Importance of vegetation, topography and flow paths for water transit times of base flow in alpine headwater catchments

The mean transit time (MTT) of water in a catchment gives information about storage, flow paths, sources of water and thus also about retention and release of solutes in a catchment. To our knowledge there are only a few catchment studies on the influence of vegetation cover changes on base flow MTTs. The main changes in vegetation cover in the Swiss Alps are massive shrub encroachment and forest expansion into formerly open habitats. Four small and relatively steep headwater catchments in the Swiss Alps (Ursern Valley) were investigated to relate different vegetation cover to water transit times. Time series of water stable isotopes were used to calculate MTTs. The high temporal variation of the stable isotope signals in precipitation was strongly dampened in stream base flow samples. MTTs of the four catchments were 70 to 102 weeks. The strong dampening of the stable isotope input signal as well as stream water geochemistry points to deeper flow paths and mixing of waters of different ages at the catchments' outlets. MTTs were neither related to topographic indices nor vegetation cover. The major part of the quickly infiltrating precipitation likely percolates through fractured and partially karstified deeper rock zones, which increases the control of bedrock flow paths on MTT. Snow accumulation and the timing of its melt play an important role for stable isotope dynamics during spring and early summer. We conclude that, in mountainous headwater catchments with relatively shallow soil layers, the hydrogeological and geochemical patterns (i.e. geochemistry, porosity and hydraulic conductivity of rocks) and snow dynamics influence storage, mixing and release of water in a stronger way than vegetation cover or topography do.

The Life and Times of Bills

Time is one of the scarcest resources in modern parliaments. In parliamentary systems of government the control of time in the chamber is a significant power resource enjoyed – to varying degrees – by parliamentary majorities and the governments they support. Minorities may not be able to muster enough votes to stop bills, but they may have – varying degrees of – delaying powers enabling them to extract concessions from majorities attempting to get on with their overall legislative programme. This paper provides a comparative analysis of the dynamics of the legislative process in 17 West European parliaments from the formal initiation of bills to their promulgation. The ‘biographies’ of a sample of bills are examined using techniques of event-history analysis (a) charting the dynamics of the legislative process both across the life-times of individual bills and different political systems and (b) examining whether, and to what extent, parliamentary rules and some general regime attributes influence the dynamics of this process, speeding up or delaying the passage of legislation. Using a veto-points framework and transaction cost politics as a theoretical framework, the quantitative analyses suggest a number of counter-intuitive findings (e.g., the efficiency of powerful committees) and cast doubt on some of the claims made by Tsebelis in his veto-player model.

Improving a gas ion source for C-14 AMS

For more than 4 years, gaseous samples of 1-50 mu g carbon have been routinely measured with the gas ion source of the small AMS (Accelerator Mass Spectrometer) facility MICADAS (Mini CArbon DAting System) at ETH Zurich. The applied measurement technique offers a simple and fast way of C-14 measurements without the need of sample graphitization. A major drawback of gaseous C-14 measurements, however, is the relatively low negative ion current, which results in longer measurement times and lower precision compared to graphitized samples. In December 2009, a new, improved Cs sputter ion source was installed at MICADAS and we began to optimize conditions for the measurement of gaseous samples. C-12(-) currents from the new ion source were improved from initially 3 to 12-15 mu A for routine measurements and the negative ion yield was increased by a factor of 2, reaching 8 on average during routine operation. Moreover, the new measurement settings enable a doubled CO2 flow, thus substantially reducing measurement times. The achieved performance allows closing the sample size gap between gaseous and solid samples and makes the gas ion source a promising tool for dating with a measurement precision of 5 parts per thousand on samples as small as 50 mu g carbon. (C) 2012 Elsevier B.V. All rights reserved.

SURVIVAL PREDICTION FOR BRAIN TUMOR PATIENTS USING GENE EXPRESSION DATA

Brain tumor is one of the most aggressive types of cancer in humans, with an estimated median survival time of 12 months and only 4% of the patients surviving more than 5 years after disease diagnosis. Until recently, brain tumor prognosis has been based only on clinical information such as tumor grade and patient age, but there are reports indicating that molecular profiling of gliomas can reveal subgroups of patients with distinct survival rates. We hypothesize that coupling molecular profiling of brain tumors with clinical information might improve predictions of patient survival time and, consequently, better guide future treatment decisions. In order to evaluate this hypothesis, the general goal of this research is to build models for survival prediction of glioma patients using DNA molecular profiles (U133 Affymetrix gene expression microarrays) along with clinical information. First, a predictive Random Forest model is built for binary outcomes (i.e. short vs. long-term survival) and a small subset of genes whose expression values can be used to predict survival time is selected. Following, a new statistical methodology is developed for predicting time-to-death outcomes using Bayesian ensemble trees. Due to a large heterogeneity observed within prognostic classes obtained by the Random Forest model, prediction can be improved by relating time-to-death with gene expression profile directly. We propose a Bayesian ensemble model for survival prediction which is appropriate for high-dimensional data such as gene expression data. Our approach is based on the ensemble "sum-of-trees" model which is flexible to incorporate additive and interaction effects between genes. We specify a fully Bayesian hierarchical approach and illustrate our methodology for the CPH, Weibull, and AFT survival models. We overcome the lack of conjugacy using a latent variable formulation to model the covariate effects which decreases computation time for model fitting. Also, our proposed models provides a model-free way to select important predictive prognostic markers based on controlling false discovery rates. We compare the performance of our methods with baseline reference survival methods and apply our methodology to an unpublished data set of brain tumor survival times and gene expression data, selecting genes potentially related to the development of the disease under study. A closing discussion compares results obtained by Random Forest and Bayesian ensemble methods under the biological/clinical perspectives and highlights the statistical advantages and disadvantages of the new methodology in the context of DNA microarray data analysis.

Notch signaling in the brain: in good and bad times.

Notch signaling is an evolutionarily conserved pathway, which is fundamental for neuronal development and specification. In the last decade, increasing evidence has pointed out an important role of this pathway beyond embryonic development, indicating that Notch also displays a critical function in the mature brain of vertebrates and invertebrates. This pathway appears to be involved in neural progenitor regulation, neuronal connectivity, synaptic plasticity and learning/memory. In addition, Notch appears to be aberrantly regulated in neurodegenerative diseases, including Alzheimer's disease and ischemic injury. The molecular mechanisms by which Notch displays these functions in the mature brain are not fully understood, but are currently the subject of intense research. In this review, we will discuss old and novel Notch targets and molecular mediators that contribute to Notch function in the mature brain and will summarize recent findings that explore the two facets of Notch signaling in brain physiology and pathology.