Dealing with bad guys: actor- and process-level determinants of the “devil shift” in policy making

Policy actors tend to misinterpret and distrust opponents in policy processes. This phenomenon, known as the “devil shift”, consists of the following two dimensions: actors perceive opponents as more powerful and as more evil than they really are. Analysing nine policy processes in Switzerland, this article highlights the drivers of the devil shift at two levels. On the actor level, interest groups, political parties and powerful actors suffer more from the devil shift than state actors and powerless actors. On the process level, the devil shift is stronger in policy processes dealing with socio-economic issues as compared with other issues. Finally, and in line with previous studies, there is less empirical evidence of the power dimension of the devil shift phenomenon than of its evilness dimension.

Regulation of the Telecommunications in Switzerland: A Network Approach to Assess the Regulatory Agencies' Independence

The liberalization process of the Swiss telecommunications sector follows a logic of ‘autonomous adaptation’ to the regulations of the European Union (EU). Switzerland, which is not a Member State of the EU, voluntarily adapts to the European policy without being for- mally required to do so (Sciarini et al., 2004). This process went hand in hand with the partial privatization of the legal statute and assets of the former monopolist and with the re-regulation of the liberalized telecommunications sector.

Chronic stress accelerates pancreatic cancer growth and invasion: A critical role for beta-adrenergic signaling in the pancreatic microenvironment

Pancreatic cancer cells intimately interact with a complex microenvironment that influences pancreatic cancer progression. The pancreas is innervated by fibers of the sympathetic nervous system (SNS) and pancreatic cancer cells have receptors for SNS neurotransmitters which suggests that pancreatic cancer may be sensitive to neural signaling. In vitro and non-orthotopic in vivo studies showed that neural signaling modulates tumour cell behavior. However the effect of SNS signaling on tumor progression within the pancreatic microenvironment has not previously been investigated. To address this, we used in vivo optical imaging to non-invasively track growth and dissemination of primary pancreatic cancer using an orthotopic mouse model that replicates the complex interaction between pancreatic tumor cells and their microenvironment. Stress-induced neural activation increased primary tumor growth and tumor cell dissemination to normal adjacent pancreas. These effects were associated with increased expression of invasion genes by tumor cells and pancreatic stromal cells. Pharmacological activation of β-adrenergic signaling induced similar effects to chronic stress, and pharmacological β-blockade reversed the effects of chronic stress on pancreatic cancer progression. These findings indicate that neural β-adrenergic signaling regulates pancreatic cancer progression and suggest β-blockade as a novel strategy to complement existing therapies for pancreatic cancer

Biological variation of established and novel biomarkers for atherosclerosis: Results from a prospective, parallel-group cohort study.

BACKGROUND Biomarkers are a promising tool for the management of patients with atherosclerosis, but their variation is largely unknown. We assessed within-subject and between-subject biological variation of biomarkers in peripheral artery disease (PAD) patients and healthy controls, and defined which biomarkers have a favorable variation profile for future studies. METHODS Prospective, parallel-group cohort study, including 62 patients with stable PAD (79% men, 65±7years) and 18 healthy control subjects (44% men, 57±7years). Blood samples were taken at baseline, and after 3-, 6-, and 12-months. We calculated within-subject (CVI) and between-subject (CVG) coefficients of variation and intra-class correlation coefficient (ICC). RESULTS Mean levels of D-dimer, hs-CRP, IL-6, IL-8, MMP-9, MMP-3, S100A8/A9, PAI-1, sICAM-1, and sP-selectin levels were higher in PAD patients than in healthy controls (P≤.05 for all). CVI and CVG of the different biomarkers varied considerably in both groups. An ICC≥0.5 (indicating moderate-to-good reliability) was found for hs-CRP, D-Dimer, E-selectin, IL-10, MCP-1, MMP-3, oxLDL, sICAM-1 and sP-selectin in both groups, for sVCAM in healthy controls and for MMP-9, PAI-1 and sCD40L in PAD patients. CONCLUSIONS Single biomarker measurements are of limited utility due to large within-subject variation, both in PAD patients and healthy subjects. D-dimer, hs-CRP, MMP-9, MMP-3, PAI-1, sP-selectin and sICAM-1 are biomarkers with both higher mean levels in PAD patients and a favorable variation profile making them most suitable for future studies.

