Attrition in the Swiss Household Panel

In this paper, we analyze magnitude and possible selectivity of attrition in first wave respondents in the Swiss Household Panel (SHP), from wave two (2000) through wave seven (2005). After comparing attrition of first wave respondents with that of other panel surveys, we proceed to model selectivity of attrition in two steps: we first build separate waveto- wave models, and second a longitudinal all-wave model. The latter model includes wave interaction effects. The first models allow for tracing of selectivity development, i.e. whether an initial selectivity might compensate or cumulates over time, the second to assessing the effects of the covariates in a specific wave, controlling for the base attrition effect. In particular it allows for the analysis of consequences due to discrete fieldwork events. Our results support the findings in the literature: attritors are in general the younger people and the males, foreigners, the socially and politically "excluded", i.e. those who show little social and political interest and participation, those who are mostly dissatisfied with various aspects in their life, and those who live in households with high unit nonresponse, and who exhibit a worse reporting behavior. This pattern is rather cumulative than compensating over panel waves. Excessive attrition in two waves presumably caused by two discrete events in the panel is not particularly selective. Still existing variation in selective attrition is worth to be further explored.

Simulation of stromatolite growth using diffusion-limited aggregation and a discrete model of biogeochemical exchanges in microbial mat

Resume : Mieux comprendre les stromatolithes et les tapis microbiens est un sujet important en biogéosciences puisque cela aide à l'étude des premières formes de vie sur Terre, a mieux cerner l'écologie des communautés microbiennes et la contribution des microorganismes a la biominéralisation, et même à poser certains fondements dans les recherches en exobiologie. D'autre part, la modélisation est un outil puissant utilisé dans les sciences naturelles pour appréhender différents phénomènes de façon théorique. Les modèles sont généralement construits sur un système d'équations différentielles et les résultats sont obtenus en résolvant ce système. Les logiciels disponibles pour implémenter les modèles incluent les logiciels mathématiques et les logiciels généraux de simulation. L'objectif principal de cette thèse est de développer des modèles et des logiciels pour aider a comprendre, via la simulation, le fonctionnement des stromatolithes et des tapis microbiens. Ces logiciels ont été développés en C++ en ne partant d'aucun pré-requis de façon a privilégier performance et flexibilité maximales. Cette démarche permet de construire des modèles bien plus spécifiques et plus appropriés aux phénomènes a modéliser. Premièrement, nous avons étudié la croissance et la morphologie des stromatolithes. Nous avons construit un modèle tridimensionnel fondé sur l'agrégation par diffusion limitée. Le modèle a été implémenté en deux applications C++: un moteur de simulation capable d'exécuter un batch de simulations et de produire des fichiers de résultats, et un outil de visualisation qui permet d'analyser les résultats en trois dimensions. Après avoir vérifié que ce modèle peut en effet reproduire la croissance et la morphologie de plusieurs types de stromatolithes, nous avons introduit un processus de sédimentation comme facteur externe. Ceci nous a mené a des résultats intéressants, et permis de soutenir l'hypothèse que la morphologie des stromatolithes pourrait être le résultat de facteurs externes autant que de facteurs internes. Ceci est important car la classification des stromatolithes est généralement fondée sur leur morphologie, imposant que la forme d'un stromatolithe est dépendante de facteurs internes uniquement (c'est-à-dire les tapis microbiens). Les résultats avancés dans ce mémoire contredisent donc ces assertions communément admises. Ensuite, nous avons décidé de mener des recherches plus en profondeur sur les aspects fonctionnels des tapis microbiens. Nous avons construit un modèle bidimensionnel de réaction-diffusion fondé sur la simulation discrète. Ce modèle a été implémenté dans une application C++ qui permet de paramétrer et exécuter des simulations. Nous avons ensuite pu comparer les résultats de simulation avec des données du monde réel et vérifier que le modèle peut en effet imiter le comportement de certains tapis microbiens. Ainsi, nous avons pu émettre et vérifier des hypothèses sur le fonctionnement de certains tapis microbiens pour nous aider à mieux en comprendre certains aspects, comme la dynamique des éléments, en particulier le soufre et l'oxygène. En conclusion, ce travail a abouti à l'écriture de logiciels dédiés à la simulation de tapis microbiens d'un point de vue tant morphologique que fonctionnel, suivant deux approches différentes, l'une holistique, l'autre plus analytique. Ces logiciels sont gratuits et diffusés sous licence GPL (General Public License). Abstract : Better understanding of stromatolites and microbial mats is an important topic in biogeosciences as it helps studying the early forms of life on Earth, provides clues re- garding the ecology of microbial ecosystems and their contribution to biomineralization, and gives basis to a new science, exobiology. On the other hand, modelling is a powerful tool used in natural sciences for the theoretical approach of various phenomena. Models are usually built on a system of differential equations and results are obtained by solving that system. Available software to implement models includes mathematical solvers and general simulation software. The main objective of this thesis is to develop models and software able to help to understand the functioning of stromatolites and microbial mats. Software was developed in C++ from scratch for maximum performance and flexibility. This allows to build models much more specific to a phenomenon rather than general software. First, we studied stromatolite growth and morphology. We built a three-dimensional model based on diffusion-limited aggregation. The model was implemented in two C++ applications: a simulator engine, which can run a batch of simulations and produce result files, and a Visualization tool, which allows results to be analysed in three dimensions. After verifying that our model can indeed reproduce the growth and morphology of several types of stromatolites, we introduced a sedimentation process as an external factor. This lead to interesting results, and allowed to emit the hypothesis that stromatolite morphology may be the result of external factors as much as internal factors. This is important as stromatolite classification is usually based on their morphology, imposing that a stromatolite shape is dependant on internal factors only (i.e. the microbial mat). This statement is contradicted by our findings, Second, we decided to investigate deeper the functioning of microbial mats, We built a two-dimensional reaction-diffusion model based on discrete simulation, The model was implemented in a C++ application that allows setting and running simulations. We could then compare simulation results with real world data and verify that our model can indeed mimic the behaviour of some microbial mats. Thus, we have proposed and verified hypotheses regarding microbial mats functioning in order to help to better understand them, e.g. the cycle of some elements such as oxygen or sulfur. ln conclusion, this PhD provides a simulation software, dealing with two different approaches. This software is free and available under a GPL licence.

