreased from 1020 s (0%, regular cement) to 720 s for the 30% composition. Viscosity of the 30% composition (145 Pa s) was higher than the ones received from regular cement and the 45% composition (100-125 Pa s). The monomer release was in the range of 4-10 mg/mL for all porosities; showing no higher release for the porous materials. The generation of pores using an aqueous gel seems to be a promising method to make the PMMA cement more compliant and lower its mechanical properties to values close to those of cancellous bone.

Parameter estimation for transformer modeling

Large Power transformers, an aging and vulnerable part of our energy infrastructure, are at choke points in the grid and are key to reliability and security. Damage or destruction due to vandalism, misoperation, or other unexpected events is of great concern, given replacement costs upward of $2M and lead time of 12 months. Transient overvoltages can cause great damage and there is much interest in improving computer simulation models to correctly predict and avoid the consequences. EMTP (the Electromagnetic Transients Program) has been developed for computer simulation of power system transients. Component models for most equipment have been developed and benchmarked. Power transformers would appear to be simple. However, due to their nonlinear and frequency-dependent behaviors, they can be one of the most complex system components to model. It is imperative that the applied models be appropriate for the range of frequencies and excitation levels that the system experiences. Thus, transformer modeling is not a mature field and newer improved models must be made available. In this work, improved topologically-correct duality-based models are developed for three-phase autotransformers having five-legged, three-legged, and shell-form cores. The main problem in the implementation of detailed models is the lack of complete and reliable data, as no international standard suggests how to measure and calculate parameters. Therefore, parameter estimation methods are developed here to determine the parameters of a given model in cases where available information is incomplete. The transformer nameplate data is required and relative physical dimensions of the core are estimated. The models include a separate representation of each segment of the core, including hysteresis of the core, λ-i saturation characteristic, capacitive effects, and frequency dependency of winding resistance and core loss. Steady-state excitation, and de-energization and re-energization transients are simulated and compared with an earlier-developed BCTRAN-based model. Black start energization cases are also simulated as a means of model evaluation and compared with actual event records. The simulated results using the model developed here are reasonable and more correct than those of the BCTRAN-based model. Simulation accuracy is dependent on the accuracy of the equipment model and its parameters. This work is significant in that it advances existing parameter estimation methods in cases where the available data and measurements are incomplete. The accuracy of EMTP simulation for power systems including three-phase autotransformers is thus enhanced. Theoretical results obtained from this work provide a sound foundation for development of transformer parameter estimation methods using engineering optimization. In addition, it should be possible to refine which information and measurement data are necessary for complete duality-based transformer models. To further refine and develop the models and transformer parameter estimation methods developed here, iterative full-scale laboratory tests using high-voltage and high-power three-phase transformer would be helpful.

Introduction to Realistic Neural Modeling

This document corresponds to the tutorial on realistic neural modeling given by David Beeman at WAM-BAMM*05, the first annual meeting of the World Association of Modelers (WAM) Biologically Accurate Modeling Meeting (BAMM) on March 31, 2005 in San Antonio, TX. Part I - Introduction to Realistic Neural Modeling for the Beginner: This is a general overview and introduction to compartmental cell modeling and realistic network simulation for the beginner. Although examples are drawn from GENESIS simulations, the tutorial emphasizes the general modeling approach, rather than the details of using any particular simulator. Part II - Getting Started with Modeling Using GENESIS: This builds upon the background of Part I to describe some details of how this approach is used to construct cell and network simulations in GENESIS. It serves as an introduction and roadmap to the extended hands-on GENESIS Modeling Tutorial.

Recent Developments in NEURON

We describe four recent additions to NEURON's suite of graphical tools that make it easier for users to create and manage models: an enhancement to the Channel Builder that facilitates the specification and efficient simulation of stochastic channel models

Modeling Calcium Concentration and Biochemical Reactions

Almost all regions of the brain receive one or more neuromodulatory inputs, and disrupting these inputs produces deficits in neuronal function. Neuromodulators act through intracellular second messenger pathways to influence the electrical properties of neurons, integration of synaptic inputs, spatio-temporal firing dynamics of neuronal networks, and, ultimately, systems behavior. Second messengers pathways consist of series of bimolecular reactions, enzymatic reactions, and diffusion. Calcium is the second messenger molecule with the most effectors, and thus is highly regulated by buffers, pumps and intracellular stores. Computational modeling provides an innovative, yet practical method to evaluate the spatial extent, time course and interaction among second messenger pathways, and the interaction of second messengers with neuron electrical properties. These processes occur both in compartments where the number of molecules are large enough to describe reactions deterministically (e.g. cell body), and in compartments where the number of molecules is small enough that reactions occur stochastically (e.g. spines). – In this tutorial, I explain how to develop models of second messenger pathways and calcium dynamics. The first part of the tutorial explains the equations used to model bimolecular reactions, enzyme reactions, calcium release channels, calcium pumps and diffusion. The second part explains some of the GENESIS, Kinetikit and Chemesis objects that implement the appropriate equations. In depth explanation of calcium and second messenger models is provided by reviewing code, both in XPP, Chemesis and Kinetikit, that implements simple models of calcium dynamics and second messenger cascades.

Neural Networks as Cybernetic Systems - Part I

Neural Networks as Cybernetic Systems is a textbox that combines classical systems theory with artificial neural network technology.

Neural Networks as Cybernetic Systems - Part II

Neural Networks as Cybernetic Systems is a textbox that combines classical systems theory with artificial neural network technology.

The art to keep in touch: The ''good use'' of Lagrange multipliers

Physically-based modeling for computer animation allows to produce more realistic motions in less time without requiring the expertise of skilled animators. But, a computer animation is not only a numerical simulation based on classical mechanics since it follows a precise story-line. One common way to define aims in an animation is to add geometric constraints. There are several methods to manage these constraints within a physically-based framework. In this paper, we present an algorithm for constraints handling based on Lagrange multipliers. After few remarks on the equations of motion that we use, we present a first algorithm proposed by Platt. We show with a simple example that this method is not reliable. Our contribution consists in improving this algorithm to provide an efficient and robust method to handle simultaneous active constraints.

Neural Networks as Cybernetic Systems (3rd and revised edition) - Part I

Neural Networks as Cybernetic Systems is a textbox that combines classical systems theory with artificial neural network technology. This third edition essentially compares with the 2nd one, but has been improved by correction of errors and by a rearrangement and minor expansion of the sections referring to recurrent networks. These changes hopefully allow for an easier comprehension of the essential aspects of this important domain that has received growing attention during the last years.

Neural Networks as Cybernetic Systems (3rd and revised edition) - Part 2

eural Networks as Cybernetic Systems is a textbox that combines classical systems theory with artificial neural network technology. This third edition essentially compares with the 2nd one, but has been improved by correction of errors and by a rearrangement and minor expansion of the sections referring to recurrent networks. These changes hopefully allow for an easier comprehension of the essential aspects of this important domain that has received growing attention during the last years.