Extensive Copy-Number Variation of Young Genes across Stickleback Populations

Duplicate genes emerge as copy-number variations (CNVs) at the population level, and remain copy-number polymorphic until they are fixed or lost. The successful establishment of such structural polymorphisms in the genome plays an important role in evolution by promoting genetic diversity, complexity and innovation. To characterize the early evolutionary stages of duplicate genes and their potential adaptive benefits, we combine comparative genomics with population genomics analyses to evaluate the distribution and impact of CNVs across natural populations of an eco-genomic model, the three-spined stickleback. With whole genome sequences of 66 individuals from populations inhabiting three distinct habitats, we find that CNVs generally occur at low frequencies and are often only found in one of the 11 populations surveyed. A subset of CNVs, however, displays copy-number differentiation between populations, showing elevated within-population frequencies consistent with local adaptation. By comparing teleost genomes to identify lineage-specific genes and duplications in sticklebacks, we highlight rampant gene content differences among individuals in which over 30% of young duplicate genes are CNVs. These CNV genes are evolving rapidly at the molecular level and are enriched with functional categories associated with environmental interactions, depicting the dynamic early copy-number polymorphic stage of genes during population differentiation.

Genomics of Divergence along a Continuum of Parapatric Population Differentiation

The patterns of genomic divergence during ecological speciation are shaped by a combination of evolutionary forces. Processes such as genetic drift, local reduction of gene flow around genes causing reproductive isolation, hitchhiking around selected variants, variation in recombination and mutation rates are all factors that can contribute to the heterogeneity of genomic divergence. On the basis of 60 fully sequenced three-spined stickleback genomes, we explore these different mechanisms explaining the heterogeneity of genomic divergence across five parapatric lake and river population pairs varying in their degree of genetic differentiation. We find that divergent regions of the genome are mostly specific for each population pair, while their size and abundance are not correlated with the extent of genome-wide population differentiation. In each pair-wise comparison, an analysis of allele frequency spectra reveals that 25–55% of the divergent regions are consistent with a local restriction of gene flow. Another large proportion of divergent regions (38–75%) appears to be mainly shaped by hitchhiking effects around positively selected variants. We provide empirical evidence that alternative mechanisms determining the evolution of genomic patterns of divergence are not mutually exclusive, but rather act in concert to shape the genome during population differentiation, a first necessary step towards ecological speciation.

Un modèle animal simple pour l'apprentissage des techniques de microanastomoses vasculaires de congruences diefférentes

BACKGROUND Since the pioneering work of Jacobson and Suarez, microsurgery has steadily progressed and is now used in all surgical specialities, particularly in plastic surgery. Before performing clinical procedures it is necessary to learn the basic techniques in the laboratory. OBJECTIVE To assess an animal model, thereby circumventing the following issues: ethical rules, cost, anesthesia and training time. METHODS Between July 2012 and September 2012, 182 earthworms were used for 150 microsurgical trainings to simulate discrepancy microanastomoses. Training was undertaken over 10 weekly periods. Each training session included 15 simulations of microanastomoses performed using the Harashina technique (earthworm diameters >1.5 mm [n=5], between 1.0 mm and 1.5 mm [n=5], and <1.0 mm [n=5]). The technique is presented and documented. A linear model with main variable as the number of the week (as a numeric covariate) and the size of the animal (as a factor) was used to determine the trend in time of anastomosis over subsequent weeks as well as differences between the different size groups. RESULTS The linear model showed a significant trend (P<0.001) in time of anastomosis in the course of the training, as well as significant differences (P<0.001) between the groups of animal of different sizes. For diameter >1.5 mm, mean anastomosis time decreased from 19.6±1.9 min to 12.6±0.7 min between the first and last week of training. For training involving smaller diameters, the results showed a reduction in execution time of 36.1% (P<0.01) (diameter between 1.0 mm and 1.5 mm) and 40.6% (P<0.01) (diameter <1.0 mm) between the first and last weeks. The study demonstrates an improvement in the dexterity and speed of nodes' execution. CONCLUSION The earthworm appears to be a reliable experimental model for microsurgical training of discrepancy microanastomoses. Its numerous advantages, as discussed in the present report, show that this model of training will significantly grow and develop in the near future.