Simulation-based systematic review of imatinib population pharmacokinetics and PK-PD relationships in chronic myeloid leukemia (CML) patients

Objectives: Several population pharmacokinetic (PPK) and pharmacokinetic-pharmacodynamic (PK-PD) analyses have been performed with the anticancer drug imatinib. Inspired by the approach of meta-analysis, we aimed to compare and combine results from published studies in a useful way - in particular for improving the clinical interpretation of imatinib concentration measurements in the scope of therapeutic drug monitoring (TDM). Methods: Original PPK analyses and PK-PD studies (PK surrogate: trough concentration Cmin; PD outcomes: optimal early response and specific adverse events) were searched systematically on MEDLINE. From each identified PPK model, a predicted concentration distribution under standard dosage was derived through 1000 simulations (NONMEM), after standardizing model parameters to common covariates. A "reference range" was calculated from pooled simulated concentrations in a semi-quantitative approach (without specific weighting) over the whole dosing interval. Meta-regression summarized relationships between Cmin and optimal/suboptimal early treatment response. Results: 9 PPK models and 6 relevant PK-PD reports in CML patients were identified. Model-based predicted median Cmin ranged from 555 to 1388 ng/ml (grand median: 870 ng/ml and inter-quartile range: 520-1390 ng/ml). The probability to achieve optimal early response was predicted to increase from 60 to 85% from 520 to 1390 ng/ml across PK-PD studies (odds ratio for doubling Cmin: 2.7). Reporting of specific adverse events was too heterogeneous to perform a regression analysis. The general frequency of anemia, rash and fluid retention increased however consistently with Cmin, but less than response probability. Conclusions: Predicted drug exposure may differ substantially between various PPK analyses. In this review, heterogeneity was mainly attributed to 2 "outlying" models. The established reference range seems to cover the range where both good efficacy and acceptable tolerance are expected for most patients. TDM guided dose adjustment appears therefore justified for imatinib in CML patients. Its usefulness remains now to be prospectively validated in a randomized trial.

Dynamic simulation of regulatory networks using SQUAD.

