Evaluation of occupational exposure: comparison of biological and environmental variabilities using physiologically based toxicokinetic modeling

PURPOSE: Few studies compare the variabilities that characterize environmental (EM) and biological monitoring (BM) data. Indeed, comparing their respective variabilities can help to identify the best strategy for evaluating occupational exposure. The objective of this study is to quantify the biological variability associated with 18 bio-indicators currently used in work environments. METHOD: Intra-individual (BV(intra)), inter-individual (BV(inter)), and total biological variability (BV(total)) were quantified using validated physiologically based toxicokinetic (PBTK) models coupled with Monte Carlo simulations. Two environmental exposure profiles with different levels of variability were considered (GSD of 1.5 and 2.0). RESULTS: PBTK models coupled with Monte Carlo simulations were successfully used to predict the biological variability of biological exposure indicators. The predicted values follow a lognormal distribution, characterized by GSD ranging from 1.1 to 2.3. Our results show that there is a link between biological variability and the half-life of bio-indicators, since BV(intra) and BV(total) both decrease as the biological indicator half-lives increase. BV(intra) is always lower than the variability in the air concentrations. On an individual basis, this means that the variability associated with the measurement of biological indicators is always lower than the variability characterizing airborne levels of contaminants. For a group of workers, BM is less variable than EM for bio-indicators with half-lives longer than 10-15 h. CONCLUSION: The variability data obtained in the present study can be useful in the development of BM strategies for exposure assessment and can be used to calculate the number of samples required for guiding industrial hygienists or medical doctors in decision-making.

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.

Physiologically based pharmacokinetic modeling of arsenic in the mouse

A remarkable feature of the carcinogenicity of inorganic arsenic is that while human exposures to high concentrations of inorganic arsenic in drinking water are associated with increases in skin, lung, and bladder cancer, inorganic arsenic has not typically caused tumors in standard laboratory animal test protocols. Inorganic arsenic administered for periods of up to 2 yr to various strains of laboratory mice, including the Swiss CD-1, Swiss CR:NIH(S), C57Bl/6p53(+/-), and C57Bl/6p53(+/+), has not resulted in significant increases in tumor incidence. However, Ng et al. (1999) have reported a 40% tumor incidence in C57Bl/6J mice exposed to arsenic in their drinking water throughout their lifetime, with no tumors reported in controls. In order to investigate the potential role of tissue dosimetry in differential susceptibility to arsenic carcinogenicity, a physiologically based pharmacokinetic (PBPK) model for inorganic arsenic in the rat, hamster, monkey, and human (Mann et al., 1996a, 1996b) was extended to describe the kinetics in the mouse. The PBPK model was parameterized in the mouse using published data from acute exposures of B6C3F1 mice to arsenate, arsenite, monomethylarsonic acid (MMA), and dimethylarsinic acid (DMA) and validated using data from acute exposures of C57Black mice. Predictions of the acute model were then compared with data from chronic exposures. There was no evidence of changes in the apparent volume of distribution or in the tissue-plasma concentration ratios between acute and chronic exposure that might support the possibility of inducible arsenite efflux. The PBPK model was also used to project tissue dosimetry in the C57Bl/6J study, in comparison with tissue levels in studies having shorter duration but higher arsenic treatment concentrations. The model evaluation indicates that pharmacokinetic factors do not provide an explanation for the difference in outcomes across the various mouse bioassays. Other possible explanations may relate to strain-specific differences, or to the different durations of dosing in each of the mouse studies, given the evidence that inorganic arsenic is likely to be active in the later stages of the carcinogenic process. [Authors]

Measurements of glial metabolic fluxes with C-11-acetate using positron emission and an adapted NMR-based metabolic modeling approach