Chow–Liu trees are sufficient predictive models for reproducing key features of functional networks of periictal EEG time-series

Seizure freedom in patients suffering from pharmacoresistant epilepsies is still not achieved in 20–30% of all cases. Hence, current therapies need to be improved, based on a more complete understanding of ictogenesis. In this respect, the analysis of functional networks derived from intracranial electroencephalographic (iEEG) data has recently become a standard tool. Functional networks however are purely descriptive models and thus are conceptually unable to predict fundamental features of iEEG time-series, e.g., in the context of therapeutical brain stimulation. In this paper we present some first steps towards overcoming the limitations of functional network analysis, by showing that its results are implied by a simple predictive model of time-sliced iEEG time-series. More specifically, we learn distinct graphical models (so called Chow–Liu (CL) trees) as models for the spatial dependencies between iEEG signals. Bayesian inference is then applied to the CL trees, allowing for an analytic derivation/prediction of functional networks, based on thresholding of the absolute value Pearson correlation coefficient (CC) matrix. Using various measures, the thus obtained networks are then compared to those which were derived in the classical way from the empirical CC-matrix. In the high threshold limit we find (a) an excellent agreement between the two networks and (b) key features of periictal networks as they have previously been reported in the literature. Apart from functional networks, both matrices are also compared element-wise, showing that the CL approach leads to a sparse representation, by setting small correlations to values close to zero while preserving the larger ones. Overall, this paper shows the validity of CL-trees as simple, spatially predictive models for periictal iEEG data. Moreover, we suggest straightforward generalizations of the CL-approach for modeling also the temporal features of iEEG signals.

Provenance analysis using Raman spectroscopy of carbonaceous material: A case study in the Southern Alps of New Zealand

Detrital provenance analyses in orogenic settings, in which sediments are collected at the outlet of a catchment, have become an important tool to estimate how erosion varies in space and time. Here we present how Raman Spectroscopy on Carbonaceous Material (RSCM) can be used for provenance analysis. RSCM provides an estimate of the peak temperature (RSCM-T) experienced during metamorphism. We show that we can infer modern erosion patterns in a catchment by combining new measurements on detrital sands with previously acquired bedrock data. We focus on the Whataroa catchment in the Southern Alps of New Zealand and exploit the metamorphic gradient that runs parallel to the main drainage direction. To account for potential sampling biases, we also quantify abrasion properties using flume experiments and measure the total organic carbon content in the bedrock that produced the collected sands. Finally, we integrate these parameters into a mass-conservative model. Our results first demonstrate that RSCM-T can be used for detrital studies. Second, we find that spatial variations in tracer concentration and erosion have a first-order control on the RSCM-T distributions, even though our flume experiments reveal that weak lithologies produce substantially more fine particles than do more durable lithologies. This result implies that sand specimens are good proxies for mapping spatial variations in erosion when the bedrock concentration of the target mineral is quantified. The modeling suggests that highest present-day erosion rates (in Whataroa catchment) are not situated at the range front but around 10 km into the mountain belt.

Benign vs malignant inferolateral early repolarization: Focus on the T wave.

BACKGROUND Inferolateral early repolarization (ER) is highly prevalent and is associated with idiopathic ventricular fibrillation (VF). OBJECTIVE The purpose of this study was to evaluate the potential role of T-wave parameters to differentiate between malignant and benign ER. METHODS We compared the ECGs of patients with ER and VF (n = 92) with control subjects with asymptomatic ER (n = 247). We assessed J-wave amplitude, QTc interval, T-wave/R-wave (T/R) ratio in leads II and V5, and presence of low-amplitude T waves (T-wave amplitude <0.1 mV and <10% of R-wave amplitude in lead I, II, or V4-V6). RESULTS Compared to controls, the VF group had longer QTc intervals (388 ms vs 377 ms, P = .001), higher J-wave amplitudes (0.23 mV vs 0.17 mV, P <.001), higher prevalence of low-amplitude T waves (29% vs 3%, P <.001), and lower T/R ratio (0.18 vs 0.30, P <.001). Logistic regression analysis demonstrated that QTc interval (odds ratio [OR] per 10 ms: 1.15, 95% confidence interval [CI} 1.02-1.30), maximal J-wave amplitude (OR per 0.1 mV: 1.68, 95% CI 1.23-2.31), lower T/R ratio (OR per 0.1 unit: 0.62, 95% CI 0.47-0.81), presence of low-amplitude T waves (OR 3.53, 95% CI 1.26-9.88). and presence of J waves in the inferior leads (OR 2.58, 95% CI 1.18-5.65) were associated with malignant ER. CONCLUSION Patients with malignant ER have a higher prevalence of low-amplitude T waves, lower T/R ratio (lead II or V5), and longer QTc interval. The combination of these parameters with J-wave amplitude and distribution of J waves may allow for improved identification of malignant ER.