BACKGROUND: The ambition of most molecular biologists is the understanding of the intricate network of molecular interactions that control biological systems. As scientists uncover the components and the connectivity of these networks, it becomes possible to study their dynamical behavior as a whole and discover what is the specific role of each of their components. Since the behavior of a network is by no means intuitive, it becomes necessary to use computational models to understand its behavior and to be able to make predictions about it. Unfortunately, most current computational models describe small networks due to the scarcity of kinetic data available. To overcome this problem, we previously published a methodology to convert a signaling network into a dynamical system, even in the total absence of kinetic information. In this paper we present a software implementation of such methodology. RESULTS: We developed SQUAD, a software for the dynamic simulation of signaling networks using the standardized qualitative dynamical systems approach. SQUAD converts the network into a discrete dynamical system, and it uses a binary decision diagram algorithm to identify all the steady states of the system. Then, the software creates a continuous dynamical system and localizes its steady states which are located near the steady states of the discrete system. The software permits to make simulations on the continuous system, allowing for the modification of several parameters. Importantly, SQUAD includes a framework for perturbing networks in a manner similar to what is performed in experimental laboratory protocols, for example by activating receptors or knocking out molecular components. Using this software we have been able to successfully reproduce the behavior of the regulatory network implicated in T-helper cell differentiation. CONCLUSION: The simulation of regulatory networks aims at predicting the behavior of a whole system when subject to stimuli, such as drugs, or determine the role of specific components within the network. The predictions can then be used to interpret and/or drive laboratory experiments. SQUAD provides a user-friendly graphical interface, accessible to both computational and experimental biologists for the fast qualitative simulation of large regulatory networks for which kinetic data is not necessarily available.

Ab initio modeling and molecular dynamics simulation of the alpha 1b-adrenergic receptor activation.

This work describes the ab initio procedure employed to build an activation model for the alpha 1b-adrenergic receptor (alpha 1b-AR). The first version of the model was progressively modified and complicated by means of a many-step iterative procedure characterized by the employment of experimental validations of the model in each upgrading step. A combined simulated (molecular dynamics) and experimental mutagenesis approach was used to determine the structural and dynamic features characterizing the inactive and active states of alpha 1b-AR. The latest version of the model has been successfully challenged with respect to its ability to interpret and predict the functional properties of a large number of mutants. The iterative approach employed to describe alpha 1b-AR activation in terms of molecular structure and dynamics allows further complications of the model to allow prediction and interpretation of an ever-increasing number of experimental data.

Hydrogeophysical data integration at larger scales: Application of Bayesian sequential simulation for the characterization of heterogeneous alluvial aquifers

Knowledge of the spatial distribution of hydraulic conductivity (K) within an aquifer is critical for reliable predictions of solute transport and the development of effective groundwater management and/or remediation strategies. While core analyses and hydraulic logging can provide highly detailed information, such information is inherently localized around boreholes that tend to be sparsely distributed throughout the aquifer volume. Conversely, larger-scale hydraulic experiments like pumping and tracer tests provide relatively low-resolution estimates of K in the investigated subsurface region. As a result, traditional hydrogeological measurement techniques contain a gap in terms of spatial resolution and coverage, and they are often alone inadequate for characterizing heterogeneous aquifers. Geophysical methods have the potential to bridge this gap. The recent increased interest in the application of geophysical methods to hydrogeological problems is clearly evidenced by the formation and rapid growth of the domain of hydrogeophysics over the past decade (e.g., Rubin and Hubbard, 2005).

Automatic measurement of key ski jumping phases and temporal events with a wearable system.

We propose a new method, based on inertial sensors, to automatically measure at high frequency the durations of the main phases of ski jumping (i.e. take-off release, take-off, and early flight). The kinematics of the ski jumping movement were recorded by four inertial sensors, attached to the thigh and shank of junior athletes, for 40 jumps performed during indoor conditions and 36 jumps in field conditions. An algorithm was designed to detect temporal events from the recorded signals and to estimate the duration of each phase. These durations were evaluated against a reference camera-based motion capture system and by trainers conducting video observations. The precision for the take-off release and take-off durations (indoor < 39 ms, outdoor = 27 ms) can be considered technically valid for performance assessment. The errors for early flight duration (indoor = 22 ms, outdoor = 119 ms) were comparable to the trainers' variability and should be interpreted with caution. No significant changes in the error were noted between indoor and outdoor conditions, and individual jumping technique did not influence the error of take-off release and take-off. Therefore, the proposed system can provide valuable information for performance evaluation of ski jumpers during training sessions.

Effort, reward and self-reported mental health: a simulation study on negative affectivity bias.

