Topics in public finance: social security and taxation

Summary The field of public finance focuses on the spending and taxing activities of governments and their influence on the allocation of resources and distribution of income. This work covers in three parts different topics related to public finance which are currently widely discussed in media and politics. The first two parts deal with issues on social security, which is in general one of the biggest spending shares of governments. The third part looks at the main income source of governments by analyzing the perceived value of tax competition. Part one deals with the current problem of increased early retirement by focusing on Switzerland as a special case. Early retirement is predominantly considered to be the result of incentives set by social security and the tax system. But the Swiss example demonstrates that the incidence of early retirement has dramatically increased even in the absence of institutional changes. We argue that the wealth effect also plays an important role in the retirement decision for middle and high income earners. An actuarially fair, but mandatory funded system with a relatively high replacement rate may thus contribute to a low labor market participation rate of elderly workers. We provide evidence using a unique dataset on individual retirement decisions in Swiss pension funds, allowing us to perfectly control for pension scheme details. Our findings suggest that affordability is a key determinant in the retirement decisions. The higher the accumulated pension capital, the earlier men, and to a smaller extent women, tend to leave the workforce. The fact that early retirement has become much more prevalent in the last 15 years is a further indicator of the importance of a wealth effect, as the maturing of the Swiss mandatory funded pension system over that period has led to an increase in the effective replacement rates for middle and high income earners. Part two covers the theoretical side of social security. Theories analyzing optimal social security benefits provide important qualitative results, by mainly using one general type of an economy. Economies are however very diverse concerning numerous aspects, one of the most important being the wealth level. This can lead to significant quantitative benefit differences that imply differences in replacement rates and levels of labor supply. We focus on several aspects related to this fact. In a within cohort social security model, we introduce disability insurance with an imperfect screening mechanism. We then vary the wealth level of the model economy and analyze how the optimal social security benefit structure or equivalently, the optimal replacement rates, changes depending on the wealth level of the economy, and if the introduction of disability insurance into a social security system is preferable for all economies. Second, the screening mechanism of disability insurance and the threshold level at which people are defined as disabled can differ. For economies with different wealth levels, we determine for different thresholds the screening level that maximizes social welfare. Finally, part three turns to the income of governments, by adding an element to the controversy on tax competition versus tax harmonization.2 Inter-jurisdictional tax competition can generate at least two potential benefits or costs: On a public level, tax competition may result in a lower or higher efficiency in the production of public services. But there is also a more private benefit in the form of an option for individuals to move to a community with a lower tax rate in the future. To explore the value citizens attach to tax competition we analyze a unique popular vote for a complete tax harmonization between communities in the third largest Swiss canton, Vaud. Although a majority of voters would have seemingly benefited from replacing the current tax rate by a revenue-neutral average tax rate, the proposal was rejected by a large margin. Our estimates suggest that the estimated combined perceived benefit from tax competition is in the range of 10%.

Induction of an immune response through the idiotypic network with monoclonal anti-idiotype antibodies in the carcinoembryonic antigen system.

Anti-idiotype antibodies can mimic the conformational epitopes of the original antigen and act as antigen substitutes for vaccination and/or serological purposes. To investigate this possibility concerning the tumor marker carcinoembryonic antigen (CEA), BALB/c mice were immunized with the previously described anti-CEA monoclonal antibody (MAb) 5.D11 (AB1). After cell fusion, 15 stable cloned cell lines secreting anti-Ids (AB2) were obtained. Selected MAbs gave various degrees of inhibition (up to 100%) of the binding of 125I-labeled CEA to MAb 5.D11. Absence of reactivity of anti-Id MAbs with normal mouse IgG was first demonstrated by the fact that anti-Id MAbs were not absorbed by passage through a mouse IgG column, and second because they bound specifically to non-reduced MAb 5.D11 on Western blots. Anti-5.D11 MAbs did not inhibit binding to CEA of MAb 10.B9, another anti-CEA antibody obtained in the same fusion as 5.D11, or that of several anti-CEA MAbs reported in an international workshop, with the exception of two other anti-CEA MAbs, both directed against the GOLD IV epitope. When applied to an Id-anti-Id competitive radioimmunoassay, a sensitivity of 2 ng/ml of CEA was obtained, which is sufficient for monitoring circulating CEA in carcinoma patients. To verify that the anti-Id MAbs have the potential to be used as CEA vaccines, syngeneic BALB/c mice were immunized with these MAbs (AB2). Sera from immunized mice were demonstrated to contain AB3 antibodies recognizing the original antigen, CEA, both in enzyme immunoassay and by immunoperoxidase staining of human colon carcinoma. These results open the perspective of vaccination against colorectal carcinoma through the use of anti-idiotype antibodies as antigen substitutes.

