Multi-locus microsatellite analysis supports the hypothesis of an autochthonous focus of Echinococcus multilocularis in northern Italy

Echinococcus multilocularis is characterised by a wide geographical distribution, encompassing three continents (North America, Asia and Europe) yet very low genetic variability is documented. Recently, this parasite has been detected in red foxes (Vulpes vulpes) circulating in an Alpine region of Italy, close to Austria. This finding raised the question as to whether an autochthonous cycle exists in Italy or whether the infected foxes originated from the neighbouring regions of Austria. Studies have shown that multi-locus microsatellite analysis can identify genomic regions carrying mutations that result in a local adaptation. We used a tandem repeated multi-locus microsatellite (EmsB) to evaluate the genetic differences amongst adult worms of E. multilocularis collected in Italy, worms from neighbouring Austria and from other European and extra-European countries. Fluorescent PCR was performed on a panel of E. multilocularis samples to assess intra-specific polymorphism. The analysis revealed four closed genotypes for Italian samples of E. multilocularis which were unique compared with the other 25 genotypes from Europe and the five genotypes from Alaska. An analysis in the Alpine watershed, comparing Italian adult worms with those from neighbouring areas in Austria, showed a unique cluster for Italian samples. This result supports the hypothesis of the presence of an autochthonous cycle of E. multilocularis in Italy. EmsB can be useful for 'tracking' the source of infection of this zoonotic parasite and developing appropriate measures for preventing or reducing the risk of human alveolar echinococcosis.

A test of the OPEC cartel hypothesis: 1974-1983

This paper tests whether the higher oil prices fo the last decade could have been the result of producer collusion. We find little evidence that OPEC influenced oil prices during the years of skyrocketing prices (1974-1980), but there is evidence that it did so during the recent years of softening prices (1981-1983).

Do implicit motives and basic psychological needs interact to predict well-being and flow? Testing a universal hypothesis and a matching hypothesis

Self-Determination Theory (Deci and Ryan in Intrinsic motivation and self-determination in human behavior. Plenum Press, New York, 1985) suggests that certain experiences, such as competence, are equally beneficial to everyone’s well-being (universal hypothesis), whereas Motive Disposition Theory (McClelland in Human motivation. Scott, Foresman, Glenview, IL, 1985) predicts that some people, such as those with a high achievement motive, should benefit particularly from such experiences (matching hypothesis). Existing research on motives as moderators of the relationship between basic need satisfaction and positive outcomes supports both these seemingly inconsistent views. Focusing on the achievement motive, we sought to resolve this inconsistency by considering the specificity of the outcome variables. When predicting domain-specific well-being and flow, the achievement motive should interact with felt competence. However, when it comes to predicting general well-being and flow, felt competence should unfold its effects without being moderated by the achievement motive. Two studies confirmed these assumptions indicating that the universal and matching hypotheses are complementary rather than mutually exclusive.

In vitro precision of fit of computer-aided designed and computer-aided manufactured titanium screw-retained fixed dental prostheses before and after ceramic veneering

OBJECTIVE To compare the precision of fit of full-arch implant-supported screw-retained computer-aided designed and computer-aided manufactured (CAD/CAM) titanium-fixed dental prostheses (FDP) before and after veneering. The null-hypothesis was that there is no difference in vertical microgap values between pure titanium frameworks and FDPs after porcelain firing. MATERIALS AND METHODS Five CAD/CAM titanium grade IV frameworks for a screw-retained 10-unit implant-supported reconstruction on six implants (FDI tooth positions 15, 13, 11, 21, 23, 25) were fabricated after digitizing the implant platforms and the cuspid-supporting framework resin pattern with a laser scanner (CARES(®) Scan CS2; Institut Straumann AG, Basel, Switzerland). A bonder, an opaquer, three layers of porcelain, and one layer of glaze were applied (Vita Titankeramik) and fired according to the manufacturer's preheating and fire cycle instructions at 400-800°C. The one-screw test (implant 25 screw-retained) was applied before and after veneering of the FDPs to assess the vertical microgap between implant and framework platform with a scanning electron microscope. The mean microgap was calculated from interproximal and buccal values. Statistical comparison was performed with non-parametric tests. RESULTS All vertical microgaps were clinically acceptable with values <90 μm. No statistically significant pairwise difference (P = 0.98) was observed between the relative effects of vertical microgap of unveneered (median 19 μm; 95% CI 13-35 μm) and veneered FDPs (20 μm; 13-31 μm), providing support for the null-hypothesis. Analysis within the groups showed significantly different values between the five implants of the FDPs before (P = 0.044) and after veneering (P = 0.020), while a monotonous trend of increasing values from implant 23 (closest position to screw-retained implant 25) to 15 (most distant implant) could not be observed (P = 0.169, P = 0.270). CONCLUSIONS Full-arch CAD/CAM titanium screw-retained frameworks have a high accuracy. Porcelain firing procedure had no impact on the precision of fit of the final FDPs. All implant microgap measurements of each FDP showed clinically acceptable vertical misfit values before and after veneering. Thus, the results do not only show accurate performance of the milling and firing but show also a reproducible scanning and designing process.