Background : In the present article, we propose an alternative method for dealing with negative affectivity (NA) biases in research, while investigating the association between a deleterious psychosocial environment at work and poor mental health. First, we investigated how strong NA must be to cause an observed correlation between the independent and dependent variables. Second, we subjectively assessed whether NA can have a large enough impact on a large enough number of subjects to invalidate the observed correlations between dependent and independent variables.Methods : We simulated 10,000 populations of 300 subjects each, using the marginal distribution of workers in an actual population that had answered the Siegrist's questionnaire on effort and reward imbalance (ERI) and the General Health Questionnaire (GHQ).Results : The results of the present study suggested that simulated NA has a minimal effect on the mean scores for effort and reward. However, the correlations between the effort and reward imbalance (ERI) ratio and the GHQ score might be important, even in simulated populations with a limited NA.Conclusions : When investigating the relationship between the ERI ratio and the GHQ score, we suggest the following rules for the interpretation of the results: correlations with an explained variance of 5% and below should be considered with caution; correlations with an explained variance between 5% and 10% may result from NA, although this effect does not seem likely; and correlations with an explained variance of 10% and above are not likely to be the result of NA biases. [Authors]

Microsatellites can be misleading: an empirical and simulation study.

It has been long recognized that highly polymorphic genetic markers can lead to underestimation of divergence between populations when migration is low. Microsatellite loci, which are characterized by extremely high mutation rates, are particularly likely to be affected. Here, we report genetic differentiation estimates in a contact zone between two chromosome races of the common shrew (Sorex araneus), based on 10 autosomal microsatellites, a newly developed Y-chromosome microsatellite, and mitochondrial DNA. These results are compared to previous data on proteins and karyotypes. Estimates of genetic differentiation based on F- and R-statistics are much lower for autosomal microsatellites than for all other genetic markers. We show by simulations that this discrepancy stems mainly from the high mutation rate of microsatellite markers for F-statistics and from deviations from a single-step mutation model for R-statistics. The sex-linked genetic markers show that all gene exchange between races is mediated by females. The absence of male-mediated gene flow most likely results from male hybrid sterility.

Scan statistics analysis of forest fire clusters

Spatio-temporal clusters in 1997?2003 fire sequences of Tuscany region (central Italy) have been identified and analysed by using the scan statistic, a method which was devised to evidence clusters in epidemiology. Results showed that the method is reliable to find clusters of events and to evaluate their significance via Monte Carlo replication. The evaluation of the presence of spatial and temporal patterns in fire occurrence and their significance could have a great impact in forthcoming studies on fire occurrences prediction.

Please die during office hours : periodicity of cardiovascular events in switzerland between 1969 and 2007

Purpose: to evaluate and compare the periodical patterns of death from cardiovascular disease (CVD), including acute myocardial infarction (AMI) and stroke in the Swiss population between the years 1969 and 2007.¦Methods: Swiss mortality database for the period of 1969- 2007 (2'362'430 deaths overall). The number of deaths due to CVD, AMI and stroke according to the time of day, day of the week and month were assessed, overall and after dividing the events according to gender and age (< 65 or ≥65 years old).¦Results: In general and for all four subgroups according to age and sex, there is a daily variation in the number of deaths with a first peak in the morning (8h00 -12h00) and a smaller second peak in the late afternoon (14h - 18h). Both males and females have similar hourly patterns, although the magnitude of the difference diminishes in older patients particularly for people who die from stroke. For the weekly variation, there seems to be a significant trend only in the younger population with the lowest mortality rates on Sunday and the highest on Mondays for all diseases. When it comes to seasonal variation according to month, the trend is more significant in the elder patients with the highest death rates during the winter months (+31%) and the lowest in the summer (July/August).¦Conclusion: There is a timely pattern for CVD, AMI and stroke deaths in Switzerland. This pattern changes according to the age and sex of the patients. Knowing this trend, its triggering factors and consequences, perhaps there could be measures put in place to prevent, diagnose and treat the population which is the most vulnerable at certain times.

Synapse formation on adult-born hippocampal neurons.