Hard-wired heterogeneity in blood stem cells revealed using a dynamic regulatory network model.

MOTIVATION: Combinatorial interactions of transcription factors with cis-regulatory elements control the dynamic progression through successive cellular states and thus underpin all metazoan development. The construction of network models of cis-regulatory elements, therefore, has the potential to generate fundamental insights into cellular fate and differentiation. Haematopoiesis has long served as a model system to study mammalian differentiation, yet modelling based on experimentally informed cis-regulatory interactions has so far been restricted to pairs of interacting factors. Here, we have generated a Boolean network model based on detailed cis-regulatory functional data connecting 11 haematopoietic stem/progenitor cell (HSPC) regulator genes. RESULTS: Despite its apparent simplicity, the model exhibits surprisingly complex behaviour that we charted using strongly connected components and shortest-path analysis in its Boolean state space. This analysis of our model predicts that HSPCs display heterogeneous expression patterns and possess many intermediate states that can act as 'stepping stones' for the HSPC to achieve a final differentiated state. Importantly, an external perturbation or 'trigger' is required to exit the stem cell state, with distinct triggers characterizing maturation into the various different lineages. By focusing on intermediate states occurring during erythrocyte differentiation, from our model we predicted a novel negative regulation of Fli1 by Gata1, which we confirmed experimentally thus validating our model. In conclusion, we demonstrate that an advanced mammalian regulatory network model based on experimentally validated cis-regulatory interactions has allowed us to make novel, experimentally testable hypotheses about transcriptional mechanisms that control differentiation of mammalian stem cells. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Adaptive Privacy Management System Design For Context-Aware Mobile Devices

While mobile technologies can provide great personalized services for mobile users, they also threaten their privacy. Such personalization-privacy paradox are particularly salient for context aware technology based mobile applications where user's behaviors, movement and habits can be associated with a consumer's personal identity. In this thesis, I studied the privacy issues in the mobile context, particularly focus on an adaptive privacy management system design for context-aware mobile devices, and explore the role of personalization and control over user's personal data. This allowed me to make multiple contributions, both theoretical and practical. In the theoretical world, I propose and prototype an adaptive Single-Sign On solution that use user's context information to protect user's private information for smartphone. To validate this solution, I first proved that user's context is a unique user identifier and context awareness technology can increase user's perceived ease of use of the system and service provider's authentication security. I then followed a design science research paradigm and implemented this solution into a mobile application called "Privacy Manager". I evaluated the utility by several focus group interviews, and overall the proposed solution fulfilled the expected function and users expressed their intentions to use this application. To better understand the personalization-privacy paradox, I built on the theoretical foundations of privacy calculus and technology acceptance model to conceptualize the theory of users' mobile privacy management. I also examined the role of personalization and control ability on my model and how these two elements interact with privacy calculus and mobile technology model. In the practical realm, this thesis contributes to the understanding of the tradeoff between the benefit of personalized services and user's privacy concerns it may cause. By pointing out new opportunities to rethink how user's context information can protect private data, it also suggests new elements for privacy related business models.

The Rare Cancer Network: achievements from 1993 to 2012.

The Rare Cancer Network (RCN), founded in 1993, performs research involving rare tumors that are not common enough to be the focus of prospective study. Over 55 studies have either been completed or are in progress.The aim of the paper is to present an overview of the 30 studies done through the RCN to date, organized by disease site. Five studies focus on breast pathology, including sarcoma, lymphoma, phyllodes tumor, adenoid cystic carcinoma, and ductal carcinoma in situ in young women. Three studies on prostate cancer address prostatic small cell carcinoma and adenocarcinoma of young and elderly patients. Six studies on head and neck cancers include orbital and intraocular lymphoma, mucosal melanoma, pediatric nasopharyngeal carcinoma, olfactory neuroblastoma, and mucosa-associated lymphoid tissue lymphoma of the salivary glands. There were 4 central nervous system studies on patients with cerebellar glioblastoma multiforme, atypical and malignant meningioma, spinal epidural lymphoma and myxopapillary ependymoma. Outside of these disease sites, there is a wide variety of other studies on tumors ranging from uterine leiomyosarcoma to giant cell tumors of the bone. The studies done by the RCN represent a wide range of rare pathologies that were previously only studied in small series or case reports. With further growth of the RCN and collaboration between members our ability to analyze rare tumors will increase and result in better understanding of their behavior and ultimately help direct research that may improve patient outcomes.

