Quantitative proteome analysis in cardiovascular physiology and pathology. I. Data processing

Methodological evaluation of the proteomic analysis of cardiovascular-tissue material has been performed with a special emphasis on establishing examinations that allow reliable quantitative analysis of silver-stained readouts. Reliability, reproducibility, robustness and linearity were addressed and clarified. In addition, several types of normalization procedures were evaluated and new approaches are proposed. It has been found that the silver-stained readout offers a convenient approach for quantitation if a linear range for gel loading is defined. In addition, a broad range of a 10-fold input (loading 20-200 microg per gel) fulfills the linearity criteria, although at the lowest input (20 microg) a portion of protein species will remain undetected. The method is reliable and reproducible within a range of 65-200 microg input. The normalization procedure using the sum of all spot intensities from a silver-stained 2D pattern has been shown to be less reliable than other approaches, namely, normalization through median or through involvement of interquartile range. A special refinement of the normalization through virtual segmentation of pattern, and calculation of normalization factor for each stratum provides highly satisfactory results. The presented results not only provide evidence for the usefulness of silver-stained gels for quantitative evaluation, but they are directly applicable to the research endeavor of monitoring alterations in cardiovascular pathophysiology.

Borrelia in granuloma annulare, morphea and lichen sclerosus: a PCR-based study and review of the literature

Morphea, granuloma annulare (GA) and lichen sclerosus et atrophicans (LSA) have also been suggested to be linked to Borrelia infection. Previous studies based on serologic data or detection of Borrelia by immunohistochemistry and polymerase chain reaction (PCR) reported contradictory results. Thus, we examined skin biopsies of morphea, GA and LSA by PCR to assess the prevalence of Borrelia DNA in an endemic area and to compare our results with data in the literature.

Safety of non-therapeutic atomoxetine exposures - a national poison data system study

AIMS This study's objective is to assess the safety of non-therapeutic atomoxetine exposures reported to the US National Poison Database System (NPDS). METHODS This is a retrospective database study of non-therapeutic single agent ingestions of atomoxetine in children and adults reported to the NPDS between 2002 and 2010. RESULTS A total of 20 032 atomoxetine exposures were reported during the study period, and 12 370 of these were single agent exposures. The median age was 9 years (interquartile range 3, 14), and 7380 were male (59.7%). Of the single agent exposures, 8813 (71.2%) were acute exposures, 3315 (26.8%) were acute-on-chronic, and 166 (1.3%) were chronic. In 10 608 (85.8%) cases, exposure was unintentional, in 1079 (8.7%) suicide attempts, and in 629 (5.1%) cases abuse. Of these cases, 3633 (29.4 %) were managed at health-care facilities. Acute-on-chronic exposure was associated with an increased risk of a suicidal reason for exposure compared with acute ingestions (odds ratio 1.44, 95% confidence interval 1.26-1.65). Most common clinical effects were drowsiness or lethargy (709 cases; 5.7%), tachycardia (555; 4.5%), and nausea (388; 3.1%). Major toxicity was observed in 21 cases (seizures in nine (42.9%), tachycardia in eight (38.1%), coma in six (28.6%), and ventricular dysrhythmia in one case (4.8%)). CONCLUSIONS Non-therapeutic atomoxetine exposures were largely safe, but seizures were rarely observed.

Paleoclimate data-model comparison and the role of climate forcings over the past 1500 years

The past 1500 years provide a valuable opportunity to study the response of the climate system to external forcings. However, the integration of paleoclimate proxies with climate modeling is critical to improving the understanding of climate dynamics. In this paper, a climate system model and proxy records are therefore used to study the role of natural and anthropogenic forcings in driving the global climate. The inverse and forward approaches to paleoclimate data–model comparison are applied, and sources of uncertainty are identified and discussed. In the first of two case studies, the climate model simulations are compared with multiproxy temperature reconstructions. Robust solar and volcanic signals are detected in Southern Hemisphere temperatures, with a possible volcanic signal detected in the Northern Hemisphere. The anthropogenic signal dominates during the industrial period. It is also found that seasonal and geographical biases may cause multiproxy reconstructions to overestimate the magnitude of the long-term preindustrial cooling trend. In the second case study, the model simulations are compared with a coral δ18O record from the central Pacific Ocean. It is found that greenhouse gases, solar irradiance, and volcanic eruptions all influence the mean state of the central Pacific, but there is no evidence that natural or anthropogenic forcings have any systematic impact on El Niño–Southern Oscillation. The proxy climate relationship is found to change over time, challenging the assumption of stationarity that underlies the interpretation of paleoclimate proxies. These case studies demonstrate the value of paleoclimate data–model comparison but also highlight the limitations of current techniques and demonstrate the need to develop alternative approaches.

