Outcome and Experience from the Swiss Mammography Screening Pilot Programmes

BACKGROUND:The Swiss breast cancer screening pilot programme was conducted in 3 districts of theFrench-speaking canton of Vaud (ca. 300,000 resident women) between October 1993 and January 1999.Women aged 50 to 69 were invited by mail every 2 years for a free of charge screening mammography (doubleview, multiple reading). This first ever-organised cancer screening programme in Switzerland showed thefeasibility and acceptability of this kind of public health intervention in the liberal Swiss healthcare system, whichwas the main objective of the pilot programme. This mammographic screening programme was extended to thewhole canton in 1999, and contributed to the implementation of similar programmes in 2 neighbouring cantons. OBJECTIVE:To appraise the use, the quality and the effectiveness of the Swiss screening pilot programme. METHODS:About 15,000 women (aged 50-69) were enrolled. Logistic regression analyses were performedseparately to identify determinants of initial and subsequent attendance. Standard indicators of quality,effectiveness and impact of the programme were assessed and compared with European recommendations. Tothis intent, linkage with data from the Vaud Cancer Registry was performed. RESULTS:About half the target population was screened at least once during the pilot trial. Participation washigher among Swiss than foreigners, among widowed or married women than among single, divorced or separatedones. Attendance also increased with age and decreasing distance between residence and the dedicatedscreening centre. Apart from Swiss citizenship, socio-demographic factors were not associated with reattendance.Intensity of prior recruitment, outcome of previous screening test (positive vs. negative) and indicators of women'shealth behaviour (time of last mammography prior to initial screen, smoking status) were the main determinants ofreattendance. Programme performance and quality indicators were, overall, in line with European Guidelines. Theywere overall more favourable among 60-69 than 50-59 year-olds and improved over time. CONCLUSION:The objectives of the pilot programme were met. Even if participation should increase in order toreach European standards, performance indicators overall met quality requirements. Ways to improve screeninguse, quality and effectiveness were devised and taken into account for the generalisation of the programme.

In situ evaluation of single-cell lysis by cytosol extraction observation through fluorescence decay and dielectrophoretic trapping time

We present a new method for lysis of single cells in continuous flow, where cells are sequentially trapped, lysed and released in an automatic process. Using optimized frequencies, dielectrophoretic trapping allows exposing cells in a reproducible way to high electrical fields for long durations, thereby giving good control on the lysis parameters. In situ evaluation of cytosol extraction on single cells has been studied for Chinese hamster ovary (CHO) cells through out-diffusion of fluorescent molecules for different voltage amplitudes. A diffusion model is proposed to correlate this out-diffusion to the total area of the created pores, which is dependent on the potential drop across the cell membrane and enables evaluation of the total pore area in the membrane. The dielectrophoretic trapping is no longer effective after lysis because of the reduced conductivity inside the cells, leading to cell release. The trapping time is linked to the time required for cytosol extraction and can thus provide additional validation of the effective cytosol extraction for non-fluorescent cells. Furthermore, the application of one single voltage for both trapping and lysis provides a fully automatic process including cell trapping, lysis, and release, allowing operating the device in continuous flow without human intervention.

Innovation sources and productivity: a quantile regression analysis

This paper explores the effects of two main sources of innovation —intramural and external R&D— on the productivity level in a sample of 3,267 Catalan firms. The data set used is based on the official innovation survey of Catalonia which was a part of the Spanish sample of CIS4, covering the years 2002-2004. We compare empirical results by applying usual OLS and quantile regression techniques both in manufacturing and services industries. In quantile regression, results suggest different patterns at both innovation sources as we move across conditional quantiles. The elasticity of intramural R&D activities on productivity decreased when we move up the high productivity levels both in manufacturing and services sectors, while the effects of external R&D rise in high-technology industries but are more ambiguous in low-technology and services industries.

Factors explaining local privatization: A meta-regression analysis

Privatization of local public services has been implemented worldwide in the last decades. Why local governments privatize has been the subject of much discussion, and many empirical works have been devoted to analyzing the factors that explain local privatization. Such works have found a great diversity of motivations, and the variation among reported empirical results is large. To investigate this diversity we undertake a meta-regression analysis of the factors explaining the decision to privatize local services. Overall, our results indicate that significant relationships are very dependent upon the characteristics of the studies. Indeed, fiscal stress and political considerations have been found to contribute to local privatization specially in the studies of US cases published in the eighties that consider a broad range of services. Studies that focus on one service capture more accurately the influence of scale economies on privatization. Finally, governments of small towns are more affected by fiscal stress, political considerations and economic efficiency, while ideology seems to play a major role for large cities.