Objectives: Acetate brain metabolism has the particularity to occur specifically in glial cells. Labeling studies, using acetate labeled either with 13C (NMR) or 11C (PET), are governed by the same biochemical reactions and thus follow the same mathematical principles. In this study, the objective was to adapt an NMR acetate brain metabolism model to analyse [1-11C]acetate infusion in rats. Methods: Brain acetate infusion experiments were modeled using a two-compartment model approach used in NMR.1-3 The [1-11C]acetate labeling study was done using a beta scintillator.4 The measured radioactive signal represents the time evolution of the sum of all labeled metabolites in the brain. Using a coincidence counter in parallel, an arterial input curve was measured. The 11C at position C-1 of acetate is metabolized in the first turn of the TCA cycle to the position 5 of glutamate (Figure 1A). Through the neurotransmission process, it is further transported to the position 5 of glutamine and the position 5 of neuronal glutamate. After the second turn of the TCA cycle, tracer from [1-11C]acetate (and also a part from glial [5-11C]glutamate) is transferred to glial [1-11C]glutamate and further to [1-11C]glutamine and neuronal glutamate through the neurotransmission cycle. Brain poster session: oxidative mechanisms S460 Journal of Cerebral Blood Flow & Metabolism (2009) 29, S455-S466 Results: The standard acetate two-pool PET model describes the system by a plasma pool and a tissue pool linked by rate constants. Experimental data are not fully described with only one tissue compartment (Figure 1B). The modified NMR model was fitted successfully to tissue time-activity curves from 6 single animals, by varying the glial mitochondrial fluxes and the neurotransmission flux Vnt. A glial composite rate constant Kgtg=Vgtg/[Ace]plasma was extracted. Considering an average acetate concentration in plasma of 1 mmol/g5 and the negligible additional amount injected, we found an average Vgtg = 0.08±0.02 (n = 6), in agreement with previous NMR measurements.1 The tissue time-activity curve is dominated by glial glutamate and later by glutamine (Figure 1B). Labeling of neuronal pools has a low influence, at least for the 20 mins of beta-probe acquisition. Based on the high diffusivity of CO2 across the blood-brain barrier; 11CO2 is not predominant in the total tissue curve, even if the brain CO2 pool is big compared with other metabolites, due to its strong dilution through unlabeled CO2 from neuronal metabolism and diffusion from plasma. Conclusion: The two-compartment model presented here is also able to fit data of positron emission experiments and to extract specific glial metabolic fluxes. 11C-labeled acetate presents an alternative for faster measurements of glial oxidative metabolism compared to NMR, potentially applicable to human PET imaging. However, to quantify the relative value of the TCA cycle flux compared to the transmitochondrial flux, the chemical sensitivity of NMR is required. PET and NMR are thus complementary.

Cryptic diversity among Western Palearctic tree frogs: postglacial range expansion, range limits, and secondary contacts of three European tree frog lineages (Hyla arborea group).

We characterize divergence times, intraspecific diversity and distributions for recently recognized lineages within the Hyla arborea species group, based on mitochondrial and nuclear sequences from 160 localities spanning its whole distribution. Lineages of H. arborea, H. orientalis, H. molleri have at least Pliocene age, supporting species level divergence. The genetically uniform Iberian H. molleri, although largely isolated by the Pyrenees, is parapatric to H. arborea, with evidence for successful hybridization in a small Aquitanian corridor (southwestern France), where the distribution also overlaps with H. meridionalis. The genetically uniform H. arborea, spread from Crete to Brittany, exhibits molecular signatures of a postglacial range expansion. It meets different mtDNA clades of H. orientalis in NE-Greece, along the Carpathians, and in Poland along the Vistula River (there including hybridization). The East-European H. orientalis is strongly structured genetically. Five geographic mitochondrial clades are recognized, with a molecular signature of postglacial range expansions for the clade that reached the most northern latitudes. Hybridization with H. savignyi is suggested in southwestern Turkey. Thus, cryptic diversity in these Pliocene Hyla lineages covers three extremes: a genetically poor, quasi-Iberian endemic (H. molleri), a more uniform species distributed from the Balkans to Western Europe (H. arborea), and a well-structured Asia Minor-Eastern European species (H. orientalis).