Loss to follow-up of HIV-infected women after delivery: The Swiss HIV Cohort Study and the Swiss Mother and Child HIV Cohort Study.

INTRODUCTION HIV-infected pregnant women are very likely to engage in HIV medical care to prevent transmission of HIV to their newborn. After delivery, however, childcare and competing commitments might lead to disengagement from HIV care. The aim of this study was to quantify loss to follow-up (LTFU) from HIV care after delivery and to identify risk factors for LTFU. METHODS We used data on 719 pregnancies within the Swiss HIV Cohort Study from 1996 to 2012 and with information on follow-up visits available. Two LTFU events were defined: no clinical visit for >180 days and no visit for >360 days in the year after delivery. Logistic regression analysis was used to identify risk factors for a LTFU event after delivery. RESULTS Median maternal age at delivery was 32 years (IQR 28-36), 357 (49%) women were black, 280 (39%) white, 56 (8%) Asian and 4% other ethnicities. One hundred and seven (15%) women reported any history of IDU. The majority (524, 73%) of women received their HIV diagnosis before pregnancy, most of those (413, 79%) had lived with diagnosed HIV longer than three years and two-thirds (342, 65%) were already on antiretroviral therapy (ART) at time of conception. Of the 181 women diagnosed during pregnancy by a screening test, 80 (44%) were diagnosed in the first trimester, 67 (37%) in the second and 34 (19%) in the third trimester. Of 357 (69%) women who had been seen in HIV medical care during three months before conception, 93% achieved an undetectable HIV viral load (VL) at delivery. Of 62 (12%) women with the last medical visit more than six months before conception, only 72% achieved an undetectable VL (p=0.001). Overall, 247 (34%) women were LTFU over 180 days in the year after delivery and 86 (12%) women were LTFU over 360 days with 43 (50%) of those women returning. Being LTFU for 180 days was significantly associated with history of intravenous drug use (aOR 1.73, 95% CI 1.09-2.77, p=0.021) and not achieving an undetectable VL at delivery (aOR 1.79, 95% CI 1.03-3.11, p=0.040) after adjusting for maternal age, ethnicity, time of HIV diagnosis and being on ART at conception. CONCLUSIONS Women with a history of IDU and women with a detectable VL at delivery were more likely to be LTFU after delivery. This is of concern regarding their own health, as well as risk for sexual partners and subsequent pregnancies. Further strategies should be developed to enhance retention in medical care beyond pregnancy.

3D Intervertebral Disc Localization and Segmentation from MR Images by Data-Driven Regression and Classification

In this paper we propose a new fully-automatic method for localizing and segmenting 3D intervertebral discs from MR images, where the two problems are solved in a unified data-driven regression and classification framework. We estimate the output (image displacements for localization, or fg/bg labels for segmentation) of image points by exploiting both training data and geometric constraints simultaneously. The problem is formulated in a unified objective function which is then solved globally and efficiently. We validate our method on MR images of 25 patients. Taking manually labeled data as the ground truth, our method achieves a mean localization error of 1.3 mm, a mean Dice metric of 87%, and a mean surface distance of 1.3 mm. Our method can be applied to other localization and segmentation tasks.

Time Variable Gravity: Contributions of GOCE Satellite Data to Monthly and Bi-monthly GRACE Gravity Estimates

A feasibility study by Pail et al. (Can GOCE help to improve temporal gravity field estimates? In: Ouwehand L (ed) Proceedings of the 4th International GOCE User Workshop, ESA Publication SP-696, 2011b) shows that GOCE (‘Gravity field and steady-state Ocean Circulation Explorer’) satellite gravity gradiometer (SGG) data in combination with GPS derived orbit data (satellite-to-satellite tracking: SST-hl) can be used to stabilize and reduce the striping pattern of a bi-monthly GRACE (‘Gravity Recovery and Climate Experiment’) gravity field estimate. In this study several monthly (and bi-monthly) combinations of GRACE with GOCE SGG and GOCE SST-hl data on the basis of normal equations are investigated. Our aim is to assess the role of the gradients (solely) in the combination and whether already one month of GOCE observations provides sufficient data for having an impact in the combination. The estimation of clean and stable monthly GOCE SGG normal equations at high resolution ( >  d/o 150) is found to be difficult, and the SGG component, solely, does not show significant added value to monthly and bi-monthly GRACE gravity fields. Comparisons of GRACE-only and combined monthly and bi-monthly solutions show that the striping pattern can only be reduced when using both GOCE observation types (SGG, SST-hl), and mainly between d/o 45 and 60.