Additive functions in boolean models of gene regulatory network modules.

Gene-on-gene regulations are key components of every living organism. Dynamical abstract models of genetic regulatory networks help explain the genome's evolvability and robustness. These properties can be attributed to the structural topology of the graph formed by genes, as vertices, and regulatory interactions, as edges. Moreover, the actual gene interaction of each gene is believed to play a key role in the stability of the structure. With advances in biology, some effort was deployed to develop update functions in Boolean models that include recent knowledge. We combine real-life gene interaction networks with novel update functions in a Boolean model. We use two sub-networks of biological organisms, the yeast cell-cycle and the mouse embryonic stem cell, as topological support for our system. On these structures, we substitute the original random update functions by a novel threshold-based dynamic function in which the promoting and repressing effect of each interaction is considered. We use a third real-life regulatory network, along with its inferred Boolean update functions to validate the proposed update function. Results of this validation hint to increased biological plausibility of the threshold-based function. To investigate the dynamical behavior of this new model, we visualized the phase transition between order and chaos into the critical regime using Derrida plots. We complement the qualitative nature of Derrida plots with an alternative measure, the criticality distance, that also allows to discriminate between regimes in a quantitative way. Simulation on both real-life genetic regulatory networks show that there exists a set of parameters that allows the systems to operate in the critical region. This new model includes experimentally derived biological information and recent discoveries, which makes it potentially useful to guide experimental research. The update function confers additional realism to the model, while reducing the complexity and solution space, thus making it easier to investigate.

The potential of the European network of congenital anomaly registers (EUROCAT) for drug safety surveillance: a descriptive study.

BACKGROUND: European Surveillance of Congenital Anomalies (EUROCAT) is a network of population-based congenital anomaly registries in Europe surveying more than 1 million births per year, or 25% of the births in the European Union. This paper describes the potential of the EUROCAT collaboration for pharmacoepidemiology and drug safety surveillance. METHODS: The 34 full members and 6 associate members of the EUROCAT network were sent a questionnaire about their data sources on drug exposure and on drug coding. Available data on drug exposure during the first trimester available in the central EUROCAT database for the years 1996-2000 was summarised for 15 out of 25 responding full members. RESULTS: Of the 40 registries, 29 returned questionnaires (25 full and 4 associate members). Four of these registries do not collect data on maternal drug use. Of the full members, 15 registries use the EUROCAT drug code, 4 use the international ATC drug code, 3 registries use another coding system and 7 use a combination of these coding systems. Obstetric records are the most frequently used sources of drug information for the registries, followed by interviews with the mother. Only one registry uses pharmacy data. Percentages of cases with drug exposure (excluding vitamins/minerals) varied from 4.4% to 26.0% among different registries. The categories of drugs recorded varied widely between registries. CONCLUSIONS: Practices vary widely between registries regarding recording drug exposure information. EUROCAT has the potential to be an effective collaborative framework to contribute to post-marketing drug surveillance in relation to teratogenic effects, but work is needed to implement ATC drug coding more widely, and to diversify the sources of information used to determine drug exposure in each registry.

Probing the different chaperone activities of the bacterial HSP70-HSP40 system using a thermolabile luciferase substrate.