Direct binding of peptides to MHC class I molecules on living cells. Analysis at the single cell level.

To directly assess the binding of exogenous peptides to cell surface-associated MHC class I molecules at the single cell level, we examined the possibility of combining the use of biotinylated peptide derivatives with an immunofluorescence detection system based on flow cytometry. Various biotinylated derivatives of the adenovirus 5 early region 1A peptide 234-243, an antigenic peptide recognized by CTL in the context of H-2Db, were first screened in functional assays for their ability to bind efficiently to Db molecules on living cells. Suitable peptide derivatives were then tested for their ability to generate positive fluorescence signals upon addition of phycoerythrin-labeled streptavidin to peptide derivative-bearing cells. Strong fluorescent staining of Db-expressing cells was achieved after incubation with a peptide derivative containing a biotin group at the C-terminus. Competition experiments using the unmodified parental peptide as well as unrelated peptides known to bind to Kd, Kb, or Db, respectively, established that binding of the biotinylated peptide to living cells was Db-specific. By using Con A blasts derived from different H-2 congenic mouse strains, it could be shown that the biotinylated peptide bound only to Db among > 20 class I alleles tested. Moreover, binding of the biotinylated peptide to cells expressing the Dbm13 and Dbm14 mutant molecules was drastically reduced compared to Db. Binding of the biotinylated peptide to freshly isolated Db+ cells was readily detectable, allowing direct assessment of the relative amount of peptide bound to distinct lymphocyte subpopulations by three-color flow cytometry. While minor differences between peripheral T and B cells could be documented, thymocytes were found to differ widely in their peptide binding activity. In all cases, these differences correlated positively with the differential expression of Db at the cell surface. Finally, kinetic studies at different temperatures strongly suggested that the biotinylated peptide first associated with Db molecules available constitutively at the cell surface and then with newly arrived Db molecules.

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.

Responsibility for regional waste generation: A single region extended input-output analysis with uni-directional trade flows

The paper uses a regional input-output (IO) framework and data derived on waste generation by industry to examine regional accountability for waste generation. In addition to estimating a series of industry output-waste coefficients, the paper considers two methods for waste attribution but focuses first on one (trade endogenised linear attribution system (TELAS)) that permits a greater focus on private and public final consumption as the main exogenous driver of waste generation. Second, the paper uses a domestic technology assumption (DTA) to consider a regional ‘waste footprint’ where local consumption requirements are assumed to be met through domestic production.

A Bootstrap Neural Network Based Heterogeneous Panel Unit Root Test: Application to Exchange Rates

This paper proposes a bootstrap artificial neural network based panel unit root test in a dynamic heterogeneous panel context. An application to a panel of bilateral real exchange rate series with the US Dollar from the 20 major OECD countries is provided to investigate the Purchase Power Parity (PPP). The combination of neural network and bootstrapping significantly changes the findings of the economic study in favour of PPP.

Evaluating sampling strategies and logistic regression methods for modelling complex land cover changes

The role of land cover change as a significant component of global change has become increasingly recognized in recent decades. Large databases measuring land cover change, and the data which can potentially be used to explain the observed changes, are also becoming more commonly available. When developing statistical models to investigate observed changes, it is important to be aware that the chosen sampling strategy and modelling techniques can influence results. We present a comparison of three sampling strategies and two forms of grouped logistic regression models (multinomial and ordinal) in the investigation of patterns of successional change after agricultural land abandonment in Switzerland. Results indicated that both ordinal and nominal transitional change occurs in the landscape and that the use of different sampling regimes and modelling techniques as investigative tools yield different results. Synthesis and applications. Our multimodel inference identified successfully a set of consistently selected indicators of land cover change, which can be used to predict further change, including annual average temperature, the number of already overgrown neighbouring areas of land and distance to historically destructive avalanche sites. This allows for more reliable decision making and planning with respect to landscape management. Although both model approaches gave similar results, ordinal regression yielded more parsimonious models that identified the important predictors of land cover change more efficiently. Thus, this approach is favourable where land cover change pattern can be interpreted as an ordinal process. Otherwise, multinomial logistic regression is a viable alternative.