Biological exposure indicators: quantification of biological variability using toxicokinetic modeling

Compartmental and physiologically based toxicokinetic modeling coupled with Monte Carlo simulation were used to quantify the impact of biological variability (physiological, biochemical, and anatomic parameters) on the values of a series of bio-indicators of metal and organic industrial chemical exposures. A variability extent index and the main parameters affecting biological indicators were identified. Results show a large diversity in interindividual variability for the different categories of biological indicators examined. Measurement of the unchanged substance in blood, alveolar air, or urine is much less variable than the measurement of metabolites, both in blood and urine. In most cases, the alveolar flow and cardiac output were identified as the prime parameters determining biological variability, thus suggesting the importance of workload intensity on absorbed dose for inhaled chemicals.

Haematopoietic stem cell transplantation: activity in Switzerland compared with surrounding European countries.

Haematopoietic stem cell transplantation (HSCT) is a highly specialised procedure used to treat malignancies of the lymphohaematopoietic system as well as some acquired and inherited disorders of the blood. This analysis by the Swiss Blood Stem Cell Transplantation Group, based on data from 2008-2011, describes, treatment rates in Switzerland for specific indications and compares this with data from Germany, France, Italy and the Netherlands, corrected for the size of the population. Differences in transplant rates, in rates for particular indications, and in the use of specific transplant technologies such as use of unrelated donors, use of cord blood or mismatched family donors are described. These data are put in correlation with donor availability from international registries and with number of transplant teams and number of procedures per team all corrected for population size.

ConnectomeViewer - Multi-Modal Multi-Level Network Visualization and Analysis.

Introduction: The field of Connectomic research is growing rapidly, resulting from methodological advances in structural neuroimaging on many spatial scales. Especially progress in Diffusion MRI data acquisition and processing made available macroscopic structural connectivity maps in vivo through Connectome Mapping Pipelines (Hagmann et al, 2008) into so-called Connectomes (Hagmann 2005, Sporns et al, 2005). They exhibit both spatial and topological information that constrain functional imaging studies and are relevant in their interpretation. The need for a special-purpose software tool for both clinical researchers and neuroscientists to support investigations of such connectome data has grown. Methods: We developed the ConnectomeViewer, a powerful, extensible software tool for visualization and analysis in connectomic research. It uses the novel defined container-like Connectome File Format, specifying networks (GraphML), surfaces (Gifti), volumes (Nifti), track data (TrackVis) and metadata. Usage of Python as programming language allows it to by cross-platform and have access to a multitude of scientific libraries. Results: Using a flexible plugin architecture, it is possible to enhance functionality for specific purposes easily. Following features are already implemented: * Ready usage of libraries, e.g. for complex network analysis (NetworkX) and data plotting (Matplotlib). More brain connectivity measures will be implemented in a future release (Rubinov et al, 2009). * 3D View of networks with node positioning based on corresponding ROI surface patch. Other layouts possible. * Picking functionality to select nodes, select edges, get more node information (ConnectomeWiki), toggle surface representations * Interactive thresholding and modality selection of edge properties using filters * Arbitrary metadata can be stored for networks, thereby allowing e.g. group-based analysis or meta-analysis. * Python Shell for scripting. Application data is exposed and can be modified or used for further post-processing. * Visualization pipelines using filters and modules can be composed with Mayavi (Ramachandran et al, 2008). * Interface to TrackVis to visualize track data. Selected nodes are converted to ROIs for fiber filtering The Connectome Mapping Pipeline (Hagmann et al, 2008) processed 20 healthy subjects into an average Connectome dataset. The Figures show the ConnectomeViewer user interface using this dataset. Connections are shown that occur in all 20 subjects. The dataset is freely available from the homepage (connectomeviewer.org). Conclusions: The ConnectomeViewer is a cross-platform, open-source software tool that provides extensive visualization and analysis capabilities for connectomic research. It has a modular architecture, integrates relevant datatypes and is completely scriptable. Visit www.connectomics.org to get involved as user or developer.

Integrating species distribution models (SDMs) and phylogeography for two species of Alpine Primula.