During mild heat-stress, a native thermolabile polypeptide may partially unfold and transiently expose water-avoiding hydrophobic segments that readily tend to associate into a stable misfolded species, rich in intra-molecular non-native beta-sheet structures. When the concentration of the heat-unfolded intermediates is elevated, the exposed hydrophobic segments tend to associate with other molecules into large stable insoluble complexes, also called "aggregates." In mammalian cells, stress- and mutation-induced protein misfolding and aggregation may cause degenerative diseases and aging. Young cells, however, effectively counteract toxic protein misfolding with a potent network of molecular chaperones that bind hydrophobic surfaces and actively unfold otherwise stable misfolded and aggregated polypeptides. Here, we followed the behavior of a purified, initially mostly native thermolabile luciferase mutant, in the presence or absence of the Escherichia coli DnaK-DnaJ-GrpE chaperones and/or of ATP, at 22 °C or under mild heat-stress. We concomitantly measured luciferase enzymatic activity, Thioflavin-T fluorescence, and light-scattering to assess the effects of temperature and chaperones on the formation, respectively, of native, unfolded, misfolded, and/or of aggregated species. During mild heat-denaturation, DnaK-DnaJ-GrpE+ATP best maintained, although transiently, high luciferase activity and best prevented heat-induced misfolding and aggregation. In contrast, the ATP-less DnaK and DnaJ did not maintain optimal luciferase activity and were less effective at preventing luciferase misfolding and aggregation. We present a model accounting for the experimental data, where native, unfolded, misfolded, and aggregated species spontaneously inter-convert, and in which DnaK-DnaJ-GrpE+ATP specifically convert stable misfolded species into unstable unfolded intermediates.

The HVEM network: new directions in targeting novel costimulatory/co-inhibitory molecules for cancer therapy.

The regulation of the immune system is controlled by many cell surface receptors. A prominent representative is the 'molecular switch' HVEM (herpes virus entry mediator) that can activate either proinflammatory or inhibitory signaling pathways. HVEM ligands belong to two distinct families: the TNF-related cytokines LIGHT and lymphotoxin-α, and the Ig-related membrane proteins BTLA and CD160. HVEM and its ligands have been involved in the pathogenesis of various autoimmune and inflammatory diseases, but recent reports indicate that this network may also be involved in tumor progression and resistance to immune response. Here we summarize the recent advances made regarding the knowledge on HVEM and its ligands in cancer cells, and their potential roles in tumor progression and escape to immune responses. Blockade or enhancement of these pathways may help improving cancer therapy.

A 2D/3D image analysis system to track fluorescently labeled structures in rod-shaped cells: application to measure spindle pole asymmetry during mitosis.

BACKGROUND: The yeast Schizosaccharomyces pombe is frequently used as a model for studying the cell cycle. The cells are rod-shaped and divide by medial fission. The process of cell division, or cytokinesis, is controlled by a network of signaling proteins called the Septation Initiation Network (SIN); SIN proteins associate with the SPBs during nuclear division (mitosis). Some SIN proteins associate with both SPBs early in mitosis, and then display strongly asymmetric signal intensity at the SPBs in late mitosis, just before cytokinesis. This asymmetry is thought to be important for correct regulation of SIN signaling, and coordination of cytokinesis and mitosis. In order to study the dynamics of organelles or large protein complexes such as the spindle pole body (SPB), which have been labeled with a fluorescent protein tag in living cells, a number of the image analysis problems must be solved; the cell outline must be detected automatically, and the position and signal intensity associated with the structures of interest within the cell must be determined. RESULTS: We present a new 2D and 3D image analysis system that permits versatile and robust analysis of motile, fluorescently labeled structures in rod-shaped cells. We have designed an image analysis system that we have implemented as a user-friendly software package allowing the fast and robust image-analysis of large numbers of rod-shaped cells. We have developed new robust algorithms, which we combined with existing methodologies to facilitate fast and accurate analysis. Our software permits the detection and segmentation of rod-shaped cells in either static or dynamic (i.e. time lapse) multi-channel images. It enables tracking of two structures (for example SPBs) in two different image channels. For 2D or 3D static images, the locations of the structures are identified, and then intensity values are extracted together with several quantitative parameters, such as length, width, cell orientation, background fluorescence and the distance between the structures of interest. Furthermore, two kinds of kymographs of the tracked structures can be established, one representing the migration with respect to their relative position, the other representing their individual trajectories inside the cell. This software package, called "RodCellJ", allowed us to analyze a large number of S. pombe cells to understand the rules that govern SIN protein asymmetry. CONCLUSIONS: "RodCell" is freely available to the community as a package of several ImageJ plugins to simultaneously analyze the behavior of a large number of rod-shaped cells in an extensive manner. The integration of different image-processing techniques in a single package, as well as the development of novel algorithms does not only allow to speed up the analysis with respect to the usage of existing tools, but also accounts for higher accuracy. Its utility was demonstrated on both 2D and 3D static and dynamic images to study the septation initiation network of the yeast Schizosaccharomyces pombe. More generally, it can be used in any kind of biological context where fluorescent-protein labeled structures need to be analyzed in rod-shaped cells. AVAILABILITY: RodCellJ is freely available under http://bigwww.epfl.ch/algorithms.html, (after acceptance of the publication).