Political Efficacy and Voter Turnouts in East and West Germany

This article asks if voters' participation in federal elections is lower in the new Länder (East Germany) than in the old Länder (West Germany). It is assumed that voters in the new Länder are less convinced they can influence politics by voting. Using the perspective of cognitive psychology the article stresses differences in individual interpretations of the election context among citizens of both the new and old Länder. Furthermore, it is argued that the strength of the expected influence by voting depends on the structure and direction of individuals' beliefs in their competence and control as well as their belief in causality and self-efficacy. These beliefs may differ among voters in the new and old Länder. For empirical analysis, the article uses data from the German General Social Survey 1998.

Voter Participation in the 1998 Bundestag Elections: A Theoretical Modification and Empirical Application of Downs’ Theory of Voter Participation

This article seeks to contribute to the illumination of the so-called 'paradox of voting' using the German Bundestag elections of 1998 as an empirical case. Downs' model of voter participation will be extended to include elements of the theory of subjective expected utility (SEU). This will allow a theoretical and empirical exploration of the crucial mechanisms of individual voters' decisions to participate, or abstain from voting, in the German general election of 1998. It will be argued that the infinitely low probability of an individual citizen's vote to decide the election outcome will not necessarily reduce the probability of electoral participation. The empirical analysis is largely based on data from the ALLBUS 1998. It confirms the predictions derived from SEU theory. The voters' expected benefits and their subjective expectation to be able to influence government policy by voting are the crucial mechanisms to explain participation. By contrast, the explanatory contribution of perceived information and opportunity costs is low.

Assessment of the wind-up phenomenon in the equine nociceptive trigeminal system.

Repeated sub-threshold nociceptive electrical stimulation resulting in temporal summation of the limb nociceptive withdrawal reflex is a well-established non-invasive model to investigate the wind-up phenomenon in horses. Due to structural similarities of the trigeminal sensory nucleus to the dorsal horn of the spinal cord, temporal summation should be evoked by repeated transcutaneous electrical stimulation of trigeminal afferents. To evaluate this hypothesis repeated transcutaneous electrical stimulation was applied to the supraorbital and infraorbital nerves of 10 horses. Stimulation intensities varied between 0.5 and 1.3 times the trigemino-cervical reflex threshold defined for single stimulation. Evoked electromyographic activity of the orbicularis oculi, splenius and cleidomastoideus muscles was recorded and the signals analysed in the previously established epochs typical to the early and late component of the blink reflex and to the trigemino-cervical reflex. Behavioural reactions were evaluated with the aid of numerical rating scale. The nociceptive late component and the trigemino-cervical reflex were not elicited by sub-threshold intensity repeated transcutaneous electrical stimulation. Furthermore, the median reflex amplitude for the 10 horses showed a tendency to decline over the stimulation train so temporal summation of afferent trigeminal inputs could not be observed. Therefore, the modulation of trigeminal nociceptive processing attributable to repeated Aδ fibre stimulations seems to differ from spinal processing of similar inputs as it seems to have an inhibitory rather than facilitatory effect. Further evaluation is necessary to highlight the underlying mechanism.