Index Tracking Using Data-Mining Techniques and Mixed-Binary Linear Programming

Index tracking has become one of the most common strategies in asset management. The index-tracking problem consists of constructing a portfolio that replicates the future performance of an index by including only a subset of the index constituents in the portfolio. Finding the most representative subset is challenging when the number of stocks in the index is large. We introduce a new three-stage approach that at first identifies promising subsets by employing data-mining techniques, then determines the stock weights in the subsets using mixed-binary linear programming, and finally evaluates the subsets based on cross validation. The best subset is returned as the tracking portfolio. Our approach outperforms state-of-the-art methods in terms of out-of-sample performance and running times.

Comparing CFSR and conventional weather data for discharge and soil loss modelling with SWAT in small catchments in the Ethiopian Highlands

Accurate rainfall data are the key input parameter for modelling river discharge and soil loss. Remote areas of Ethiopia often lack adequate precipitation data and where these data are available, there might be substantial temporal or spatial gaps. To counter this challenge, the Climate Forecast System Reanalysis (CFSR) of the National Centers for Environmental Prediction (NCEP) readily provides weather data for any geographic location on earth between 1979 and 2014. This study assesses the applicability of CFSR weather data to three watersheds in the Blue Nile Basin in Ethiopia. To this end, the Soil and Water Assessment Tool (SWAT) was set up to simulate discharge and soil loss, using CFSR and conventional weather data, in three small-scale watersheds ranging from 112 to 477 ha. Calibrated simulation results were compared to observed river discharge and observed soil loss over a period of 32 years. The conventional weather data resulted in very good discharge outputs for all three watersheds, while the CFSR weather data resulted in unsatisfactory discharge outputs for all of the three gauging stations. Soil loss simulation with conventional weather inputs yielded satisfactory outputs for two of three watersheds, while the CFSR weather input resulted in three unsatisfactory results. Overall, the simulations with the conventional data resulted in far better results for discharge and soil loss than simulations with CFSR data. The simulations with CFSR data were unable to adequately represent the specific regional climate for the three watersheds, performing even worse in climatic areas with two rainy seasons. Hence, CFSR data should not be used lightly in remote areas with no conventional weather data where no prior analysis is possible.

Processing-dependent and -independent pathways for recognition of iodinated contrast media by specific human T cells

One to three percent of patients exposed to intravenously injected iodinated contrast media (CM) develop delayed hypersensitivity reactions. Positive patch test reactions, immunohistological findings, and CM-specific proliferation of T cells in vitro suggest a pathogenetic role for T cells. We have previously demonstrated that CM-specific T cell clones (TCCs) show a broad range of cross-reactivity to different CM. However, the mechanism of specific CM recognition by T cell receptors (TCRs) has not been analysed so far.

Dynamic computer simulations of electrophoresis: a versatile research and teaching tool

Software is available, which simulates all basic electrophoretic systems, including moving boundary electrophoresis, zone electrophoresis, ITP, IEF and EKC, and their combinations under almost exactly the same conditions used in the laboratory. These dynamic models are based upon equations derived from the transport concepts such as electromigration, diffusion, electroosmosis and imposed hydrodynamic buffer flow that are applied to user-specified initial distributions of analytes and electrolytes. They are able to predict the evolution of electrolyte systems together with associated properties such as pH and conductivity profiles and are as such the most versatile tool to explore the fundamentals of electrokinetic separations and analyses. In addition to revealing the detailed mechanisms of fundamental phenomena that occur in electrophoretic separations, dynamic simulations are useful for educational purposes. This review includes a list of current high-resolution simulators, information on how a simulation is performed, simulation examples for zone electrophoresis, ITP, IEF and EKC and a comprehensive discussion of the applications and achievements.