Choline-PET in prostate cancer management: The point of view of the radiation oncologist.

Among PET radiotracers, FDG seems to be quite accepted as an accurate oncology diagnostic tool, frequently helpful also in the evaluation of treatment response and in radiation therapy treatment planning for several cancer sites. To the contrary, the reliability of Choline as a tracer for prostate cancer (PC) still remains an object of debate for clinicians, including radiation oncologists. This review focuses on the available data about the potential impact of Choline-PET in the daily clinical practice of radiation oncologists managing PC patients. In summary, routine Choline-PET is not indicated for initial local T staging, but it seems better than conventional imaging for nodal staging and for all patients with suspected metastases. In these settings, Choline-PET showed the potential to change patient management. A critical limit remains spatial resolution, limiting the accuracy and reliability for small lesions. After a PSA rise, the problem of the trigger PSA value remains crucial. Indeed, the overall detection rate of Choline-PET is significantly increased when the trigger PSA, or the doubling time, increases, but higher PSA levels are often a sign of metastatic spread, a contraindication for potentially curable local treatments such as radiation therapy. Even if several published data seem to be promising, the current role of PET in treatment planning in PC patients to be irradiated still remains under investigation. Based on available literature data, all these issues are addressed and discussed in this review.

Multifractal portrayal of the Swiss population

Fractal geometry is a fundamental approach for describing the complex irregularities of the spatial structure of point patterns. The present research characterizes the spatial structure of the Swiss population distribution in the three Swiss geographical regions (Alps, Plateau and Jura) and at the entire country level. These analyses were carried out using fractal and multifractal measures for point patterns, which enabled the estimation of the spatial degree of clustering of a distribution at different scales. The Swiss population dataset is presented on a grid of points and thus it can be modelled as a "point process" where each point is characterized by its spatial location (geometrical support) and a number of inhabitants (measured variable). The fractal characterization was performed by means of the box-counting dimension and the multifractal analysis was conducted through the Renyi's generalized dimensions and the multifractal spectrum. Results showed that the four population patterns are all multifractals and present different clustering behaviours. Applying multifractal and fractal methods at different geographical regions and at different scales allowed us to quantify and describe the dissimilarities between the four structures and their underlying processes. This paper is the first Swiss geodemographic study applying multifractal methods using high resolution data.

Wound infection after excision and primary midline closure for pilonidal disease: risk factor analysis to improve patient selection.

BACKGROUND: Excision and primary midline closure for pilonidal disease (PD) is a simple procedure; however, it is frequently complicated by infection and prolonged healing. The aim of this study was to analyze risk factors for surgical site infection (SSI) in this context. METHODS: All consecutive patients undergoing excision and primary closure for PD from January 2002 through October 2008 were retrospectively assessed. The end points were SSI, as defined by the Center for Disease Control, and time to healing. Univariable and multivariable risk factor analyses were performed. RESULTS: One hundred thirty-one patients were included [97 men (74%), median age = 24 (range 15-66) years]. SSI occurred in 41 (31%) patients. Median time to healing was 20 days (range 12-76) in patients without SSI and 62 days (range 20-176) in patients with SSI (P < 0.0001). In univariable and multivariable analyses, smoking [OR = 2.6 (95% CI 1.02, 6.8), P = 0.046] and lack of antibiotic prophylaxis [OR = 5.6 (95% CI 2.5, 14.3), P = 0.001] were significant predictors for SSI. Adjusted for SSI, age over 25 was a significant predictor of prolonged healing. CONCLUSION: This study suggests that the rate of SSI after excision and primary closure of PD is higher in smokers and could be reduced by antibiotic prophylaxis. SSI significantly prolongs healing time, particularly in patients over 25 years.

Routine use of point-of-care tests: usefulness and application in clinical microbiology.