The major intention of the present study was to investigate whether an approach combining the use of niche-based palaeodistribution modeling and phylo-geography would support or modify hypotheses about the Quaternary distributional history derived from phylogeographic methods alone. Our study system comprised two closely related species of Alpine Primula. We used species distribution models based on the extant distribution of the species and last glacial maximum (LGM) climate models to predict the distribution of the two species during the LGM. Phylogeographic data were generated using amplified fragment length polymorphisms (AFLPs). In Primula hirsuta, models of past distribution and phylogeographic data are partly congruent and support the hypothesis of widespread nunatak survival in the Central Alps. Species distribution models (SDMs) allowed us to differentiate between alpine regions that harbor potential nunatak areas and regions that have been colonized from other areas. SDMs revealed that diversity is a good indicator for nunataks, while rarity is a good indicator for peripheral relict populations that were not source for the recolonization of the inner Alps. In P. daonensis, palaeo-distribution models and phylogeographic data are incongruent. Besides the uncertainty inherent to this type of modeling approach (e.g., relatively coarse 1-km grain size), disagreement of models and data may partly be caused by shifts of ecological niche in both species. Nevertheless, we demonstrate that the combination of palaeo-distribution modeling with phylogeographical approaches provides a more differentiated picture of the distributional history of species and partly supports (P. hirsuta) and partly modifies (P. daonensis and P. hirsuta) hypotheses of Quaternary distributional history. Some of the refugial area indicated by palaeodistribution models could not have been identified with phylogeographic data.

Characterization of Fas (Apo-1, CD95)-Fas ligand interaction.

The death-inducing receptor Fas is activated when cross-linked by the type II membrane protein Fas ligand (FasL). When human soluble FasL (sFasL, containing the extracellular portion) was expressed in human embryo kidney 293 cells, the three N-linked glycans of each FasL monomer were found to be essential for efficient secretion. Based on the structure of the closely related lymphotoxin alpha-tumor necrosis factor receptor I complex, a molecular model of the FasL homotrimer bound to three Fas molecules was generated using knowledge-based protein modeling methods. Point mutations of amino acid residues predicted to affect the receptor-ligand interaction were introduced at three sites. The F275L mutant, mimicking the loss of function murine gld mutation, exhibited a high propensity for aggregation and was unable to bind to Fas. Mutants P206R, P206D, and P206F displayed reduced cytotoxicity toward Fas-positive cells with a concomitant decrease in the binding affinity for the recombinant Fas-immunoglobulin Fc fusion proteins. Although the cytotoxic activity of mutant Y218D was unaltered, mutant Y218R was inactive, correlating with the prediction that Tyr-218 of FasL interacts with a cluster of three basic amino acid side chains of Fas. Interestingly, mutant Y218F could induce apoptosis in murine, but not human cells.

How Social Dominance Orientation affects union participation: The role of union identification and perceived union instrumentality

Bridging social dominance theory and labour studies, this field study investigated the mechanisms underpinning the relationship between rejection of group-based domination and participation in union activities. Respondents (N = 135) were members of a public sector union in California, that is, a hierarchy-attenuating institution. Results revealed that union identification mediated the negative relationship between social dominance orientation and active union participation. Moreover, the mediational effect of union identification was moderated by perceived union instrumentality (i.e. outcome- and process-based benefits afforded by the union), indicating that the relationship between union identification and participation was stronger among those union members who consider that the union affects workplace justice. The findings reveal the importance of both identity-based and instrumental motivations underlying union participation. The novelty of applying social dominance theory to union behaviour is underscored.

