Completed suicides of citalopram users-the role of CYP genotypes and adverse drug interactions.

Depression is known to be a risk factor for suicide. Currently, the most used antidepressants are selective serotonin reuptake inhibitors (SSRIs). Not all users, however, benefit from them. In such cases, treatment failure can be explained in part by genetic differences. In this study, we investigated the role of pharmacogenetic factors in citalopram-positive completed suicides (n = 349). Since citalopram is metabolized by CYP2C19 and CYP2D6 enzymes, the study population was genotyped for clinically relevant CYP2C19 and CYP2D6 polymorphisms and CYP2D6 copy number variation. To assess genetic differences between suicide cases and Finns in general, Finnish population samples (n = 855) were used as controls. Also, the role of drug interactions among suicide cases was evaluated. We found enrichment of a combined group of genetically predicted poor and ultrarapid metabolizer phenotypes (gMPs) of CYP2C19 among suicide victims compared to controls 0.356 [0.31-0.41] vs. 0.265 [0.24-0.30] (p = 0.0065). In CYP2D6 gMPs, there was no difference between cases and controls when the study population was analyzed as a whole. However, there were significantly more poor metabolizers among females who committed suicide by poisoning compared to female controls. In 8% of all drug poisoning deaths, lifetime drug-drug interaction was evaluated having a contribution to the fatal outcome. From clinical perspective, pharmacogenetic testing prior to initiation of SSRI drug could be beneficial. It may also be useful in medico-legal settings as it may elucidate obscure poisoning cases. Also, the possibility of unintentional drug interactions should be taken into account in drug poisoning deaths.

A MATLAB package for the EIDORS project to reconstruct two-dimensional EIT images.

The EIDORS (electrical impedance and diffuse optical reconstruction software) project aims to produce a software system for reconstructing images from electrical or diffuse optical data. MATLAB is a software that is used in the EIDORS project for rapid prototyping, graphical user interface construction and image display. We have written a MATLAB package (http://venda.uku.fi/ vauhkon/) which can be used for two-dimensional mesh generation, solving the forward problem and reconstructing and displaying the reconstructed images (resistivity or admittivity). In this paper we briefly describe the mathematical theory on which the codes are based on and also give some examples of the capabilities of the package.

Sensitivity matrix and reconstruction algorithm for EIT assuming axial uniformity.

In electrical impedance tomography (EIT) two-dimensional models continue to be applied despite their known inability to provide correct reconstruction. In this paper, a reconstruction algorithm that assumes a translationally invariant conductivity distribution is described. A more precise forward solver is obtained by taking off-slice currents into consideration. An appropriate sensitivity matrix is derived. Numerical evidence for the improvement in precision compared to two-dimensional reconstruction is given.

Errors due to the truncation of the computational domain in static three-dimensional electrical impedance tomography.

In electrical impedance tomography (EIT), an approximation for the internal resistivity distribution is computed based on the knowledge of the injected currents and measured voltages on the surface of the body. The currents spread out in three dimensions and therefore off-plane structures have a significant effect on the reconstructed images. A question arises: how far from the current carrying electrodes should the discretized model of the object be extended? If the model is truncated too near the electrodes, errors are produced in the reconstructed images. On the other hand if the model is extended very far from the electrodes the computational time may become too long in practice. In this paper the model truncation problem is studied with the extended finite element method. Forward solutions obtained using so-called infinite elements, long finite elements and separable long finite elements are compared to the correct solution. The effects of the truncation of the computational domain on the reconstructed images are also discussed and results from the three-dimensional (3D) sensitivity analysis are given. We show that if the finite element method with ordinary elements is used in static 3D EIT, the dimension of the problem can become fairly large if the errors associated with the domain truncation are to be avoided.

Three-dimensional electrical impedance tomography based on the complete electrode model.

In electrical impedance tomography an approximation for the internal resistivity distribution is computed based on the knowledge of the injected currents and measured voltages on the surface of the body. It is often assumed that the injected currents are confined to the two-dimensional (2-D) electrode plane and the reconstruction is based on 2-D assumptions. However, the currents spread out in three dimensions and, therefore, off-plane structures have significant effect on the reconstructed images. In this paper we propose a finite element-based method for the reconstruction of three-dimensional resistivity distributions. The proposed method is based on the so-called complete electrode model that takes into account the presence of the electrodes and the contact impedances. Both the forward and the inverse problems are discussed and results from static and dynamic (difference) reconstructions with real measurement data are given. It is shown that in phantom experiments with accurate finite element computations it is possible to obtain static images that are comparable with difference images that are reconstructed from the same object with the empty (saline filled) tank as a reference.