Bayesian Model Averaging in the Instrumental Variable Regression Model

This paper considers the instrumental variable regression model when there is uncertainty about the set of instruments, exogeneity restrictions, the validity of identifying restrictions and the set of exogenous regressors. This uncertainty can result in a huge number of models. To avoid statistical problems associated with standard model selection procedures, we develop a reversible jump Markov chain Monte Carlo algorithm that allows us to do Bayesian model averaging. The algorithm is very exible and can be easily adapted to analyze any of the di¤erent priors that have been proposed in the Bayesian instrumental variables literature. We show how to calculate the probability of any relevant restriction (e.g. the posterior probability that over-identifying restrictions hold) and discuss diagnostic checking using the posterior distribution of discrepancy vectors. We illustrate our methods in a returns-to-schooling application.

The S. pombe cdc16 gene is required both for maintenance of p34cdc2 kinase activity and regulation of septum formation: a link between mitosis and cytokinesis?

In the fission yeast Schizosaccharomyces pombe, septum formation and cytokinesis are dependent upon the initiation, though not the completion of mitosis. A number of cell cycle mutants which show phenotypes consistent with a defect in the regulation of septum formation have been isolated. A mutation in the S. pombe cdc16 gene leads to the formation of multiple septa without cytokinesis, suggesting that the normal mechanisms that limit the cell to the formation of a single septum in each cycle do not operate. Mutations in the S. pombe early septation mutants cdc7, cdc11, cdc14 and cdc15 lead to the formation of elongated, multinucleate cells, as a result of S phase and mitosis continuing in the absence of cytokinesis. This suggests that in these cells, the normal mechanisms which initiate cytokinesis are defective and that they are unable to respond to this by preventing further nuclear cycles. Genetic analysis has implied that the products of some of these genes may interact with that of the cdc16 gene. To understand how the processes of septation and cytokinesis are regulated and coordinated with mitosis we are studying the early septation mutants and cdc16. In this paper, we present the cloning and analysis of the cdc16 gene. Deletion of the gene shows that it is essential for cell proliferation: spores lacking a functional cdc16 gene germinate, complete mitosis and form multiple septa without undergoing cell cleavage.(ABSTRACT TRUNCATED AT 250 WORDS)

Distinct ultrastructural aspects in different biopsies of a single patient with diffuse cutaneous leishmaniasis

The authors investigated the relation between parasites and host-cells in active and regressed lesions of a patient with diffuse cutaneous leishmaniasis, evaluating the frequency of different cell types, and the location and integrity of amastigotes. No correlation was found between parasite integrity and size of parasitophorous vacuoles. They observed ultrastructural findings characterizing a cell mediated immune response: macrophages lysis, parasitic destruction inside macrophages, close contact between parasitized macrophages and lymphocytes and between parasites and lymphocytes, lymphocytic infiltration and fibrosis. They suggest that in DCL there is a limited cellular immune response, although insufficient to control infection.

Model Switching and Model Averaging in Time- Varying Parameter Regression Models

This paper investigates the usefulness of switching Gaussian state space models as a tool for implementing dynamic model selecting (DMS) or averaging (DMA) in time-varying parameter regression models. DMS methods allow for model switching, where a different model can be chosen at each point in time. Thus, they allow for the explanatory variables in the time-varying parameter regression model to change over time. DMA will carry out model averaging in a time-varying manner. We compare our exact approach to DMA/DMS to a popular existing procedure which relies on the use of forgetting factor approximations. In an application, we use DMS to select different predictors in an in ation forecasting application. We also compare different ways of implementing DMA/DMS and investigate whether they lead to similar results.

A Consistent Nonparametric Bootstrap Test of Exogeneity

This paper proposes a novel way of testing exogeneity of an explanatory variable without any parametric assumptions in the presence of a "conditional" instrumental variable. A testable implication is derived that if an explanatory variable is endogenous, the conditional distribution of the outcome given the endogenous variable is not independent of its instrumental variable(s). The test rejects the null hypothesis with probability one if the explanatory variable is endogenous and it detects alternatives converging to the null at a rate n..1=2:We propose a consistent nonparametric bootstrap test to implement this testable implication. We show that the proposed bootstrap test can be asymptotically justi.ed in the sense that it produces asymptotically correct size under the null of exogeneity, and it has unit power asymptotically. Our nonparametric test can be applied to the cases in which the outcome is generated by an additively non-separable structural relation or in which the outcome is discrete, which has not been studied in the literature.