Labor market experience and well-being after firm closure. Survey evidence on displaced manufacturing workers in Switzerland

This study examines how plant closure affected individuals' careers and lives about two years after they lost their job. We analyze the displaced workers' reemployment prospects and study for reemployed workers the characteristics of their new jobs in terms of reemployment sectors, wages, and job quality. Additionally, we inquire how workers' sociability and subjective well-being were affected by job loss. Our analysis is based on our own survey conducted in Switzerland in 2011. The survey included the workforce of five manufacturing companies that had closed down two years earlier. We addressed the risk of biases typically prevailing with observational data by complementing it with register data from the public unemployment insurance. Moreover, we use a control group based on matched data from the Swiss Household Panel. We find that workers experience strongly diverging outcomes after plant closure: on the one hand, high proportions of the workers experience a smooth transition after plant closure. More than two-thirds of the workers returned to employment, more than half of them within less than six months. With respect to their social lives, we find that positive changes in relationships with their spouse, family and friends are more frequent than negative changes. On the other hand, for a small group of workers plant closure had a detrimental effect. Close to twenty percent remained unemployed. About ten percent of the workers were long-term unemployed and subsequently often were reemployed in jobs of lower quality. Unemployed workers and workers who dropped out of the labor force were particularly prone to find their subjective well-being decreasing. The most vulnerable subgroup in our study were workers over 55. This result stands in striking contrast to a large body of literature that considers labor market institutions to be primarily biased against young workers. Our findings show that older workers not only take longer to find a job but are also less likely to return to employment. Moreover, if they manage to find a job, they experience the severest cuts in wages and job quality of all cohorts. From a life-course perspective this result is remarkable since it shows that workers are not protected from hardship in their late careers. In light of the current demographic changes this finding may have important policy implications. -- Cette étude analyse l'impact des fermetures d'entreprises sur les travailleurs licenciés. Plus précisément, nous examinons les chances de réinsertion des travailleurs dans le marché du travail et - pour ceux qui l'ont fait avec succès - dans quels secteurs, pour quels salaires et avec quelle qualité d'emploi ils sont réengagés. Nous nous intéressons également aux répercussions engendrées par la perte de l'emploi sur la sociabilité et le bien-être subjectif des travailleurs concernés. Notre analyse se base sur les données d'une enquête que nous avons menée en 2011. Cette enquête cible le personnel de cinq entreprises industrielles suisses qui avaient fermé leurs portes deux ans auparavant. Pour dépasser les biais typiques liés aux données d'observation, nous utilisons en complément des données administratives issues de l'assurance chômage publique. De plus, nous utilisons un groupe de contrôle basé sur des données appariées provenant du Panel Suisse de Ménage. Nos analyses montrent des résultats fortement contrastés. D'un côté, la majeure partie des travailleurs ont vécu une transition professionnelle plutôt facile : plus des deux tiers des personnes ont retrouvé un travail et parmi elles plus de la moitié en moins de six mois. Par rapport aux relations sociales, tant avec leur partenaire, qu'avec les membres de leur famille et leurs amis, les changements expérimentés étaient plus fréquemment positifs que négatifs. De l'autre côté, cependant, pour une petite partie de travailleurs la fermeture de leur entreprise a eu des conséquences très négatives sur leur carrière et leur bien-être. Au moment de notre enquête, presque vingt pourcents des travailleurs étaient au chômage. Les personnes au chômage et celles qui avaient quitté le marché du travail ont été particulièrement affectées par une diminution de leur bien-être subjectif. Les plus vulnérables parmi les travailleurs licenciés étaient ceux qui étaient âgés de plus de 55 ans. Notre analyse montre que les travailleurs âgés ont beaucoup moins fréquemment retrouvé un travail. Pour les personnes de plus de 55 ans qui ont tout de même retrouvé un emploi, la réinsertion a durée plus longtemps, les pertes de salaire étaient plus conséquentes et la diminution de la qualité de l'emploi plus grande que pour les autres cohortes. Au vu des changements démographiques actuels, ce résultat interpellant peut avoir des implications politiques importantes.