S-system parameter estimation for noisy metabolic profiles using newton-flow analysis.

Biochemical systems are commonly modelled by systems of ordinary differential equations (ODEs). A particular class of such models called S-systems have recently gained popularity in biochemical system modelling. The parameters of an S-system are usually estimated from time-course profiles. However, finding these estimates is a difficult computational problem. Moreover, although several methods have been recently proposed to solve this problem for ideal profiles, relatively little progress has been reported for noisy profiles. We describe a special feature of a Newton-flow optimisation problem associated with S-system parameter estimation. This enables us to significantly reduce the search space, and also lends itself to parameter estimation for noisy data. We illustrate the applicability of our method by applying it to noisy time-course data synthetically produced from previously published 4- and 30-dimensional S-systems. In addition, we propose an extension of our method that allows the detection of network topologies for small S-systems. We introduce a new method for estimating S-system parameters from time-course profiles. We show that the performance of this method compares favorably with competing methods for ideal profiles, and that it also allows the determination of parameters for noisy profiles.

Towards robust network based complex systems : from evolutionary cellular automata to biological models

Abstract Sitting between your past and your future doesn't mean you are in the present. Dakota Skye Complex systems science is an interdisciplinary field grouping under the same umbrella dynamical phenomena from social, natural or mathematical sciences. The emergence of a higher order organization or behavior, transcending that expected of the linear addition of the parts, is a key factor shared by all these systems. Most complex systems can be modeled as networks that represent the interactions amongst the system's components. In addition to the actual nature of the part's interactions, the intrinsic topological structure of underlying network is believed to play a crucial role in the remarkable emergent behaviors exhibited by the systems. Moreover, the topology is also a key a factor to explain the extraordinary flexibility and resilience to perturbations when applied to transmission and diffusion phenomena. In this work, we study the effect of different network structures on the performance and on the fault tolerance of systems in two different contexts. In the first part, we study cellular automata, which are a simple paradigm for distributed computation. Cellular automata are made of basic Boolean computational units, the cells; relying on simple rules and information from- the surrounding cells to perform a global task. The limited visibility of the cells can be modeled as a network, where interactions amongst cells are governed by an underlying structure, usually a regular one. In order to increase the performance of cellular automata, we chose to change its topology. We applied computational principles inspired by Darwinian evolution, called evolutionary algorithms, to alter the system's topological structure starting from either a regular or a random one. The outcome is remarkable, as the resulting topologies find themselves sharing properties of both regular and random network, and display similitudes Watts-Strogtz's small-world network found in social systems. Moreover, the performance and tolerance to probabilistic faults of our small-world like cellular automata surpasses that of regular ones. In the second part, we use the context of biological genetic regulatory networks and, in particular, Kauffman's random Boolean networks model. In some ways, this model is close to cellular automata, although is not expected to perform any task. Instead, it simulates the time-evolution of genetic regulation within living organisms under strict conditions. The original model, though very attractive by it's simplicity, suffered from important shortcomings unveiled by the recent advances in genetics and biology. We propose to use these new discoveries to improve the original model. Firstly, we have used artificial topologies believed to be closer to that of gene regulatory networks. We have also studied actual biological organisms, and used parts of their genetic regulatory networks in our models. Secondly, we have addressed the improbable full synchronicity of the event taking place on. Boolean networks and proposed a more biologically plausible cascading scheme. Finally, we tackled the actual Boolean functions of the model, i.e. the specifics of how genes activate according to the activity of upstream genes, and presented a new update function that takes into account the actual promoting and repressing effects of one gene on another. Our improved models demonstrate the expected, biologically sound, behavior of previous GRN model, yet with superior resistance to perturbations. We believe they are one step closer to the biological reality.

