Serum tests, liver stiffness and artificial neural networks for diagnosing cirrhosis and portal hypertension

BACKGROUND The diagnostic performance of biochemical scores and artificial neural network models for portal hypertension and cirrhosis is not well established. AIMS To assess diagnostic accuracy of six serum scores, artificial neural networks and liver stiffness measured by transient elastography, for diagnosing cirrhosis, clinically significant portal hypertension and oesophageal varices. METHODS 202 consecutive compensated patients requiring liver biopsy and hepatic venous pressure gradient measurement were included. Several serum tests (alone and combined into scores) and liver stiffness were measured. Artificial neural networks containing or not liver stiffness as input variable were also created. RESULTS The best non-invasive method for diagnosing cirrhosis, portal hypertension and oesophageal varices was liver stiffness (C-statistics=0.93, 0.94, and 0.90, respectively). Among serum tests/scores the best for diagnosing cirrhosis and portal hypertension and oesophageal varices were, respectively, Fibrosis-4, and Lok score. Artificial neural networks including liver stiffness had high diagnostic performance for cirrhosis, portal hypertension and oesophageal varices (accuracy>80%), but were not statistically superior to liver stiffness alone. CONCLUSIONS Liver stiffness was the best non-invasive method to assess the presence of cirrhosis, portal hypertension and oesophageal varices. The use of artificial neural networks integrating different non-invasive tests did not increase the diagnostic accuracy of liver stiffness alone.

Impact of Taylor-Aris diffusivity on analyte and system zone dispersion in CZE assessed by computer simulation and experimental validation.

Application of pressure-driven laminar flow has an impact on zone and boundary dispersion in open tubular CE. The GENTRANS dynamic simulator for electrophoresis was extended with Taylor-Aris diffusivity which accounts for dispersion due to the parabolic flow profile associated with pressure-driven flow. Effective diffusivity of analyte and system zones as functions of the capillary diameter and the amount of flow in comparison to molecular diffusion alone were studied for configurations with concomitant action of imposed hydrodynamic flow and electroosmosis. For selected examples under realistic experimental conditions, simulation data are compared with those monitored experimentally using modular CE setups featuring both capacitively coupled contactless conductivity and UV absorbance detection along a 50 μm id fused-silica capillary of 90 cm total length. The data presented indicate that inclusion of flow profile based Taylor-Aris diffusivity provides realistic simulation data for analyte and system peaks, particularly those monitored in CE with conductivity detection.

Concentration of organic compounds in slush, under-ice water, and the snow-ice fast-ice cover of the southeast sector of the Antarctic in April 2008

Data are presented on concentration of hydrocarbons (HC) relative to concentrations of suspended matter, lipids, organic carbon, and chlorophyll a in surface waters and snow-ice cover of the East Antarctic coastal areas. It was shown that growth of concentrations of aliphatic HC (AHC) to 30 µg/l in surface waters takes place in frontal zones and under young ice formation. AHC concentration in snow increases with growth of aerosol concentration in the atmosphere. In the lower part of ice, at the boundary with seawater, despite low temperatures, autochthonous processes may provide high AHC concentrations (up to 289 µg/l). Within the snow-ice cover on fast ice, concentration co-variations of all the compounds considered take place.

Over-determined charbonate chemstry dataset from different kinds of manipulation (TA, DIC) and water types (natural and artificial seawater)

The growing field of ocean acidification research is concerned with the investigation of organism responses to increasing pCO2 values. One important approach in this context is culture work using seawater with adjusted CO2 levels. As aqueous pCO2 is difficult to measure directly in small-scale experiments, it is generally calculated from two other measured parameters of the carbonate system (often AT, CT or pH). Unfortunately, the overall uncertainties of measured and subsequently calculated values are often unknown. Especially under high pCO2, this can become a severe problem with respect to the interpretation of physiological and ecological data. In the few datasets from ocean acidification research where all three of these parameters were measured, pCO2 values calculated from AT and CT are typically about 30% lower (i.e. ~300 µatm at a target pCO2 of 1000 µatm) than those calculated from AT and pH or CT and pH. This study presents and discusses these discrepancies as well as likely consequences for the ocean acidification community. Until this problem is solved, one has to consider that calculated parameters of the carbonate system (e.g. pCO2, calcite saturation state) may not be comparable between studies, and that this may have important implications for the interpretation of CO2 perturbation experiments.

Medem Channel profiles based on stand-alone model simulation and corrections with nudging

State-of-the-art process-based models have shown to be applicable to the simulation and prediction of coastal morphodynamics. On annual to decadal temporal scales, these models may show limitations in reproducing complex natural morphological evolution patterns, such as the movement of bars and tidal channels, e.g. the observed decadal migration of the Medem Channel in the Elbe Estuary, German Bight. Here a morphodynamic model is shown to simulate the hydrodynamics and sediment budgets of the domain to some extent, but fails to adequately reproduce the pronounced channel migration, due to the insufficient implementation of bank erosion processes. In order to allow for long-term simulations of the domain, a nudging method has been introduced to update the model-predicted bathymetries with observations. The model-predicted bathymetry is nudged towards true states in annual time steps. Sensitivity analysis of a user-defined correlation length scale, for the definition of the background error covariance matrix during the nudging procedure, suggests that the optimal error correlation length is similar to the grid cell size, here 80-90 m. Additionally, spatially heterogeneous correlation lengths produce more realistic channel depths than do spatially homogeneous correlation lengths. Consecutive application of the nudging method compensates for the (stand-alone) model prediction errors and corrects the channel migration pattern, with a Brier skill score of 0.78. The proposed nudging method in this study serves as an analytical approach to update model predictions towards a predefined 'true' state for the spatiotemporal interpolation of incomplete morphological data in long-term simulations.