Facing Structural Disadvantage: The Role of Ingroup Connectedness

This thesis focuses on the social-psychological factors that help coping with structural disadvantage, and specifically on the role of cohesive ingroups and the sense of connectedness and efficacy they entail in this process. It aims to complement existing group-based models of coping that are grounded in a categorization perspective to groups and consequently focus exclusively on the large-scale categories made salient in intergroup contexts of comparisons. The dissertation accomplishes this aim through a reconsideration of between-persons relational interdependence as a sufficient and independent antecedent of a sense of groupness, and the benefits that a sense of group connectedness in one's direct environment, regardless of the categorical or relational basis of groupness, might have in the everyday struggles of disadvantaged group members. The three empirical papers aim to validate this approach, outlined in the first theoretical introduction, by testing derived hypotheses. They are based on data collected with youth populations (15-30) from three institutions in French-speaking Switzerland within the context of a larger project on youth transitions. Methods of data collection are paper-pencil questionnaires and in-depth interviews with a selected sub-sample of participants. The key argument of the first paper is that members of socially disadvantaged categories face higher barriers to their life project and that a general sense of connectedness, either based on categorical identities or other proximal groups and relations, mitigates the feeling of powerlessness associated with this experience. The second paper develops and tests a model that defines individual needs satisfaction as antecedent of self-group bonds and the efficacy beliefs derived from these intragroup bonds as the mechanism underlining the role of ingroups in coping. The third paper highlights the complexities that might be associated with the construction of a sense of groupness directly from intergroup comparisons and categorization-based disadvantage, and points out a more subtle understanding of the processes underling the emergence of groupness out of the situation of structural disadvantage. Overall, the findings confirm the central role of ingroups in coping with structural disadvantage and the importance of an understanding of groupness and its role that goes beyond the dominant focus on intergroup contexts and categorization processes.

Development of the Positive Emotions Program for Schizophrenia (PEPS): an intervention to improve pleasure and motivation in schizophrenia

Objectives: The efficacy of drug-based treatments and psychological interventions on the primary negative symptoms of schizophrenia remains limited. Recent literature has distinguished negative symptoms associated with a diminished capacity to experience, from those associated with a limited capacity for expression. The positive emotions program for schizophrenia (PEPS) is a new method that specifically aims to reduce the syndrome of a diminished capacity to experience. Methods: The intervention's vital ingredients were identified through a literature review of emotion in schizophrenia and positive psychology. The program has been beta-tested on various groups of health-care professionals. Results: A detailed description of the final version of PEPS is presented here. The French version of the program is freely downloadable. Conclusion: PEPS is a specific, short, easy to use, group-based intervention to improve pleasure, and motivation in schizophrenia. It was built considering a recovery-oriented approach to schizophrenia.

Homology modeling and metabolism prediction of human carboxylesterase-2 using docking analyses by GriDock: a parallelized tool based on AutoDock 4.0.

Metabolic problems lead to numerous failures during clinical trials, and much effort is now devoted to developing in silico models predicting metabolic stability and metabolites. Such models are well known for cytochromes P450 and some transferases, whereas less has been done to predict the activity of human hydrolases. The present study was undertaken to develop a computational approach able to predict the hydrolysis of novel esters by human carboxylesterase hCES2. The study involved first a homology modeling of the hCES2 protein based on the model of hCES1 since the two proteins share a high degree of homology (congruent with 73%). A set of 40 known substrates of hCES2 was taken from the literature; the ligands were docked in both their neutral and ionized forms using GriDock, a parallel tool based on the AutoDock4.0 engine which can perform efficient and easy virtual screening analyses of large molecular databases exploiting multi-core architectures. Useful statistical models (e.g., r (2) = 0.91 for substrates in their unprotonated state) were calculated by correlating experimental pK(m) values with distance between the carbon atom of the substrate's ester group and the hydroxy function of Ser228. Additional parameters in the equations accounted for hydrophobic and electrostatic interactions between substrates and contributing residues. The negatively charged residues in the hCES2 cavity explained the preference of the enzyme for neutral substrates and, more generally, suggested that ligands which interact too strongly by ionic bonds (e.g., ACE inhibitors) cannot be good CES2 substrates because they are trapped in the cavity in unproductive modes and behave as inhibitors. The effects of protonation on substrate recognition and the contrasting behavior of substrates and products were finally investigated by MD simulations of some CES2 complexes.