It is now widely accepted that adult neurogenesis plays a fundamental role in hippocampal function. Neurons born in the adult dentate gyrus of the hippocampus undergo a series of events before they fully integrate in the network and eventually become undistinguishable from neurons born during embryogenesis. Adult hippocampal neurogenesis is strongly regulated by neuronal activity and neurotransmitters, and the synaptic integration of adult-born neurons occurs in discrete steps, some of which are very different from perinatal synaptogenesis. Here, we review the current knowledge on the development of the synaptic input and output of neurons born in the adult hippocampus, from the stem/progenitor cell to the fully mature neuron. We also provide insight on the regulation of adult neurogenesis by some neurotransmitters and discuss some specificities of the integration of new neurons in an adult environment. The understanding of the mechanisms regulating the synaptic integration of adult-born neurons is not only crucial for our understanding of brain plasticity, but also provides a framework for the manipulation and monitoring of endogenous adult neurogenesis as well as grafted cells, for potential therapeutic applications.

Reduced quality of life associated adverse events in intermediate hepatocellular carcinoma patients treated with PRECISION TACE with drug eluting beads: Results from the PRECISION V randomized trial : B-241

Purpose: To evaluate the extent of quality of life (QoL) associated adverse events (AEs) following PRECISION TACE with DC Bead compared with conventional transarterial chemoembolisation (cTACE). Methods and Materials: 201 intermediate HCC patients were treated with DC Bead (PRECISION TACE) or conventional TACE (cTACE) with doxorubicin in the PRECISION V clinical study. 93 patients were treated with DC Bead and 108 Patients with cTACE every 2 months and followed up for 6 months. AEs were classified according to the South West Oncology Group criteria. QoL associated AEs were defined as alopecia, constipation, nausea, vomiting, pyrexia, chills, asthenia, fatigue, and headache. Results: The biggest difference in QoL associated AEs was for alopecia: 2 patients (2.2%) for DC-Bead versus 21 patients (19.4%) for cTACE. For other clinical symptoms, constipation (n=10; 10.8% vs. n=13; 12%), vomiting (n=10; 10.8% vs. n=14; 13.0%), pyrexia (n=16; 17.2% vs. n=26; 24.1%), chills (n=1; 1.1% vs. n=5; 4.6%), and headache (n=2; 2.2% vs. n=8; 7.4%) showed lower incidence in the DC Bead group versus cTACE. Nausea, n= 15; 13.9% (n=15; 16.1%) and fatigue, n=6; 5.6% (n=13; 14.0%) were lower for cTACE. Total dose of doxorubicin was on average 35% higher in the DC Bead group. Conclusion: Although patients in the DC Bead group received a higher doxorubicin dose, less QoL associated AEs were reported for this group. Alopecia, the most obvious outward sign of toxicity, was only reported in a tenth of DC Bead patients. Thus, PRECISION TACE with DC Bead improves quality of life associated adverse events.

Cell-based computational modeling of vascular morphogenesis using Tissue Simulation Toolkit.

Computational modeling has become a widely used tool for unraveling the mechanisms of higher level cooperative cell behavior during vascular morphogenesis. However, experimenting with published simulation models or adding new assumptions to those models can be daunting for novice and even for experienced computational scientists. Here, we present a step-by-step, practical tutorial for building cell-based simulations of vascular morphogenesis using the Tissue Simulation Toolkit (TST). The TST is a freely available, open-source C++ library for developing simulations with the two-dimensional cellular Potts model, a stochastic, agent-based framework to simulate collective cell behavior. We will show the basic use of the TST to simulate and experiment with published simulations of vascular network formation. Then, we will present step-by-step instructions and explanations for building a recent simulation model of tumor angiogenesis. Demonstrated mechanisms include cell-cell adhesion, chemotaxis, cell elongation, haptotaxis, and haptokinesis.

Cutting edge: apoptosis of superantigen-activated T cells occurs preferentially after a discrete number of cell divisions in vivo.

Staphylococcal enterotoxins are bacterial products that display superantigen activity in vitro as well as in vivo. For instance, staphylococcal enterotoxin B (SEB) polyclonally activates T cells that bear the Vbeta8 gene segment of the TCR. SEB-activated T cells undergo a burst of proliferation that is followed by apoptosis. Using an in vivo adaptation of a fluorescent cell division monitoring technique, we show here that SEB-activated T cells divide asynchronously, and that apoptosis of superantigen-activated T cells is preferentially restricted to cells which have undergone a discrete number of cell divisions. Collectively, our data suggest that superantigen-activated T cells are programmed to undergo a fixed number of cell divisions before undergoing apoptosis. A delayed death program may provide a mechanistic compromise between effector functions and homeostasis of activated T cells.