Molecular phylogenetics of soricid shrews (Mammalia) based on mitochondrial cytochrome b gene sequences: with special reference to the Soricinae

Molecular phylogeny of soricid shrews (Soricidae, Eulipotyphla, Mammalia) based on 1140 bp mitochondrial cytochrome b gene (cytb) sequences was inferred by the maximum likelihood (ML) method. All 13 genera of extant Soricinae and two genera of Crocidurinae were included in the analyses. Anourosorex was phylogenetically distant from the main groupings within Soricinae and Crocidurinae in the ML tree. Thus, it could not be determined to which subfamily Anourosorex should be assigned: Soricinae, Crocidurinae or a new subfamily. Soricinae (excluding Anourosorex) should be divided into four tribes: Neomyini, Notiosoricini, Soricini and Blarinini. However, monophyly of Blarinini was not robust in the present data set. Also, branching orders among tribes of Soricinae and those among genera of Neomyini could not be determined because of insufficient phylogenetic information of the cytb sequences. For water shrews of Neomyini (Chimarrogale, Nectogale and Neomys), monophyly of Neomys and the Chimarrogale-Nectogale group could not be verified, which implies the possibility of multiple origins for the semi-aquatic mode of living among taxa within Neomyini. Episoriculus may contain several separate genera. Blarinella was included in Blarinini not Soricini, based on the cytb sequences, but the confidence level was rather low; hence more phylogenetic information is needed to determine its phylogenetic position. Furthermore, some specific problems of taxonomy of soricid shrews were clarified, for example phylogeny of local populations of Notiosorex crawfordi, Chimarrogale himalayica and Crocidura attenuata.

Optimized MEGA-SPECIAL for in vivo glutamine detection in the rat brain at 14.1 T.

Glutamine has multiple roles in brain metabolism and its concentration can be altered in various pathological conditions. An accurate knowledge of its concentration is therefore highly desirable to monitor and study several brain disorders in vivo. However, in recent years, several MRS studies have reported conflicting glutamine concentrations in the human brain. A recent hypothesis for explaining these discrepancies is that a short T2 component of the glutamine signal may impact on its quantification at long echo times. The present study therefore aimed to investigate the impact of acquisition parameters on the quantified glutamine concentration using two different acquisition techniques, SPECIAL at ultra-short echo time and MEGA-SPECIAL at moderate echo time. For this purpose, MEGA-SPECIAL was optimized for the first time for glutamine detection. Based on the very good agreement of the glutamine concentration obtained between the two measurements, it was concluded that no impact of a short T2 component of the glutamine signal was detected.

What's so special about conversion disorder? A problem and a proposal for diagnostic classification.

Conversion disorder presents a problem for the revisions of DSM-IV and ICD-10, for reasons that are informative about the difficulties of psychiatric classification more generally. Giving up criteria based on psychological aetiology may be a painful sacrifice but it is still the right thing to do.

Robust Nonlinear Mapping of Soil Contamination Using Support Regression

Spatial data analysis mapping and visualization is of great importance in various fields: environment, pollution, natural hazards and risks, epidemiology, spatial econometrics, etc. A basic task of spatial mapping is to make predictions based on some empirical data (measurements). A number of state-of-the-art methods can be used for the task: deterministic interpolations, methods of geostatistics: the family of kriging estimators (Deutsch and Journel, 1997), machine learning algorithms such as artificial neural networks (ANN) of different architectures, hybrid ANN-geostatistics models (Kanevski and Maignan, 2004; Kanevski et al., 1996), etc. All the methods mentioned above can be used for solving the problem of spatial data mapping. Environmental empirical data are always contaminated/corrupted by noise, and often with noise of unknown nature. That's one of the reasons why deterministic models can be inconsistent, since they treat the measurements as values of some unknown function that should be interpolated. Kriging estimators treat the measurements as the realization of some spatial randomn process. To obtain the estimation with kriging one has to model the spatial structure of the data: spatial correlation function or (semi-)variogram. This task can be complicated if there is not sufficient number of measurements and variogram is sensitive to outliers and extremes. ANN is a powerful tool, but it also suffers from the number of reasons. of a special type ? multiplayer perceptrons ? are often used as a detrending tool in hybrid (ANN+geostatistics) models (Kanevski and Maignank, 2004). Therefore, development and adaptation of the method that would be nonlinear and robust to noise in measurements, would deal with the small empirical datasets and which has solid mathematical background is of great importance. The present paper deals with such model, based on Statistical Learning Theory (SLT) - Support Vector Regression. SLT is a general mathematical framework devoted to the problem of estimation of the dependencies from empirical data (Hastie et al, 2004; Vapnik, 1998). SLT models for classification - Support Vector Machines - have shown good results on different machine learning tasks. The results of SVM classification of spatial data are also promising (Kanevski et al, 2002). The properties of SVM for regression - Support Vector Regression (SVR) are less studied. First results of the application of SVR for spatial mapping of physical quantities were obtained by the authorsin for mapping of medium porosity (Kanevski et al, 1999), and for mapping of radioactively contaminated territories (Kanevski and Canu, 2000). The present paper is devoted to further understanding of the properties of SVR model for spatial data analysis and mapping. Detailed description of the SVR theory can be found in (Cristianini and Shawe-Taylor, 2000; Smola, 1996) and basic equations for the nonlinear modeling are given in section 2. Section 3 discusses the application of SVR for spatial data mapping on the real case study - soil pollution by Cs137 radionuclide. Section 4 discusses the properties of the modelapplied to noised data or data with outliers.

Current cardiovascular risk management patterns with special focus on lipid lowering in daily practice in Switzerland.

Background: There may be a considerable gap between LDL cholesterol (LDL-C) and blood pressure (BP) goal values recommended by the guidelines and results achieved in daily practice. Design Prospective cross-sectional survey of cardiovascular disease risk profiles and management with focus on lipid lowering and BP lowering in clinical practice. Methods: In phase 1, the cardiovascular risk of patients with known lipid profile visiting their general practitioner was anonymously assessed in accordance to the PROCAM-score. In phase 2, high-risk patients who did not achieve LDL-C goal less than 2.6 mmol/l in phase 1 could be further documented. Results: Six hundred thirty-five general practitioners collected the data of 23 892 patients with known lipid profile. Forty percent were high-risk patients (diabetes mellitus or coronary heart disease or PROCAM-score >20%), compared with 27% estimated by the physicians. Goal attainment rate was almost double for BP than for LDL-C in high-risk patients (62 vs. 37%). Both goals were attained by 25%. LDL-C values in phase 1 and 2 were available for 3097 high-risk patients not at LDL-C goal in phase 1; 32% of patients achieved LDL-C goal of less than 2.6 mmol/l after a mean of 17 weeks. The most successful strategies for LDL-C reduction were implemented in only 22% of the high-risk patients. Conclusion: Although patients at high cardiovascular risk were treated more intensively than low or medium risk patients, the majority remained insufficiently controlled, which is an incentive for intensified medical education. Adequate implementation of Swiss and International guidelines would expectedly contribute to improved achievement of LDL-C and BP goal values in daily practice.