The HVEM network: new directions in targeting novel costimulatory/co-inhibitory molecules for cancer therapy.

The regulation of the immune system is controlled by many cell surface receptors. A prominent representative is the 'molecular switch' HVEM (herpes virus entry mediator) that can activate either proinflammatory or inhibitory signaling pathways. HVEM ligands belong to two distinct families: the TNF-related cytokines LIGHT and lymphotoxin-α, and the Ig-related membrane proteins BTLA and CD160. HVEM and its ligands have been involved in the pathogenesis of various autoimmune and inflammatory diseases, but recent reports indicate that this network may also be involved in tumor progression and resistance to immune response. Here we summarize the recent advances made regarding the knowledge on HVEM and its ligands in cancer cells, and their potential roles in tumor progression and escape to immune responses. Blockade or enhancement of these pathways may help improving cancer therapy.

Continuous arterial spin labeling of mouse cerebral blood flow using an actively-detuned two-coil system at 9.4T.

Among numerous magnetic resonance imaging (MRI) techniques, perfusion MRI provides insight into the passage of blood through the brain's vascular network non-invasively. Studying disease models and transgenic mice would intrinsically help understanding the underlying brain functions, cerebrovascular disease and brain disorders. This study evaluates the feasibility of performing continuous arterial spin labeling (CASL) on all cranial arteries for mapping murine cerebral blood flow at 9.4 T. We showed that with an active-detuned two-coil system, a labeling efficiency of 0.82 ± 0.03 was achieved with minimal magnetization transfer residuals in brain. The resulting cerebral blood flow of healthy mouse was 99 ± 26 mL/100g/min, in excellent agreement with other techniques. In conclusion, high magnetic fields deliver high sensitivity and allowing not only CASL but also other MR techniques, i.e. (1)H MRS and diffusion MRI etc, in studying murine brains.

Outcome and patterns of failure in testicular lymphoma: a multicenter Rare Cancer Network study.

PURPOSE: To assess the outcome and patterns of failure in patients with testicular lymphoma treated by chemotherapy (CT) and/or radiation therapy (RT). METHODS AND MATERIALS: Data from a series of 36 adult patients with Ann Arbor Stage I (n = 21), II (n = 9), III (n = 3), or IV (n = 3) primary testicular lymphoma, consecutively treated between 1980 and 1999, were collected in a retrospective multicenter study by the Rare Cancer Network. Median age was 64 years (range: 21-91 years). Full staging workup (chest X-ray, testicular ultrasound, abdominal ultrasound, and/or thoracoabdominal computer tomography, bone marrow assessment, full blood count, lactate dehydrogenase, and cerebrospinal fluid evaluation) was completed in 18 (50%) patients. All but one patient underwent orchidectomy, and spermatic cord infiltration was found in 9 patients. Most patients (n = 29) had CT, consisting in most cases of cyclophosphamide, doxorubicin, vincristine, and prednisolone (CHOP) with (n = 17) or without intrathecal CT. External RT was delivered to scrotum alone (n = 12) or testicular, iliac, and para-aortic regions (n = 8). The median RT dose was 31 Gy (range: 20-44 Gy) in a median of 17 fractions (10-24), using a median of 1.8 Gy (range: 1.5-2.5 Gy) per fraction. The median follow-up period was 42 months (range: 6-138 months). RESULTS: After a median period of 11 months (range: 1-76 months), 14 patients presented lymphoma progression, mostly in the central nervous system (CNS) (n = 8). Among the 17 patients who received intrathecal CT, 4 had a CNS relapse (p = NS). No testicular, iliac, or para-aortic relapse was observed in patients receiving RT to these regions. The 5-year overall, lymphoma-specific, and disease-free survival was 47%, 66%, and 43%, respectively. In univariate analyses, statistically significant factors favorably influencing the outcome were early-stage and combined modality treatment. Neither RT technique nor total dose influenced the outcome. Multivariate analysis revealed that the most favorable independent factors predicting the outcome were younger age, early-stage disease, and combined modality treatment. CONCLUSIONS: In this multicenter retrospective study, CNS was found to be the principal site of relapse, and no extra-CNS lymphoma progression was observed in the irradiated volumes. More effective CNS prophylaxis, including combined modalities, should be prospectively explored in this uncommon site of extranodal lymphoma.