Point-of-care (POC) tests offer potentially substantial benefits for the management of infectious diseases, mainly by shortening the time to result and by making the test available at the bedside or at remote care centres. Commercial POC tests are already widely available for the diagnosis of bacterial and viral infections and for parasitic diseases, including malaria. Infectious diseases specialists and clinical microbiologists should be aware of the indications and limitations of each rapid test, so that they can use them appropriately and correctly interpret their results. The clinical applications and performance of the most relevant and commonly used POC tests are reviewed. Some of these tests exhibit insufficient sensitivity, and should therefore be coupled to confirmatory tests when the results are negative (e.g. Streptococcus pyogenes rapid antigen detection test), whereas the results of others need to be confirmed when positive (e.g. malaria). New molecular-based tests exhibit better sensitivity and specificity than former immunochromatographic assays (e.g. Streptococcus agalactiae detection). In the coming years, further evolution of POC tests may lead to new diagnostic approaches, such as panel testing, targeting not just a single pathogen, but all possible agents suspected in a specific clinical setting. To reach this goal, the development of serology-based and/or molecular-based microarrays/multiplexed tests will be needed. The availability of modern technology and new microfluidic devices will provide clinical microbiologists with the opportunity to be back at the bedside, proposing a large variety of POC tests that will allow quicker diagnosis and improved patient care.

Selection of patients with germline MLH1 mutated Lynch syndrome by determination of MLH1 methylation and BRAF mutation.

Lynch syndrome is one of the most common hereditary colorectal cancer (CRC) syndrome and is caused by germline mutations of MLH1, MSH2 and more rarely MSH6, PMS2, MLH3 genes. Whereas the absence of MSH2 protein is predictive of Lynch syndrome, it is not the case for the absence of MLH1 protein. The purpose of this study was to develop a sensitive and cost effective algorithm to select Lynch syndrome cases among patients with MLH1 immunohistochemical silencing. Eleven sporadic CRC and 16 Lynch syndrome cases with MLH1 protein abnormalities were selected. The BRAF c.1799T> A mutation (p.Val600Glu) was analyzed by direct sequencing after PCR amplification of exon 15. Methylation of MLH1 promoter was determined by Methylation-Sensitive Single-Strand Conformation Analysis. In patients with Lynch syndrome, there was no BRAF mutation and only one case showed MLH1 methylation (6%). In sporadic CRC, all cases were MLH1 methylated (100%) and 8 out of 11 cases carried the above BRAF mutation (73%) whereas only 3 cases were BRAF wild type (27%). We propose the following algorithm: (1) no further molecular analysis should be performed for CRC exhibiting MLH1 methylation and BRAF mutation, and these cases should be considered as sporadic CRC; (2) CRC with unmethylated MLH1 and negative for BRAF mutation should be considered as Lynch syndrome; and (3) only a small fraction of CRC with MLH1 promoter methylation but negative for BRAF mutation should be true Lynch syndrome patients. These potentially Lynch syndrome patients should be offered genetic counselling before searching for MLH1 gene mutations.

Labour Market Imperfections, International Integration and Selection

Although a large body of literature has focused on the effects of intra-firm differences on export performance, relatively little attention has been devoted to the interaction between firms' selection and international performance and labour market institutions - in contrast with the centrality of the latter to current policy and public debates on the implications of economic globalisation for national policies and institutions. In this paper, we study the effects of labour market unionisation on the process of competitive selection between heterogeneous firms and analyse how the interaction between the two is affected by trade liberalisation between countries with different unionisation patterns.

Pervasive positive selection on duplicated and nonduplicated vertebrate protein coding genes.

A stringent branch-site codon model was used to detect positive selection in vertebrate evolution. We show that the test is robust to the large evolutionary distances involved. Positive selection was detected in 77% of 884 genes studied. Most positive selection concerns a few sites on a single branch of the phylogenetic tree: Between 0.9% and 4.7% of sites are affected by positive selection depending on the branches. No functional category was overrepresented among genes under positive selection. Surprisingly, whole genome duplication had no effect on the prevalence of positive selection, whether the fish-specific genome duplication or the two rounds at the origin of vertebrates. Thus positive selection has not been limited to a few gene classes, or to specific evolutionary events such as duplication, but has been pervasive during vertebrate evolution.

