High-resolution computer simulation of the dynamics of isoelectric focusing: in quest of more realistic input parameters for carrier ampholytes

The impact of the systematic variation of either DeltapK(a) or mobility of 140 biprotic carrier ampholytes on the conductivity profile of a pH 3-10 gradient was studied by dynamic computer simulation. A configuration with the greatest DeltapK(a) in the pH 6-7 range and uniform mobilities produced a conductivity profile consistent with that which is experimentally observed. A similar result was observed when the neutral (pI = 7) ampholyte is assigned the lowest mobility and mobilities of the other carriers are systematically increased as their pI's recede from 7. When equal DeltapK(a) values and mobilities are assigned to all ampholytes a conductivity plateau in the pH 5-9 region is produced which does not reflect what is seen experimentally. The variation in DeltapK(a) values is considered to most accurately reflect the electrochemical parameters of commercially available mixtures of carrier ampholytes. Simulations with unequal mobilities of the cationic and anionic species of the carrier ampholytes show either cathodic (greater mobility of the cationic species) or anodic (greater mobility of the anionic species) drifts of the pH gradient. The simulated cationic drifts compare well to those observed experimentally in a capillary in which the focusing of three dyes was followed by whole column optical imaging. The cathodic drift flattens the acidic portion of the gradient and steepens the basic part. This phenomenon is an additional argument against the notion that focused zones of carrier ampholytes have no electrophoretic flux.

An integrated approach for reconstructing surface models of the proximal femur from sparse input data for surgical navigation

A patient-specific surface model of the proximal femur plays an important role in planning and supporting various computer-assisted surgical procedures including total hip replacement, hip resurfacing, and osteotomy of the proximal femur. The common approach to derive 3D models of the proximal femur is to use imaging techniques such as computed tomography (CT) or magnetic resonance imaging (MRI). However, the high logistic effort, the extra radiation (CT-imaging), and the large quantity of data to be acquired and processed make them less functional. In this paper, we present an integrated approach using a multi-level point distribution model (ML-PDM) to reconstruct a patient-specific model of the proximal femur from intra-operatively available sparse data. Results of experiments performed on dry cadaveric bones using dozens of 3D points are presented, as well as experiments using a limited number of 2D X-ray images, which demonstrate promising accuracy of the present approach.

A computer-aided diagnostic system to characterize CT focal liver lesions: design and optimization of a neural network classifier

In this paper, a computer-aided diagnostic (CAD) system for the classification of hepatic lesions from computed tomography (CT) images is presented. Regions of interest (ROIs) taken from nonenhanced CT images of normal liver, hepatic cysts, hemangiomas, and hepatocellular carcinomas have been used as input to the system. The proposed system consists of two modules: the feature extraction and the classification modules. The feature extraction module calculates the average gray level and 48 texture characteristics, which are derived from the spatial gray-level co-occurrence matrices, obtained from the ROIs. The classifier module consists of three sequentially placed feed-forward neural networks (NNs). The first NN classifies into normal or pathological liver regions. The pathological liver regions are characterized by the second NN as cyst or "other disease." The third NN classifies "other disease" into hemangioma or hepatocellular carcinoma. Three feature selection techniques have been applied to each individual NN: the sequential forward selection, the sequential floating forward selection, and a genetic algorithm for feature selection. The comparative study of the above dimensionality reduction methods shows that genetic algorithms result in lower dimension feature vectors and improved classification performance.

Dynamic computer simulation of electrophoretic enantiomer migration order and separation in presence of a neutral cyclodextrin

One-dimensional dynamic computer simulation was employed to investigate the separation and migration order change of ketoconazole enantiomers at low pH in presence of increasing amounts of (2-hydroxypropyl)-β-cyclodextrin (OHP-β-CD). The 1:1 interaction of ketoconazole with the neutral cyclodextrin was simulated under real experimental conditions and by varying input parameters for complex mobilities and complexation constants. Simulation results obtained with experimentally determined apparent ionic mobilities, complex mobilities, and complexation constants were found to compare well with the calculated separation selectivity and experimental data. Simulation data revealed that the migration order of the ketoconazole enantiomers at low (OHP-β-CD) concentrations (i.e. below migration order inversion) is essentially determined by the difference in complexation constants and at high (OHP-β-CD) concentrations (i.e. above migration order inversion) by the difference in complex mobilities. Furthermore, simulations with complex mobilities set to zero provided data that mimic migration order and separation with the chiral selector being immobilized. For the studied CEC configuration, no migration order inversion is predicted and separations are shown to be quicker and electrophoretic transport reduced in comparison to migration in free solution. The presented data illustrate that dynamic computer simulation is a valuable tool to study electrokinetic migration and separations of enantiomers in presence of a complexing agent.