Exemestane Versus Anastrozole in Postmenopausal Women With Early Breast Cancer: NCIC CTG MA.27—A Randomized Controlled Phase III Trial

PURPOSE In patients with hormone-dependent postmenopausal breast cancer, standard adjuvant therapy involves 5 years of the nonsteroidal aromatase inhibitors anastrozole and letrozole. The steroidal inhibitor exemestane is partially non-cross-resistant with nonsteroidal aromatase inhibitors and is a mild androgen and could prove superior to anastrozole regarding efficacy and toxicity, specifically with less bone loss. PATIENTS AND METHODS We designed an open-label, randomized, phase III trial of 5 years of exemestane versus anastrozole with a two-sided test of superiority to detect a 2.4% improvement with exemestane in 5-year event-free survival (EFS). Secondary objectives included assessment of overall survival, distant disease-free survival, incidence of contralateral new primary breast cancer, and safety. RESULTS In the study, 7,576 women (median age, 64.1 years) were enrolled. At median follow-up of 4.1 years, 4-year EFS was 91% for exemestane and 91.2% for anastrozole (stratified hazard ratio, 1.02; 95% CI, 0.87 to 1.18; P = .85). Overall, distant disease-free survival and disease-specific survival were also similar. In all, 31.6% of patients discontinued treatment as a result of adverse effects, concomitant disease, or study refusal. Osteoporosis/osteopenia, hypertriglyceridemia, vaginal bleeding, and hypercholesterolemia were less frequent on exemestane, whereas mild liver function abnormalities and rare episodes of atrial fibrillation were less frequent on anastrozole. Vasomotor and musculoskeletal symptoms were similar between arms. CONCLUSION This first comparison of steroidal and nonsteroidal classes of aromatase inhibitors showed neither to be superior in terms of breast cancer outcomes as 5-year initial adjuvant therapy for postmenopausal breast cancer by two-way test. Less toxicity on bone is compatible with one hypothesis behind MA.27 but requires confirmation. Exemestane should be considered another option as up-front adjuvant therapy for postmenopausal hormone receptor-positive breast cancer.

A BAYESIAN APPROACH TO DOSE-RESPONSE ASSESSMENT AND DRUG-DRUG INTERACTION ANALYSIS: APPLICATION TO IN VITRO STUDIES

The considerable search for synergistic agents in cancer research is motivated by the therapeutic benefits achieved by combining anti-cancer agents. Synergistic agents make it possible to reduce dosage while maintaining or enhancing a desired effect. Other favorable outcomes of synergistic agents include reduction in toxicity and minimizing or delaying drug resistance. Dose-response assessment and drug-drug interaction analysis play an important part in the drug discovery process, however analysis are often poorly done. This dissertation is an effort to notably improve dose-response assessment and drug-drug interaction analysis. The most commonly used method in published analysis is the Median-Effect Principle/Combination Index method (Chou and Talalay, 1984). The Median-Effect Principle/Combination Index method leads to inefficiency by ignoring important sources of variation inherent in dose-response data and discarding data points that do not fit the Median-Effect Principle. Previous work has shown that the conventional method yields a high rate of false positives (Boik, Boik, Newman, 2008; Hennessey, Rosner, Bast, Chen, 2010) and, in some cases, low power to detect synergy. There is a great need for improving the current methodology. We developed a Bayesian framework for dose-response modeling and drug-drug interaction analysis. First, we developed a hierarchical meta-regression dose-response model that accounts for various sources of variation and uncertainty and allows one to incorporate knowledge from prior studies into the current analysis, thus offering a more efficient and reliable inference. Second, in the case that parametric dose-response models do not fit the data, we developed a practical and flexible nonparametric regression method for meta-analysis of independently repeated dose-response experiments. Third, and lastly, we developed a method, based on Loewe additivity that allows one to quantitatively assess interaction between two agents combined at a fixed dose ratio. The proposed method makes a comprehensive and honest account of uncertainty within drug interaction assessment. Extensive simulation studies show that the novel methodology improves the screening process of effective/synergistic agents and reduces the incidence of type I error. We consider an ovarian cancer cell line study that investigates the combined effect of DNA methylation inhibitors and histone deacetylation inhibitors in human ovarian cancer cell lines. The hypothesis is that the combination of DNA methylation inhibitors and histone deacetylation inhibitors will enhance antiproliferative activity in human ovarian cancer cell lines compared to treatment with each inhibitor alone. By applying the proposed Bayesian methodology, in vitro synergy was declared for DNA methylation inhibitor, 5-AZA-2'-deoxycytidine combined with one histone deacetylation inhibitor, suberoylanilide hydroxamic acid or trichostatin A in the cell lines HEY and SKOV3. This suggests potential new epigenetic therapies in cell growth inhibition of ovarian cancer cells.

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.