Indicadors de l'estructura sòcio-afectiva en el rendiment dels esports col·lectius

The present work carries out an analysis about which elements of the socioaffective structure take more importance for different male team sports coaches. Data obtaining carries out by using a survey applied directly by interview. In the first part, the interviewed coaches were asked to point out the indicators of the stated structure they considered more important, using a previous selection. In the second part, using a qualitative technique, the interviewed coaches were asked to explain own strategies to work, to control or to evaluate the indicators they pointed out as important in the first part. Analysis show that most of the coaches gave great importance to this structure (80% of the values are over 4 points on a top 5 points scale), and all of them had their own strategies to deal with the structure in their sports.

Stochastic Search Variable Selection in Vector Error Correction Models with an Application to a Model of the UK Macroeconomy

This paper develops methods for Stochastic Search Variable Selection (currently popular with regression and Vector Autoregressive models) for Vector Error Correction models where there are many possible restrictions on the cointegration space. We show how this allows the researcher to begin with a single unrestricted model and either do model selection or model averaging in an automatic and computationally efficient manner. We apply our methods to a large UK macroeconomic model.

What Belongs Where? Variable Selection for Zero-Inflated Count Models with an Application to the Demand for Health Care

This paper develops stochastic search variable selection (SSVS) for zero-inflated count models which are commonly used in health economics. This allows for either model averaging or model selection in situations with many potential regressors. The proposed techniques are applied to a data set from Germany considering the demand for health care. A package for the free statistical software environment R is provided.

The regional electricity generation mix in Scotland: A portfolio selection approach

Standalone levelised cost assessments of electricity supply options miss an important contribution that renewable and non-fossil fuel technologies can make to the electricity portfolio: that of reducing the variability of electricity costs, and their potentially damaging impact upon economic activity. Portfolio theory applications to the electricity generation mix have shown that renewable technologies, their costs being largely uncorrelated with non-renewable technologies, can offer such benefits. We look at the existing Scottish generation mix and examine drivers of changes out to 2020. We assess recent scenarios for the Scottish generation mix in 2020 against mean-variance efficient portfolios of electricity-generating technologies. Each of the scenarios studied implies a portfolio cost of electricity that is between 22% and 38% higher than the portfolio cost of electricity in 2007. These scenarios prove to be “inefficient” in the sense that, for example, lower variance portfolios can be obtained without increasing portfolio costs, typically by expanding the share of renewables. As part of extensive sensitivity analysis, we find that Wave and Tidal technologies can contribute to lower risk electricity portfolios, while not increasing portfolio cost.

Forecasting with Medium and Large Bayesian VARs

This paper is motivated by the recent interest in the use of Bayesian VARs for forecasting, even in cases where the number of dependent variables is large. In such cases, factor methods have been traditionally used but recent work using a particular prior suggests that Bayesian VAR methods can forecast better. In this paper, we consider a range of alternative priors which have been used with small VARs, discuss the issues which arise when they are used with medium and large VARs and examine their forecast performance using a US macroeconomic data set containing 168 variables. We nd that Bayesian VARs do tend to forecast better than factor methods and provide an extensive comparison of the strengths and weaknesses of various approaches. Our empirical results show the importance of using forecast metrics which use the entire predictive density, instead of using only point forecasts.

Baysian Model Averaging, Learning and Model Selection

Agents have two forecasting models, one consistent with the unique rational expectations equilibrium, another that assumes a time-varying parameter structure. When agents use Bayesian updating to choose between models in a self-referential system, we find that learning dynamics lead to selection of one of the two models. However, there are parameter regions for which the non-rational forecasting model is selected in the long-run. A key structural parameter governing outcomes measures the degree of expectations feedback in Muth's model of price determination.